Sr Data Engineer - FullStack

About the Role:

We are looking for a skilled Full Stack Data Engineer to join our growing data platform team. You will be responsible for designing, building, and maintaining scalable data pipelines and APIs that power internal tools and analytics, with deep integration across AWS services and DevOps best practices.

This is a cross-functional role that requires a strong foundation in backend engineering, cloud-native data workflows, and API development. You will work closely with data scientists, analysts, and product stakeholders to build robust, secure, and reliable data systems.

Key Responsibilities:

• Design and build scalable ETL/ELT pipelines using AWS-native tools (Glue, Lambda, S3, DMS, Redshift, etc.)

• Develop high-performance RESTful APIs using FastAPI, enabling secure and efficient access to data assets

• Architect data platforms and microservices for ingestion, transformation, access control, and monitoring

• Implement authentication & authorization mechanisms using OAuth2/JWT

• Manage infrastructure and deployment using CI/CD pipelines (GitHub Actions, CodePipeline, etc.)

• Write modular, testable, and well-documented Python code across backend and data workflows

• Monitor, debug, and tune performance across cloud services and APIs

• Collaborate with DevOps and Security teams to enforce best practices for data security, access controls, and compliance

• Contribute to a culture of technical excellence, knowledge sharing, and continuous improvement

Must-Have Skills:

• Strong experience with AWS data stack: S3, Glue, Athena, Redshift, Lambda, DMS, IAM, CloudWatch

• Proficiency in Python, especially with frameworks like FastAPI and Pandas

• Hands-on experience building and deploying RESTful APIs with JWT-based auth

• Experience building data ingestion/transformation pipelines (structured/unstructured data)

• Expertise in designing CI/CD workflows for automated testing, deployment, and rollback

• Knowledge of SQL and performance tuning for cloud data warehouses

• Familiarity with containerization & infrastructure as code tools like Docker & CDK

• Version control experience with Git, and Agile/Scrum methodologies

Good-to-Have:

• Experience with orchestration tools like Airflow, Prefect, or AWS Step Functions

• Experience with Terraform for infrastructure as code

• Exposure to data quality, observability, or lineage tools

• Understanding of data security and compliance (GDPR, HIPAA, etc.)

• Familiarity with ML model deployment pipelines is a plus