Senior Data Engineer

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About the Role

Senior Data Engineer

Key Responsibilities

• Design, develop, and optimize

  ETL pipelines

  using Azure Databricks, Apache Spark, and Azure Data Factory (batch & real-time).
• Build advanced

  data transformation workflows

  using Python/Scala.
• Write and tune

  stored procedures, SQL queries, and Spark SQL

  for performance.
• Implement

  data ingestion, preparation, and integration

  pipelines aligned with business needs.
• Architect and manage

  Data Lakes, Data Warehouses, and Data Marts

  .
• Work with

  Azure Synapse Analytics, Snowflake

  , and other analytical warehouses.
• Implement

  CI/CD pipelines

  with Azure DevOps, GitHub, and automation/orchestration tools.
• Ensure

  data quality, governance, and security

  across data ecosystems.
• Contribute to

  solution design

  and architecture reviews for data engineering projects.
• Collaborate with cross-functional teams and provide

  technical guidance & documentation

  .
• Utilize Azure services like

  Azure Functions, Data Lake Store, Cosmos DB

  .
• Work with

  healthcare data models and standards

  (preferred).

Qualifications & Skills

• 8+ years

  of proven experience in

  Data Engineering

  .
• Strong hands-on expertise in

  Azure Databricks, Apache Spark, and ADF

  .
• Proficiency in

  Python or Scala

  for data engineering.
• Solid experience in

  ETL, Data Warehousing concepts, and Big Data processing frameworks

  .
• Strong SQL skills (MS SQL, Spark SQL, Delta Lake).
• Experience with

  Azure Synapse, Snowflake, and cloud-native data platforms

  .
• Familiarity with

  CI/CD pipelines, Git, and automation tools

  .
• Excellent problem-solving, analytical, and communication skills.

• Healthcare domain knowledge

  is a plus.