<ul><li>Design, develop, and optimize data pipelines using Azure Data Services (Azure Data Factory, Azure Data Lake Storage, Azure Synapse).</li><li>Build and maintain scalable ETL/ELT workflows using Databricks (Spark, PySpark, Delta Lake).</li><li>Implement and manage data orchestration and dependency management using Dagster or similar tools.</li><li>Partner with analytics, data science, and product teams to ensure reliable, high-quality data availability.</li><li>Optimize data models and storage strategies for performance, scalability, and cost efficiency.</li><li>Ensure data quality, observability, and reliability through monitoring, logging, and automated validation.</li><li>Support CI/CD pipelines and infrastructure-as-code practices for data platforms.</li><li>Enforce data security, governance, and compliance best practices within Azure.</li></ul>

<ul><li>3+ years of experience in data engineering or analytics engineering.</li><li>Strong hands-on experience with Databricks, including Spark-based data processing.</li><li>Experience building data pipelines in Microsoft Azure.</li><li>Proficiency with SQL and Python.</li><li>Experience with modern data orchestration tools (e.g., Dagster, Airflow, Prefect).</li><li>Familiarity with data warehousing concepts, dimensional modeling, and ELT patterns.</li><li>Experience working in Agile or DevOps-oriented environments.</li></ul>

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