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AI Summary
The engineer will execute core data engineering development work across ingestion, transformation, modeling, and integration pipelines. This role focuses on enabling high-quality trusted data availability for business analytics, AI/ML, and product systems.
1. Role Purpose (1–3 lines): Executes core data engineering development work across ingestion, transformation, modeling & integration pipelines to enable high quality trusted data availability for business analytics, AI/ML, and product systems.
2. Key Responsibilities:
· Build, test and maintain ETL/ELT pipelines, ingestion frameworks and data integration connectors across batch / streaming.
· Implement data transformations, quality rules, profiling checks, data cleansing routines and schema enforcement.
· Develop data models, curated layers, staging layers and support semantic readiness for analytical consumption.
· Support deployment, CI/CD, code repository hygiene, job scheduling, monitoring and run support.
· Follow standards for naming, folder structure, pipeline modularity, code performance and engineering quality.
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