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As a Senior Data Engineer, you will design and build scalable, reusable, and governed data pipelines and curated datasets on an AWS-based lakehouse architecture. You will help evolve a transactional lakehouse using open table formats (e.g., Apache Iceberg) and implement engineering standards that keep the platform interoperable across query engines and cloud providers. You’ll work across batch and streaming, contribute to a medallion (raw/silver/gold) pattern, and ensure datasets are discoverable, trustworthy, and platform-agnostic through metadata, lineage, and governance integration.
Job Responsibility:
Design and implement robust, reusable data pipelines for batch and streaming use cases using AWS-native services and orchestration tools
Build and standardize medallion-layered ingestion and transformation patterns (raw → silver → gold)
Develop and optimize Iceberg datasets with strong practices for schema evolution, partitioning, and performance
Apply open standards to reduce lock-in by designing storage and metadata layers that work across engines
Contribute to enterprise adoption of Apache Iceberg
Implement standardized interfaces for pipelines and data products
Embed automated quality checks, data validation, and pipeline test coverage
Emit lineage/metadata signals by instrumenting pipelines to produce OpenLineage events
Ensure consistent ownership, documentation, and discoverability for produced datasets
Champion CI/CD for data pipelines and infrastructure changes
Implement observability and contribute to incident triage and reliability improvements
Partner with Security/Platform teams on IAM least privilege, access controls, and governed data access patterns
Work closely with platform engineers, data product owners, governance teams, and downstream consumers
Mentor junior engineers and help define internal standards for Lakehouse engineering
Requirements:
Minimum 7 to 10 years of experience in Data Engineering
Strong communication and stakeholder collaboration skills