- Design, build, and maintain robust, scalable data pipelines (batch and real-time/streaming).
- Design and develop dashboards that surface key business metrics.
- Develop and optimize complex SQL queries, stored procedures, and data models.
- Write clean, production-grade Python code for data ingestion, transformation, and automation.
- Build and manage cloud-native data infrastructure on AWS, GCP, or Azure.
- Implement and maintain data lakehouse architectures (e.g., Delta Lake, Apache Iceberg).
- Support ML workflows including feature engineering, model training pipelines, and MLOps integration.
- Ensure data quality, governance, and lineage tracking across all data assets.
- Monitor pipeline performance, troubleshoot issues, and optimize for cost and efficiency.
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