Staff Data Engineer
Posted Updated 6
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Summary
A Staff Data Engineer who builds and maintains data pipelines end to end: dbt transformation models, complex Snowflake SQL, Apache Airflow DAGs on AWS ECS, and Python Lambda-based ingestion. Core stack is dbt Core, Snowflake, Airflow, and AWS services (S3, Lambda, MWAA, ECS, Glue, Lake Formation, SQS, EventBridge) with GitHub Actions CI/CD.
Job Description
Responsibilities
- Building and maintaining dbt transformation models across multiple pipeline layers — from raw ingestion through to governed, consumer-ready datasets
- Writing Snowflake SQL for complex transformations: type casting, deduplication, incremental load logic, surrogate key generation
- Developing and debugging Apache Airflow DAGs on AWS ECS
- Contributing to AWS Lambda-based ingestion( Python) — file validation, control file generation, S3 event handling
- Maintaining source-to-target mapping documentation and aligning models to business requirements and data specs
- Supporting onboarding of downstream consumers via data sharing mechanisms and event-driven notifications
- Participating in code reviews, writing YAML-based data quality tests, and owning tickets from design through to production
- Strong SQL
- Proficiency with dbt Core (Must have)
- Apache Iceberg Table format (Nice to have)
- Apache Airflow
- AWS -Working Knowledge of S3, Lambda, MWAA, ECS, Glue Catalogs, Lake Formation, Lambda, SQS, EventBridge
- Experience with fixed-format or structured financial data files
- CICD with Github Actions.
Confidentiality is assured, and only shortlisted candidates will be notified for interviews
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