Key Responsibilities
Design, develop, and maintain data ingestion, transformation, and storage solutions on Azure.
Build scalable ETL/ELT pipelines using Azure Data Factory (ADF), Azure Databricks, Azure Synapse Pipelines , etc.
Develop and optimize data models , data marts, and enterprise data warehouses.
Work with structured and unstructured data using Azure Data Lake Storage (ADLS) Gen2 .
Implement data transformation using Databricks (PySpark/Scala), SQL, or Synapse .
Manage and optimize Azure Synapse Analytics , including serverless and dedicated SQL pools.
Implement CI/CD processes for data solutions using Azure DevOps .
Ensure data quality, governance, privacy, and compliance across all environments.
Monitor performance, troubleshoot issues, and implement continuous improvements.
Collaborate with business teams, data analysts, and data scientists to deliver end-to-end data solutions.
Create clear documentation for pipelines, architecture, and operational processes.
Required Skills & Qualifications
Strong hands-on experience with Azure Data Factory , Azure Databricks , Azure Synapse , and ADLS .
Proficiency in SQL , PySpark , and Python (preferred).
Experience in ETL/ELT pipeline development and orchestration.
Solid understanding of data warehousing concepts (star schema, SCDs, fact/dimension modeling).
Experience with Azure DevOps , Git, and CI/CD pipelines.
Knowledge of Azure Event Hub, Azure Stream Analytics, or Kafka is a plus.
Ability to work with large-scale datasets and optimize performance.
Familiarity with data governance , security , and Azure IAM .
Strong problem-solving skills and ability to work in a fast-paced environment.
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