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 transparent 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.




Solid 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.

Valuable 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.

📌 Data Engineer Lead Bengaluru (India)
🏢 Careernet
📍 India