Data Engineer Lead

Key Skills: AWS, SQL, Python, DynamoDb, Data Engineer, DBT, Redshift, ETL, Airflow

Roles and Responsibilities:

• Own the design of end-to-end data architectures for AWS-based analytical and operational data platforms.
• Define data flows, storage patterns, transformation layers, and consumption models across enterprise data solutions.
• Build and review production-grade data engineering solutions using Python, SQL, Amazon Redshift, DynamoDB, and dbt.
• Translate ambiguous business and stakeholder requirements into clear technical designs, estimates, and implementation approaches.
• Present and defend architectural decisions in design reviews, solution proposals, and technical discussions.

Skills Required:

• 8 - 10 years of relevant experience in data engineering, cloud data platforms, and technical solution design.
• Strong hands-on experience with AWS data platforms and cloud-based data architecture.
• Practical expertise in Amazon Redshift, DynamoDB, Python, SQL, and dbt for data engineering solutions.
• Ability to design scalable, reliable, and maintainable data platforms and transformation workflows.
• Experience defining data integrations, transformation logic, analytical models, and service interfaces for downstream consumption.

Good to Have:

• Experience with ETL development and Apache Airflow-based orchestration.

Education: B.E., B.Tech, BCA, M.Tech, M.E., M.B.A., or equivalent degree in Computer Science, Engineering, or a related discipline.