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Build and maintain robust ETL/ELT pipelines for efficient data flow.
Monitor and troubleshoot data systems for performance and reliability.
Lead incident and problem management, ensuring SLA compliance.
Automate data processing and reporting workflows.
Collaborate with Data Engineers, Scientists, BI, and DevOps teams.
Document processes and communicate with business and IT stakeholders.
4+ years in Data Engineering or Data Operations.
Strong SQL skills and experience with relational databases.
Hands-on with cloud platforms (Google Cloud, Azure, Microsoft Fabric).
Proficient in ETL tools and orchestration frameworks (Airflow, Prefect, etc.).
Familiar with big data tools (Hadoop, Spark) and programming (Python, Java, Scala).
DevOps knowledge (CI/CD, Docker, Kubernetes) is a plus.
Bonus: Experience with MLOps, Kafka, and data governance.
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