Vacancy Description
Description
Design, build, andmaintainreliable, high-performance data pipelines for large-scalestructured and unstructured healthcare data.
UsePySparkand modern cloud-based tools (Databricks, AWS Glue, EMR, Snowflake) to transform and process data efficiently.
Support ingestion, transformation, and validation processes that ensure data consistency, integrity, and availability.
Partner with Data Architects, Data Scientists, and Analysts to translate business needs into scalable engineering solutions.
Collaborate with platform and DevOps teams to deploy, scale, and monitor data pipelines using Airflow and Kubernetes.
Participate in code reviews, documentation, and continuous improvement efforts across the engineering team.
Implement andmaintaindata validation frameworks to ensure pipeline accuracy and completeness.
Contribute to best practices in version co...
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