Job Title

Job Role : Sr Data Engineer Experience : 4+ YearsLocation : Bangalore/MumbaiMust have Skills:4+ years of experience in designing and implementing data warehouses and data lakes/lakehouses on AWS.Hands-on experience with AtScale or similar semantic layer tools to enable governed, business-friendly data access across BI platforms.Proven success working with globally distributed teams in collaborative delivery environments.Deep working knowledge across key AWS Data & Analytics services, including:Building large-scale data lake architectures on Amazon S3 and open table formatsImplementing governance and cataloging through AWS Lake Formation.Developing ETL and metadata frameworks using AWS Glue.Leveraging AWS Lambda for serverless data processing.Running distributed data workloads on Amazon EMR.Enabling real-time data pipelines with AWS Kinesis (Data Streams and Firehose).Orchestrating pipelines using AWS Step Functions/Amazon MWAA/similar services.Designing and optimizing schemas and query performance on Amazon Redshift, including Spectrum and Serverless features.Querying large datasets interactively using Amazon Athena.Managing operational databases using Amazon RDS across engines such as PostgreSQL, MySQL, and Aurora.Integrating and migrating data using AWS DMS, Glue Connectors, EventBridge, SNS, and SQS.Strong understanding of semantic modeling, including logical data models, virtual cubes, and centralized metric definitions (single source of truth).Experience optimizing performance using query pushdown, caching, and aggregate awareness over platforms like Redshift and Athena.Ability to integrate semantic layers with BI tools (QuickSight, Tableau, Power BI) and enforce row/column-level security aligned with governance frameworks.Strong programming capability in Python and PySpark for large-scale data processing.Proficiency in writing complex SQL queries, analytical functions, and performance tuning for large datasets.Familiarity with NoSQL databases such as Amazon DynamoDB, MongoDB, or DocumentDB.Strong understanding of partitioning, indexing, scaling approaches, and query optimization techniques.Proven experience in architecting and implementing data pipelines using native AWS services in a modular and resilient manner.Solid understanding of data modeling concepts, including dimensional, normalized, and lakehouse patterns.Good experience with DBT.Solution Architect- Associate or Data Engineer- Associate Certification.Good to have skills:Experience of working for customers/workloads in one of FSI,Retail,CPG domain.Exposure to IaC tools like Terraform and to CI/CD toolsFamiliarity with data virtualization (e.g., Amazon QuickSight,PowerBI, Tableau) and data governance tools (e.g., Collibra).Managing security, monitoring, and compliance with AWS IAM, Secrets Manager, CloudWatch, CloudTrail, and KMS.Experience with AI-assisted development tools such as GitHub Copilot, Amazon Kiro (or similar GenAI IDEs) for improving developer productivity, code generation, and pipeline accelerationExposure to Data Mesh architecture,Data Governance frameworks