Databricks Data Engineer (Deerfield)
Centraprise, Deerfield, IL, United States
Databricks Data Engineer
Deerfield, IL - Onsite
Fulltime
Mandatory skills: Databricks, Spark, Azure, Python, Cosmos DB, Azure DevOps (GitHub, CI/CD pipelines, Boards etc.), Docker & Azure Kubernetes Service, Graffana, JUnit, Postman, SonarQube
Additional Skills: 3–6 years of experience in data engineering on cloud data platforms. Hands‑on experience building Spark jobs with Scala/Spark and/or PySpark on Databricks. Experience ingesting data from batch and streaming sources into ADLS Gen2 using Delta or Apache Iceberg tables. Good SQL skills for joins, aggregations, and data quality checks. Understanding of core Azure data services (Event Hubs/Kafka, Data Factory/Databricks Workflows, Key Vault). Experience working with Git‑based workflows and CI/CD in Azure DevOps or GitHub.
Good to have skills: Exposure to Spark Structured Streaming for near real‑time use cases. Experience with data quality tools or frameworks and writing unit/integration tests for data pipelines. Familiarity with data modeling and performance considerations in Lakehouse environments.
Roles & Responsibilities:
Responsible for building data products in Databricks using Scala/Spark
Responsible for Ops work managing production for the data products developed and deployed to production
Responsible for testing data products based on product specification and end to end validation
Set up monitoring, logging, and alerting Spark jobs and data pipelines using Azure Monitor/Log Analytics or similar tools
Coordinate with offshore team in India
Deerfield, IL - Onsite
Fulltime
Mandatory skills: Databricks, Spark, Azure, Python, Cosmos DB, Azure DevOps (GitHub, CI/CD pipelines, Boards etc.), Docker & Azure Kubernetes Service, Graffana, JUnit, Postman, SonarQube
Additional Skills: 3–6 years of experience in data engineering on cloud data platforms. Hands‑on experience building Spark jobs with Scala/Spark and/or PySpark on Databricks. Experience ingesting data from batch and streaming sources into ADLS Gen2 using Delta or Apache Iceberg tables. Good SQL skills for joins, aggregations, and data quality checks. Understanding of core Azure data services (Event Hubs/Kafka, Data Factory/Databricks Workflows, Key Vault). Experience working with Git‑based workflows and CI/CD in Azure DevOps or GitHub.
Good to have skills: Exposure to Spark Structured Streaming for near real‑time use cases. Experience with data quality tools or frameworks and writing unit/integration tests for data pipelines. Familiarity with data modeling and performance considerations in Lakehouse environments.
Roles & Responsibilities:
Responsible for building data products in Databricks using Scala/Spark
Responsible for Ops work managing production for the data products developed and deployed to production
Responsible for testing data products based on product specification and end to end validation
Set up monitoring, logging, and alerting Spark jobs and data pipelines using Azure Monitor/Log Analytics or similar tools
Coordinate with offshore team in India