✦ Luna Orbit — Data & Analytics

Software Development Engineer 3

at IQVIA Holdings

📍 2 Locations Remote Posted March 09, 2026
Type Not Specified
Experience mid
Exp. Years 2+ years of experience in data engineering or big data development
Education Bachelor's degree in Computer Science, Information Technology, or related field
Category Data & Analytics

This role involves designing, developing, and optimizing large-scale data pipelines using Databricks, Snowflake, and Azure Data Engineering to support enterprise analytics and reporting.

  • Develop and maintain Databricks notebooks and workflows
  • Build scalable PySpark applications
  • Develop Snowflake pipelines and SQL
  • Design data pipelines with Azure Data Factory
  • Troubleshoot pipeline issues

The position requires hands-on experience with Databricks, PySpark, Snowflake, Delta Lake, and Azure Data Factory, focusing on scalable data pipeline development, performance tuning, and data governance.

The ideal candidate is a mid-level data engineer with 2+ years of experience working with Databricks, Snowflake, and Azure Data Engineering. They excel in designing scalable data pipelines, optimizing ETL/ELT workflows, and collaborating with cross-functional teams.

Experience with DatabricksPySparkSnowflakeSQLAzure Data Engineering
Experience with Delta LakeData pipeline designETL/ELT developmentPerformance tuningCost governance
DatabricksSnowflakeAzure Data FactoryAzure Data EngineeringSpark
DatabricksPySparkDelta LakeSnowflake SQLAzure Data EngineeringData pipelinesETL/ELTSQLSnowflakeAzure Data FactorySpark
DatabricksPySparkDelta LakeSnowflake SQLAzure Data EngineeringData pipelinesETL/ELTSQLSnowflakeAzure Data FactorySpark
CollaborationProblem-solvingCommunicationTeamworkTechnical proficiency
Industry SaaS
Job Function Data engineering and pipeline development
DatabricksPySparkDelta LakeSnowflake SQLAzure Data EngineeringData pipelinesETL/ELTSQLSnowflakeAzure Data FactorySpark

Lack of experience with Databricks or Snowflake, No background in data engineering, Unfamiliarity with Azure Data Factory, No experience with ETL/ELT processes

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