Databricks & Spark: Hands-on experience with Databricks, Apache Spark, and PySpark for big data processing. • Cloud Platforms: Proficiency in Azure (preferred), AWS, or GCP for data engineering workflows • SQL & Data Modeling: Strong knowledge of SQL, schema design, and dimensional data modeling. • ETL/ELT Tools: Experience with tools like Azure Data Factory, Informatica, or Talend. • Data Warehousing: Familiarity with technologies such as Azure Synapse, Snowflake, or BigQuery. • Strong problem-solving and debugging skills. • Excellent communication and teamwork abilities. • Ability to work in a fast-paced, dynamic environment.

Good-to-Have • Knowledge of Event Hub, IoT Hub, and streaming analytics. • Exposure to Power BI, Azure DevOps, and CI/CD pipelines. • Understanding of machine learning libraries (MLlib) and predictive analytics.

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