3+ yrsHyderabadRemoteDirect career pageEst. 12–22 LPA
Posted 21h ago
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Job description
Structured overview of role & requirements
About This Role
- Design, build, test, deploy, and support enterprise feature store pipelines and reusable data pipelines using AWS and Snowflake technology stacks.
- Take end-to-end ownership of data quality, automated testing, documentation, and integration with enterprise systems for analytics-ready datasets.
- Collaborate with data engineering, MLOps, and data science teams to position data for training and inference pipelines without owning model deployment.
Minimum Requirements
- Minimum 3+ years experience in data engineering with AWS services (Glue, S3, Lambda, EventBridge, IAM, Athena) and Snowflake features (snowpipe, streams, tasks, stored procedures, Snowpark).
- Proficiency in Python, SQL, PySpark, and experience with relational databases.
- Bachelor’s or Master’s degree in Computer Science, Engineering, Technology, Mathematics, or related field.
- Experience with CI/CD pipelines on GitHub and building/optimizing data pipelines.
Ideal Candidate Profile
- Experienced in feature engineering and implementing industry and consulting standards for enterprise feature stores.
- Practiced in software engineering best practices including test-driven development, secure coding, and use of AI-assisted development tools (e.g., GitHub Copilot).
- Familiarity with data science workflows, AWS SageMaker model lifecycle practices, infrastructure as code (AWS CDK), and domain knowledge in retirement, annuities, wealth, or insurance is a plus.