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Design, develop, and maintain ETL/ELT pipelines using Azure Data Factory, Azure Databricks, and other Azure services.
Build and evolve data architecture, including models, schemas, and dictionaries.
Integrate data from multiple sources, ensuring quality, consistency, and readiness for analytics and operations.
Apply data governance policies to ensure security, privacy, and compliance.
Collaborate with data scientists, analysts, and business stakeholders to translate requirements into scalable solutions.
Stay current with emerging technologies and identify opportunities to enhance data infrastructure.
Implement best practices in big data and cloud computing to ensure efficiency and scalability.

4 to 7 years of overall experience in data warehouse, data engineering, ETLs, data mapping, SQL, databases, data lakes or lakehouse
2 years of experience in Databricks, Azure Data Factory and DevOps/CICD automation.
Strong knowledge of Azure services: ADLS Gen2, Synapse, SQL Server, ADF, Databricks.
Proficiency in Spark and PySpark for distributed data processing.
Solid programming skills in Python for scripting and automation.
Understanding of data warehousing and relational modeling.
Familiarity with compiled languages (Java, Scala) and scripting languages (SQL, R).
Excellent communication, problem-solving, and collaboration skills.
Growth mindset with a passion for continuous learning and improvement.
Experience working in Agile/Scrum teams using tools like JIRA, Teams, and Mural.
Knowledge of performance tuning, capacity planning, and production support models.