Design and build mission-critical data pipelines with scalable architecture (streaming, batch).
Improve reporting and analysis, enabling self-service for stakeholders.
Create reusable frameworks to ingest, integrate, and provision data.
Automate end-to-end data pipelines with metadata and data quality checks.
Build and support a cloud-based big data platform.
Define and automate jobs and testing.

🎯 Requirements

3-5 years in data warehouse / data lake architecture.
3+ years Python/Scala/Java/C#.
3 years with Big Data tools: batch (Hadoop/Spark) or real-time (Kafka/Flink).
2+ years AWS or other cloud environments.
Strong knowledge of Databricks SQL/Scala for data pipelines.
Familiar with batch processing and workflow tools: dbt, Airflow, NiFi.

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