AI Engineering Architect
Responsibilities
AI Architecture & Engineering
- Define and own AI reference architectures for generative AI, agentic systems, and AI augmented applications
- Architect scalable solutions using LLMs, multi agent systems, orchestration frameworks, and AI pipelines
- Design AI platforms supporting model serving, prompt management, RAG, and workflow orchestration
- Establish architectural standards for performance, scalability, reliability, and cost efficiency
Platform Engineering & Integration
- Build reusable AI components for LLM integration, vector search, embeddings, and inference services
- Enable secure and scalable deployment using Kubernetes, serverless platforms, and CI/CD pipelines
- Integrate AI capabilities into enterprise systems using APIs, SDKs, and event driven architectures
- Collaborate with QE teams to embed AI into test automation, test data generation, and intelligent validation
Engineering Governance & Quality
- Define architectural guardrails for model lifecycle, versioning, monitoring, and rollback
- Ensure adherence to non functional requirements including performance, observability, and fault tolerance
- Leverage observability tools to monitor model performance and drift
- Review designs and implementations for architectural compliance and code quality
- Mentor engineers and architects on AI engineering best practices
Core Platforms, Frameworks & Tooling
- LLM and foundation model platforms (e.g., AWS Bedrock, Azure OpenAI, Vertex AI)
- Agentic AI and orchestration frameworks (LangChain, LangGraph, CrewAI, AutoGen, Google ADK or equivalent)
- Vector databases and search technologies (OpenSearch, Pinecone, FAISS, Weaviate)
- Model lifecycle and deployment tooling (Kubernetes, containers, serverless runtimes)
- CI/CD and MLOps tooling for AI pipelines (GitHub Actions, Azure DevOps, Jenkins)
- Observability and monitoring tooling for AI systems (OpenTelemetry, Prometheus, Grafana)
Client Orientation & Leadership
- Partner with product and engineering teams to identify AI opportunities and shape roadmaps
- Support client workshops, RFPs, and solution presentations
- Mentor engineers on AI/ML/Gen AI best practices and emerging technologies
- Translate complex AI concepts into business-friendly narratives.
Technical and Professional Requirements
- 13+ years of experience in software engineering with 3+ years in AI with strong architecture ownership
- Proven experience designing and implementing enterprise-scale AI engineering or MLOps platforms
- Strong hands on experience with LLMs, prompt engineering, RAG, and agent frameworks
- Proficiency in Python, AI frameworks, and cloud-native AI services
- Experience in Kubernetes, CI/CD, and secure deployment of AI models
- Experience integrating AI capabilities into enterprise scale systems
Good to Have Skills
- Experience with multi agent orchestration and autonomous workflows
- Knowledge of model observability and monitoring tooling
- Exposure to QE platforms, test automation frameworks, or AI assisted testing
- Domain experience in regulated industries such as BFSI, Healthcare, Telecom
- Cloud and AI certifications
Preferred Skills
- Agile Testing – ALL
- AI/ML Solution Architecture and Design
- Databricks AI Engineering Services
- LLMOps
- MLOps
- Model Optimization
- Model Support
- Conversational AI Platform
- chains
- Generative AI for Data Analytics
- Prompt Engineering
- Architecture – ALL
- Digital Architecture
Educational Requirements
Bachelor of Engineering
GE eTerra
Responsibilities
Key Responsibilities
Grid Operations & Control Center Expertise
- Act as a trusted subject matter expert for transmission and distribution operations, including real time grid monitoring, switching activities, outage coordination, restoration planning, and control room procedures.
- Provide practical insight into how operators manage voltage conditions, equipment loading, alarms, contingencies, and coordination with neighboring utilities and market operators.
Operational Systems & Data Assessment
- Evaluate operational and enterprise systems across EMS, GMS, SCADA, DMS/ADMS, OMS, historians, asset platforms, market systems, and field technologies.
- Identify where system boundaries, data latency, or organizational handoffs limit operational awareness or delay effective decision making.
AI & Advanced Analytics Use Case Development
- Identify operational scenarios where AI and advanced analytics can support grid operations, including:
o Alarm prioritization and reduction of nuisance alarms
o Detection of abnormal grid behavior
o Correlation of events across transmission, distribution, and field systems
o Improved awareness during outages, restorations, and abnormal operating conditions
o Visibility into emerging asset and reliability risks
Architecture & Data Strategy Collaboration
- Work with operations, OT, IT, and data teams to define secure and reliable data sharing patterns that support near real time operational insight without disrupting control system integrity.
- Translate operational requirements into analytics and AI needs, including data quality expectations, contextual tagging, event streams, model inputs, operator review points, and explainability considerations.
GE ETERRA GMS / EMS Advisory
- Provide guidance on how GE ETERRA GMS and EMS are typically configured and used within utility control centers.
- Advise on integration touchpoints, operational workflows, and data considerations relevant to reliability monitoring, visualization, analysis, and control functions.
Roadmap & Compliance Alignment
- Contribute to long term planning for control center and situational awareness modernization.
- Ensure all recommended approaches align with established utility operating practices and applicable reliability and regulatory expectations, including NERC and FERC standards.
Additional Responsibilities
Preferred Qualifications
- Experience supporting grid modernization or control center transformation initiatives.
- Familiarity with renewable integration challenges, contingency analysis, state estimation, or grid reliability analysis.
- Exposure to AI platforms, advanced analytics, edge computing, or digital grid initiatives within utility environments.
- Knowledge of utility cybersecurity and secure operational data sharing practices.
Technical and Professional Requirements
Required Qualifications
- Bachelor’s degree in Electrical Engineering, Power Systems, Computer Engineering, or a related discipline.
- 10+ years of experience supporting electric utility operations, control centers, or grid technology programs.
- Strong understanding of transmission and distribution operations, including switching, outage response, restoration, equipment loading, and voltage management.
- Hands on experience with GE ETERRA GMS and/or EMS in production utility environments.
- Experience working across OT and IT systems such as EMS, SCADA, DMS/ADMS, OMS, GIS, AMI, asset management, historians, DER platforms, or market systems.
- Ability to communicate effectively with operators, engineers, IT/OT teams, and leadership stakeholders.
Preferred Skills
- SCADA
Educational Requirements
Master Of Engineering,Master Of Technology,Bachelor of Engineering,Bachelor Of Technology
Oracle CPQ Consultant
Responsibilities
A day in the life of an Infoscion
- As part of the Infosys consulting team, your primary role would be to get to the heart of customer issues, diagnose problem areas, design innovative solutions and facilitate deployment resulting in client delight.
- You will develop a proposal by owning parts of the proposal document and by giving inputs in solution design based on areas of expertise.
- You will plan the activities of configuration, configure the product as per the design, conduct conference room pilots and will assist in resolving any queries related to requirements and solution design
- You will conduct solution/product demonstrations, POC/Proof of Technology workshops and prepare effort estimates which suit the customer budgetary requirements and are in line with organization’s financial guidelines
- Actively lead small projects and contribute to unit-level and organizational initiatives with an objective of providing high quality value adding solutions to customers.
If you think you fit right in to help our clients navigate their next in their digital transformation journey, this is the place for you!
Additional Responsibilities
- Collaborate with the technical leads to design and create all required software to achieve the requirements
- Develop code (BML, BMLQ, JavaScript, Java, etc.) to satisfy product specifications and requirements
- Develop PL/SQL, SQL, interfaces and reports as needed to support the requested functionality
- Document all technical design decisions and code in design documents
- Work with Oracle Support Services to resolve issues
- Develop integrated test scenarios, identify test data and execute test scenarios.
- Troubleshoot, debug and resolve issues identified and document results.
- Initiate and participate in production rollout processes
- Excellent communication and presentation skills
Technical and Professional Requirements
- We are looking for candidates having a minimum of 5 years’ experience with Oracle CPQ (Big Machines) including BML and BMQL
- Blend of CPQ Design and development experience
- JavaScript, JQuery, HTML, CSS, XML
- Strong Product Knowledge
- Should be able to work as CPQ Designer & Developer as per project requirement
- Knowledge and ability to follow SDLC as well as Agile methodologies
- Experience in standard operating procedures to perform pre and post production support activities
Preferred Skills
- CPQ Cloud
Educational Requirements
ME,MSc,MTech,Bachelor of Engineering,BSc,BTech
Data Engineering AI Architect
Responsibilities
Key Responsibilities
Data Architecture for AI
- Architect AI data foundations including ingestion, transformation, enrichment, and serving layers
- Design data architectures supporting RAG, embeddings, feature stores, and training data pipelines
- Define standards for data quality, lineage, versioning, and governance for AI workloads
- Ensure data platforms support scalability, performance, and low latency AI use cases
Data Quality & Assurance
- Architect data validation and testing frameworks for AI and analytics systems
- Enable automated validation for data correctness, drift, bias, and completeness
- Define test strategies for data migration, data transformation, and AI readiness
- Collaborate with QE teams to embed data assurance into pipelines and platforms
Platform & Integration
- Integrate data platforms with AI services and analytics tools
- Define secure access patterns for data used in training, inference, and evaluation
- Enable observability for data pipelines and AI data consumption
- Guide teams on best practices for AI enabled BI and data driven systems
Core Platforms, Frameworks & Tooling
- LLM and foundation model platforms (e.g., AWS Bedrock, Azure OpenAI, Vertex AI)
- Agentic AI and orchestration frameworks (LangChain, LangGraph, CrewAI, AutoGen, Google ADK or equivalent)
- CI/CD and MLOps tooling for AI pipelines (GitHub Actions, Azure DevOps, Jenkins)
- Data ingestion and processing platforms (Spark, Kafka, cloud native ETL/ELT frameworks)
- Data quality and validation frameworks (Great Expectations, Amazon Deequ, custom reconciliation frameworks)
- Feature stores and embedding pipelines (Feast, embedding generation pipelines, vector databases)
- Data drift, bias, and consistency monitoring tools (Evidently, statistical data quality monitors)
- Metadata, lineage, and governance platforms (DataHub, Apache Atlas, cloud data catalogs)
- AI enabled analytics and Generative BI platforms (Power BI with Copilot, semantic layers, NLQ enabled BI)
- Cloud native data platforms and storage (object storage, distributed query engines, data lakehouses)
Client Orientation & Leadership
- Partner with product and engineering teams to identify Data for AI opportunities and shape roadmaps
- Support client workshops, RFPs, and solution presentations
- Mentor engineers on AI/ML/Gen AI best practices and emerging technologies
- Translate complex AI concepts into business-friendly narratives
Technical and Professional Requirements
Must Have Qualifications
- 13+ years of experience in software engineering with 3+ years in AI with strong architecture ownership
- Strong expertise in data engineering, data quality, and data governance
- Experience supporting AI use cases such as RAG, feature engineering, and model training
- Proficiency with data platforms, cloud services, and distributed data systems
- Solid understanding of QE practices related to data validation and testing
Good to Have Skills
- Experience with Generative BI or AI assisted analytics
- Knowledge of metadata management, lineage tools, and data observability
- Exposure to AI ethics and bias in data sets
- Cloud data certifications
Preferred Skills
- AI/ML Solution Architecture and Design
- Databricks AI Engineering Services
- LLMOps
- Databricks Machine Learning
- Architecture – ALL
- Databricks
- Data Architecture – Metadata Management
- Digital Architecture
- IBM Infosphere Datastage – Datastage
Educational Requirements
Bachelor of Engineering
SAP SF ECP Functional Lead
Responsibilities
A day in the life of an Infoscion
- As part of the Infosys consulting team, your primary role would be to get to the heart of customer issues, diagnose problem areas, design innovative solutions and facilitate deployment resulting in client delight.
- You will develop a proposal by owning parts of the proposal document and by giving inputs in solution design based on areas of expertise.
- You will plan the activities of configuration, configure the product as per the design, conduct conference room pilots and will assist in resolving any queries related to requirements and solution design
- You will conduct solution/product demonstrations, POC/Proof of Technology workshops and prepare effort estimates which suit the customer budgetary requirements and are in line with organization’s financial guidelines
- Actively lead small projects and contribute to unit-level and organizational initiatives with an objective of providing high quality value adding solutions to customers.
If you think you fit right in to help our clients navigate their next in their digital transformation journey, this is the place for you!
Additional Responsibilities
- Excellent Communication & Presentation skills and must be a team player
- System configuration in accordance with Solution Design & Configuration Workbook / Business Blueprint
- Expertise in translations and must uploaded translation packs for data models configuration and MDF.
- Preparation & Execution of Test Cases / Test Plans / Test scripts
- Strong learning ability – agility and willingness to acquire new competencies and adapt quickly to new tasks and environments
- should have knowledge of Knowledge of SAP HCM Familiar with Integration activities
- Experience with SAP Custom interfaces and reports.
Location of posting – Infosys Ltd. is committed to ensuring you have the best experience throughout your journey with us.
We currently have open positions in a number of locations across India – Bangalore, Pune, Hyderabad, Chennai, Chandigarh, Trivandrum, Indore, Nagpur, Mangalore, Noida, Bhubaneswar, Kolkata, Coimbatore, Jaipur, Vizag, Mysore, Kolkata, Hubli.
While we work in accordance with business requirements, we shall strive to offer you the location of your choice, where possible.
Technical and Professional Requirements
- Must have 12+ years of experience with Information Technology with 8 years of consulting experience in SuccessFactors / HCM.
- Experience in implementing US Payroll with good understanding of local and global payroll regulations.
- Must be certified in Employee Central Payroll and at least 2 full cycle (end-to-end) implementations of SuccessFactors Employee Central Payroll.
- Proven experience as a SuccessFactors Systems Analyst or similar role, with a deep understanding of SAP SF modules and functionality.
- Proficient in configuring and customizing SuccessFactors modules to meet business requirements.
- Expertise in providing Consulting Services to Global organizations in HCM Best Practices and help clients to migrate to SAP HCM Cloud solutions
- Translate requirements into System Configuration Objects and create Solution Design for SuccessFactors Employee Management Solution in compliance with the Best Practices
- Hands-on all the Data Models and excellent knowledge of XML.
Preferred Skills
- SAP HCM
- SAP Success Factors
Educational Requirements
Bachelor of Engineering
AI Trust and Governance Architect
Responsibilities
Key Responsibilities
AI Assurance Architecture
- Architect platforms and frameworks for AI assurance, evaluation, and benchmarking
- Design systems for LLM, agent, and RAG evaluation across functional, non functional, and risk dimensions
- Define architectural patterns for Responsible AI, bias detection, explainability, and safety validation
- Build reusable assurance components supporting Business Assurance, Risk Assurance, and Reliability
Security, Reliability & Governance
- Architect AI testing and validation for security, privacy, prompt injection, and adversarial robustness
- Integrate red teaming, threat simulation, and chaos style validation for AI systems
- Define governance mechanisms for model usage, auditability, traceability, and compliance
- Ensure AI systems meet enterprise standards for resilience, fault tolerance, and observability
Platform & Engineering Enablement
- Design AI assurance platforms supporting automated test execution, reporting, and insights
- Enable integration with CI/CD pipelines to enforce AI quality gates
- Collaborate with QE engineering teams to embed AI assurance into the SDLC
- Mentor teams on AI risk identification and mitigation from an engineering perspective
Core Platforms, Frameworks & Tooling
- LLM and AI evaluation frameworks (PromptFoo, DeepEval, custom LLM evaluation harnesses)
- Prompt, RAG, and agent validation tooling (prompt testing frameworks, retrieval accuracy validators, agent workflow evaluators)
- Responsible AI and model risk tooling (Fairlearn, SHAP, Explainable AI libraries, toxicity and bias scanners)
- Security and adversarial testing tools for AI systems (PyRIT, Garak)
- AI red teaming and threat simulation frameworks (automated red team scripts, adversarial test suites for LLMs and agents)
- AI assurance automation and QE frameworks (Galileo)
- Observability for AI behavior and drift (Langfuse, Arize, Evidently, custom telemetry dashboards)
Client Orientation & Leadership
- Partner with product and engineering teams to identify AI Assurance opportunities and shape roadmaps
- Support client workshops, RFPs, and solution presentations
- Mentor engineers on AI/ML/Gen AI best practices and emerging technologies
- Translate complex AI concepts into business-friendly narratives
Technical and Professional Requirements
Must Have Qualifications
- 13+ years of experience in software engineering with 3+ years in AI with strong architecture ownership
- Hands on expertise in AI/ML systems, LLM evaluation, and assurance frameworks
- Experience with AI red teaming, model risk management, or AI audit tooling
- Strong understanding of Responsible AI, AI risks, and governance principles
- Experience with security testing, adversarial testing, and reliability engineering
- Proficiency in Python, automation frameworks, and cloud platforms
Good to Have Skills
- Knowledge of regulatory or compliance considerations for AI systems
- Exposure to performance engineering, chaos engineering, or resilience testing for AI
- Contributions to internal platforms, frameworks, or standards
Preferred Skills
- Governance Risk and Compliance
- Audits
- Workflow
- Assurance
- traditional ai ml
- Conversational AI Platform
- retrieval augmented generation (rag)
- Prompt Engineering
- Responsible AI
- Data Governance
Educational Requirements
Bachelor of Engineering
SAP BRIM SOM Consultant
Responsibilities
A day in the life of an Infoscion
- As part of the Infosys consulting team, your primary role would be to get to the heart of customer issues, diagnose problem areas, design innovative solutions and facilitate deployment resulting in client delight.
- You will develop a proposal by owning parts of the proposal document and by giving inputs in solution design based on areas of expertise.
- You will plan the activities of configuration, configure the product as per the design, conduct conference room pilots and will assist in resolving any queries related to requirements and solution design
- You will conduct solution/product demonstrations, POC/Proof of Technology workshops and prepare effort estimates which suit the customer budgetary requirements and are in line with organization’s financial guidelines
- Actively lead small projects and contribute to unit-level and organizational initiatives with an objective of providing high quality value adding solutions to customers.
If you think you fit right in to help our clients navigate their next in their digital transformation journey, this is the place for you!
Additional Responsibilities
- Ability to work with clients to identify business challenges and contribute to client deliverables by refining, analyzing, and structuring relevant data
- Awareness of latest technologies and trends
- Logical thinking and problem solving skills along with an ability to collaborate
- Ability to assess the current processes, identify improvement areas and suggest the technology solutions
- One or two industry domain knowledge
Location of posting – Infosys Ltd. is committed to ensuring you have the best experience throughout your journey with us.
We currently have open positions in a number of locations across India – Bangalore, Pune, Hyderabad, Chennai, Chandigarh, Trivandrum, Indore, Nagpur, Mangalore, Noida, Bhubaneswar, Kolkata, Coimbatore, Jaipur.
While we work in accordance with business requirements, we shall strive to offer you the location of your choice, where possible.
Technical and Professional Requirements
- 9+ years of work experience (certification is a preferred) in SAP Billing and Revenue Innovation Management (BRIM) solution.
- Experience in SAP Subscription Billing (SOM) solution is mandatory.
- Experience of working in at least 2 end to end implementation in SAP BRIM area.
- Experience in delivering BRIM related consulting project activities, ranging from business requirements gathering through final project deployment through medium- to long-term engagements.
- Experience in Supporting Business Process Operational activities by providing ongoing operational, maintenance, and enhancements to existing production enabled customers.
- Good working knowledge in Subscription Order Management and Convergent Invoicing.
- End-to- end configuration and customization knowledge in the areas of SAP CRM, Convergent Charging, and Convergent Invoicing.
- Experience working in Subscription area for any industry.
Preferred Skills
- SAP BRIM – CRM SOM
Educational Requirements
Bachelor of Engineering
AI Strategic Consultant
Responsibilities
Lead end‑to‑end enterprise QE transformation by assessing current capabilities, benchmarking maturity, and defining AI‑first target-state blueprints across people, process, and technology. Design intelligent governance and operating models that embed predictive, autonomous quality practices aligned to business outcomes, while driving rapid value through early wins. Enable sustainable change through executive alignment, change management, transition and knowledge‑transfer strategies, and reduced dependency on consulting support. Additionally, support growth through C‑suite advisory, pre‑sales leadership, creation of proprietary IP, and market shaping via thought leadership and industry engagement.
Additional Responsibilities
Good‑to‑Have Skills
These enhance differentiation and future‑proof the role but are not strictly required for core execution:
AI‑driven quality engineering advisory
Guiding adoption of intelligent testing, predictive risk analytics, and autonomous quality capabilities.
AI risk assurance and trust frameworks
Understanding AI model quality, bias detection, and data quality as QE expands into AI‑enabled products.
Advanced quality intelligence and analytics mindset
Leveraging observability, telemetry, and production insights to influence testing and governance strategies.
Innovation and value‑realization focus
Ability to distinguish genuine AI‑driven lift from vendor hype and steer clients toward pragmatic value outcomes.
Technical and Professional Requirements
Mandatory Skills
These are essential for baseline success in an enterprise QE advisory leadership role:
15+ years of QE experience with enterprise-scale transformation exposure
Demonstrated ability to lead and advise large, complex organisations.
QE strategy and operating model design
Defining multi‑year QE roadmaps, governance frameworks, and risk‑based quality strategies.
Quality economics expertise
Cost-of-quality analysis, ROI articulation, and tying QE outcomes to business metrics (cost, speed, resilience).
Risk-based and outcome-driven QE leadership
Driving measurable improvements in defect leakage, release velocity, reliability, and compliance.
Modern engineering fluency (at advisory level)
Strong understanding of DevOps, CI/CD, cloud‑native, and platform engineering concepts to translate technical complexity into actionable quality guidance (without hands-on pipeline work).
Preferred Skills
- Responsible AI by Design
- generative ai
- retrieval augmented generation (rag)
- explainable ai
- RestAssured
- Architecture – ALL
- Artificial Intelligence – ALL
- Automated Testing – ALL
- Test automation framework design
- Digital Architecture
- Mobile Test Automation process
- BDD
- TDD
- ATDD for Mobile Test Automation
Educational Requirements
Bachelor of Engineering
SAP FSCM Consultant
Responsibilities
A day in the life of an Infoscion
- As part of the Infosys consulting team, your primary role would be to get to the heart of customer issues, diagnose problem areas, design innovative solutions and facilitate deployment resulting in client delight.
- You will develop a proposal by owning parts of the proposal document and by giving inputs in solution design based on areas of expertise.
- You will plan the activities of configuration, configure the product as per the design, conduct conference room pilots and will assist in resolving any queries related to requirements and solution design
- You will conduct solution/product demonstrations, POC/Proof of Technology workshops and prepare effort estimates which suit the customer budgetary requirements and are in line with organization’s financial guidelines
- Actively lead small projects and contribute to unit-level and organizational initiatives with an objective of providing high quality value adding solutions to customers.
If you think you fit right in to help our clients navigate their next in their digital transformation journey, this is the place for you!
Additional Responsibilities
- Ability to develop value-creating strategies and models that enable clients to innovate, drive growth and increase their business profitability
- Good knowledge on software configuration management systems
- Awareness of latest technologies and Industry trends
- Logical thinking and problem-solving skills along with an ability to collaborate
- Understanding of the financial processes for various types of projects and the various pricing models available
- Ability to assess the current processes, identify improvement areas and suggest the technology solutions
- One or two industry domain knowledge
- Client Interfacing skills
- Project and Team management
We currently have open positions in a number of locations across India – Bangalore, Pune, Hyderabad, Chennai, Chandigarh, Trivandrum, Indore, Nagpur, Mangalore, Noida, Bhubaneswar, Kolkata, Coimbatore, Jaipur, Mysore, Hubli, Vizag.
While we work in accordance with business requirements, we shall strive to offer you the location of your choice, where possible.
Technical and Professional Requirements
- 5+ years of SAP FSCM – Credit management (FIN-FSCM-CR) with key focus on Credit master data, Credit Rules engine, Score& Rating along with Risk of losses (receivables), XML interfaces with SAP SD, SAP FIN.
- Specialized in SAP technical, functional and business experience in order-to- cash, ecommerce B2B.
- Deep business & working experience in OTC, sales fulfillment, consumer, digital media and payment processing.
- Certified SAP configurator with extensive & deep knowledge of SAP R/3, ECC 6.0.
- Exposure to SAP Advanced Planning, GTS, EAI, XML, etc.
- Has worked on API with external partners or if not, built interfaces entailing sFTP and real- time integrations.
- Savvy with the latest technology and standards practiced in market.
- Basic debugging skills as well as ability to read simple ABAP codes. AP Controlling, Technology->SAP Functional->SAP FSCM, Technology->SAP Functional->SAP Finance
Preferred Skills
- SAP FSCM
Educational Requirements
Bachelor of Engineering
GCP BigQuery Developer
Responsibilities
Design, develop, and optimize BigQuery-based data warehouses and data marts
Build and maintain ETL/ELT pipelines using GCP services
Write efficient, complex SQL queries for data transformation and analysis
Work with Cloud Composer (Airflow), Dataflow, or Dataproc for pipeline orchestration
Perform data modelling (star/snowflake schema) for analytics use cases
Optimize query performance and manage BigQuery cost efficiency
Integrate data from various sources (APIs, Cloud Storage, databases, streaming sources)
Implement data validation, quality checks, and monitoring mechanisms
Collaborate with data analysts, data scientists, and business stakeholders
Ensure security and governance best practices within GCP
Additional Responsibilities
Experience with CI/CD tools (Cloud Build, Jenkins, GitHub Actions)
Knowledge of data visualization tools (Looker, Tableau, Power BI)
Familiarity with streaming data pipelines (Pub/Sub)
Experience with Infrastructure as Code (Terraform)
Understanding of data governance and access control in GCP
Bachelor’s degree in Computer Science, IT, or related field
GCP certifications (e.g., Professional Data Engineer) are a plus
Technical and Professional Requirements
Strong experience with Google BigQuery
Advanced proficiency in SQL
Hands-on experience with GCP services:
BigQuery
Cloud Storage
Dataflow / Dataproc
Cloud Composer (Airflow)
Experience in ETL/ELT pipeline development
Good understanding of data warehousing concepts
Familiarity with Python or PySpark for data processing
Experience in performance tuning and query optimization
Knowledge of data partitioning and clustering in BigQuery
Preferred Skills
- GCP Database
Educational Requirements
Bachelor of Engineering