Data Engineering
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Job Description
- Design, build, and support reliable data pipelines for enterprise data platforms.
- Develop and maintain reusable data assets for analytics, querying, APIs, and feature engineering.
- Write production-grade PostgreSQL SQL using CTEs, window functions, and set-based processing.
- Optimize PostgreSQL performance through query tuning, execution plan analysis, indexing, partitioning, and statistics management.
- Use EXPLAIN ANALYZE and BUFFERS to diagnose slow queries and identify I/O and execution bottlenecks.
- Design effective indexes including B-tree, Hash, GiST, and GIN, aligned with filtering, joins, and sorting requirements.
- Implement resilient pipelines with error handling, retry logic, idempotency, reprocessing, and backfill capabilities.
- Design and maintain logical and physical data models using normalized and dimensional modeling approaches.
- Define and maintain data contracts covering schemas, keys, constraints, naming conventions, SCD approaches, and business definitions.
- Manage schema evolution with backward compatibility, deprecation planning, and impact analysis.
- Implement data integration using ETL and other data tools across databases and platforms.
- Establish data quality checks and monitoring for analytics data flows.