Data Engineer
- AWS, Snowflake, Spark/PySpark, Python, SQL, Airflow/Astronomer, Data Engineering, ETL/ELT

Location:
Bangalore No. of resumes Required:1 Years of

Experience:
5-8 Years Primary

Skills:
AWS, Snowflake, Spark/PySpark, Python, SQL, Airflow/Astronomer, Data Engineering, ETL/ELT Job Title: Data Engineer Function Data Engineering / Enterprise Data Platform Engineering Role Summary We are seeking a highly experienced Data Engineer to design, build, optimize, and support enterprise-scale data platforms and data products. This is a hands-on delivery role requiring deep expertise across AWS, Snowflake, Spark, Python, SQL, and Airflow/Astronomer. The successful candidate should be capable of contributing immediately to production workloads with minimal onboarding and possess proven experience delivering large-scale, production-grade data platforms.

Key Responsibilities
• Design, develop, and maintain scalable and resilient data pipelines and data products.
• Build and optimize ELT/ETL frameworks using Spark, Python, SQL, Snowflake, and AWS.
• Develop and support batch, streaming, and event-driven data processing solutions.
• Implement and maintain workflow orchestration using Airflow/Astronomer.
• Deliver production-grade data products with strong focus on reliability, security, and performance.
• Optimize Snowflake workloads, storage, compute utilization, and query performance.
• Design scalable data models supporting analytics, AI, and operational use cases.
• Implement data quality, observability, governance, and monitoring capabilities.
• Build reusable frameworks and engineering accelerators.
• Support CI/CD pipelines, infrastructure automation, testing, deployment, and operational excellence.
• Collaborate with platform engineers, architects, analytics teams, and business stakeholders.
• Contribute to AI-ready data architecture and support Agentic AI enablement initiatives Primary Skills (Must Have) Data Engineering




• Modern Data Engineering
• Data Architecture
• Lakehouse Architecture
• Data Mesh
• Data Products
• Data Modeling
• ETL / ELT
• Batch Processing
• Streaming Processing
• Data Warehousing
• Distributed Data Processing
• Python
• SQL
• Spark / PySpark Cloud & Data Platforms
• AWS Cloud
• Snowflake
• Data Lakes
• Data Sharing
• Performance Optimization
• Data Security
• Data Governance
• Metadata Management
• Data Quality
• Data Lineage Orchestration & DevOps
• Airflow / Astronomer
• CI/CD
• Git
• Infrastructure as Code (IaC)
• DataOps
• Automated Testing
• Monitoring & Operational Excellence Secondary Skills (Nice to Have) AI & Modern Data Ecosystem
• Generative AI
• Agentic AI
• Large Language Models (LLMs)
• Model Context Protocol (MCP)
• Retrieval-Augmented Generation (RAG)
• AI-Ready Data Architecture
• Semantic Layer
• Data Consumption Patterns Advanced Data & Platform Engineering
• Kafka
• Event-Driven Architecture
• Real-Time Data Processing
• Multi-Cloud Environments
• Platform Observability
• Cost Optimization Analytics & Consumption
• Power BI
• Semantic Models
• Self-Service Analytics
• Data Products Integration & Application Development
• APIs
• Microservices
• Data Services Integration
• React Domain Experience
• Retail
• eCommerce
• Supply Chain
• Inventory Management
• Customer Analytics Key Competencies
• Strong problem-solving and analytical skills.




• Ability to translate business requirements into technical solutions.
• Robust focus on cloud cost optimization and operational efficiency.
• Ability to ensure data quality, consistency, and governance across the platform.
• Strong ownership mindset toward platform stability and SLA adherence.
• Strong decision-making capability in ambiguous and evolving environments.
• Ability to balance short-term delivery goals with long-term architectural sustainability.
• Effective stakeholder communication and collaboration skills. Experience & Qualifications
• Bachelor's degree in Engineering or related discipline.
• Master's degree in Computer Science or Information Technology preferred.
• 5-8 years of hands-on Data Engineering experience.
• Strong experience delivering production-grade data platforms and business-critical data products.
• Proven expertise in designing scalable data architectures, data models, data warehouses, and enterprise data pipelines.
• Extensive experience with Spark/PySpark, Python, SQL, AWS, and Snowflake.
• Strong understanding of data governance, security, privacy, access controls, and regulatory compliance.
• Experience with Git, CI/CD, Agile delivery methodologies, automated testing, and DataOps practices.
• Demonstrated ability to translate business requirements into scalable technical solutions.
• Experience supporting platform modernization, optimization, reliability, and operational excellence initiatives.
• Retail, eCommerce, or customer-facing digital platform experience is advantageous Ways of Working
• Hands-on contributor within enterprise data platform initiatives.
• Close collaboration with platform engineers, architects, analytics teams, and business stakeholders.
• Focus on delivering scalable, reliable, and AI-ready data platforms.
• Emphasis on operational excellence, governance, automation, and continuous improvement

📌 Data Engineer (Bengaluru)
🏢 Vriba Solutions
📍 Bengaluru