Senior AWS Data Engineer

Role Overview: Lead the design, development, and optimization of large-scale, reliable, and secure data pipelines and data lake architecture on AWS.

Architect and implement end-to-end data solutions, including data ingestion, storage, transformation, and analytics using AWS services (Glue, Redshift, S3, Lambda, EMR, Kinesis, Athena, RDS, etc.)

Mentor and guide a team of data engineers, conducting code reviews and fostering best practices in data engineering and cloud architecture. Collaborate with data scientists, analysts, and business stakeholders to translate requirements into scalable and maintainable solutions.

Oversee migration of data from legacy systems to AWS-based data lakes and data warehouses. Develop and enforce standards for data quality, security, and governance. Drive the adoption of DevOps, CI/CD, and infrastructure-as-code practices within the data engineering team.

Ensure solutions are cost-effective, performant, and aligned with enterprise data strategy. Stay current with advancements in AWS technologies and data engineering trends and evaluate new tools and frameworks for potential adoption. Troubleshoot complex data issues and provide technical leadership in problem resolution.

.

Key Responsibilities

& Skillsets: Common Skillsets: Superior analytical and problem solving skills Should be able to work on a problem independently and prepare client ready deliverable with minimal or no supervision Good communication skill for client interaction Application development Skillsets: Strong ability to debug complex data workflows, optimize application and ETL code, and automate data transformation processes Systematic, analytical problem‑solving approach with strong ownership over data quality, performance, and delivery Ability to quickly evaluate new AWS data and analytics services and determine fit for data pipelines or application architecture Hands‑on experience developing data workflows and infrastructure using IaC frameworks such as CloudFormation o