Description

 
 





What I am looking for:

- Strong hands-on Python and SQL experience

- Direct experience building ETL/ELT pipelines in enterprise environments

- Proven work with Microsoft Fabric, Databricks, Synapse, and Azure Data Factory

- Experience working with large datasets in cloud environments

- Ability to support AI/ML data pipelines (data prep, transformation, reliability)

- Strong ownership mindset and ability to work closely with engineering teams

 

Not a fit:

- No Microsoft Fabric or Databricks experience

- BI/reporting-heavy profiles (this is backend data engineering only)

- Candidates without real ETL/pipeline ownership

- Architects or leads who are not hands-on

- Vague resumes without clear project-level contributions

 


We are partnering with a client in the South Denver area that is seeking a Senior Data Engineer to support ongoing enterprise data and AI initiatives. This role will focus heavily on building and managing scalable ETL/data pipelines, preparing, and transforming enterprise data, and partnering closely with ML Engineers to support downstream AI/ML workloads.

This is a strong fit for a hands-on Data Engineer with modern Microsoft and Databricks experience who enjoys working in a cloud-first data environment.

Key Responsibilities

  • Build, optimize, and maintain ETL/ELT pipelines
  • Prepare, cleanse, and structure enterprise data for ML/AI team initiatives
  • Work across large datasets and multiple data sources in a modern cloud environment
  • Support data movement, transformation, and orchestration efforts
  • Collaborate with Data and ML Engineering teams on scalable data architecture
  • Ensure data quality, performance, and reliability across platforms

Required Skillsets

  • Strong Python and SQL development experience
  • Hands-on experience with Microsoft Fabric
  • Experience with:
    • Synapse Analytics
    • Azure Data Factory (ADF)
  • Databricks expertise
  • Experience building and managing enterprise ETL/data pipelines
  • Strong understanding of cloud-based data engineering best practices

Nice to Have

  • Experience supporting AI/ML environments
  • PySpark or Spark experience
  • Exposure to Lakehouse/data warehouse architectures
  • Azure cloud experience beyond Fabric ecosystem

 

Key Skills
Education

Bachelor's degree

Back To Jobs