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Data engineering & Databricks / UTIS-DATA-NS-006

Senior Data Engineer – Application Development (Azure)

Build Azure Databricks pipelines, REST APIs and Python applications for a global semiconductor company. The role combines lakehouse engineering with Streamlit and Databricks Apps delivery.

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Region
India
Work arrangement
Remote
Engagement type
Independent contractor with UTIS
Working hours
40 hours per week; 9:00 a.m.–5:00 p.m. US Eastern Time, Monday–Friday; full-day availability required.
Posted
July 30, 2026
Applications
Open until filled
Openings
2

What you will work on

  • Design and optimize Azure Databricks ETL/ELT pipelines for enterprise, factory and engineering data.
  • Implement Delta Lake medallion patterns and Unity Catalog governance.
  • Integrate Azure Data Factory, ADLS Gen2 and Synapse Analytics.
  • Build REST APIs, Python applications, Streamlit interfaces and Databricks Apps.
  • Support Azure cloud-native applications and containerized workloads on AKS.
  • Translate requirements into technical specifications, architecture decisions and runbooks.
  • Work through enterprise architecture, security, onboarding and change-control processes.
  • Apply Git, automated testing, Azure DevOps CI/CD and peer review across data and application code.

What you bring

  • 7+ years of hands-on Azure data engineering with deep Azure Databricks experience.
  • Delta Lake, Unity Catalog, Workflows, Databricks SQL and production ETL/ELT design.
  • Strong Python, SQL, data modeling and data warehousing.
  • REST API development and integration; Streamlit application development.
  • Azure Data Factory, ADLS and Synapse Analytics.
  • Client-facing requirements analysis, clear documentation and autonomous delivery.
  • Professional written and spoken English and full availability during the stated Eastern Time workday.
  • Reliable internet and a private workspace; client-provisioned equipment must be used for client information.

Useful additional experience

  • Azure data-engineering or Databricks Data Engineer credentials.
  • Azure DevOps, Databricks Asset Bundles and CI/CD.
  • Azure OpenAI, AI/ML, generative AI or MLOps.
  • Docker, Azure App Services, AKS and migration of MATLAB/scientific workloads.
  • Semiconductor, manufacturing, sensor or equipment-data experience.

Engagement details

  • Client onboarding can take several weeks and includes background and drug screening, confidentiality/IP agreements and an export-control attestation.
  • A client laptop and VPN access are provisioned through UTIS and the client.
  • Occasional travel to San Diego is a plus, not a requirement; the client-facing work follows the US holiday calendar.