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Walk-in || Data Engineer(DataBricks)

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Onsite

Walk-in || Data Engineer(DataBricks)

Coventine Digital

Walk-in || Data Engineer(DataBricks)

Skills

SQL QueriesPythonDatabricksPySparkAzure

1 month ago

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Important information


Contract type:

Permanent

Location:

Bengaluru, Karnataka, India

Work mode:

Onsite

Published on:

18 September 2026

What they need


Hello ,

as discussed, we are pleased to inform you about a job opening with Coventine Digital Pvt. Ltd., with a deputation to our esteemed client, **(Sandvik)-**Work from Office.

Position : Data Engineer with Databricks

Experience : 9+years

location ; Banglore

mode of interview : F2F on Wednesday & Thursday September 23rd & 24th

  • Mode of Hiring: Third-party payroll / Contract to Hire (C2H)
  • Mode of Working: Full-time, Work from Office

If you are comfortable with the details above and interested in moving forward, please respond with the following information along with your

JD:- Senior Data Engineer (Azure Databricks)

Required Skills:

  • 6+ years of experience in Databricks(important)
  • can work with onsite team to colobrate and understand the E2E requirement
  • Strong PySpark and Python development experience
  • Azure Cloud Services (ADF, ADLS, Azure Blob Storage, Key Vault, etc.)
  • Experience with data ingestion, connectors, and integration frameworks
  • SQL and performance tuning expertise
  • Experience building scalable data pipelines
  • Good communication and stakeholder management skills
  • Knowledge about data architect and DWH concept these are primary point

Responsibilities:

  • Lead design and architecture of large-scale data infrastructure and pipelines (Data Lakehouse).
  • Transform complex business requirements into automated, secure data solutions (ETL/ELT) primarily in Azure.
  • Optimize data storage and compute costs across Databricks clusters and Data Lake.
  • Troubleshoot and resolve production pipeline failures and data quality issues.
  • Drive best practices in data governance, security, and pipeline reliability.
  • Mentor and coordinate with global teams (data scientists, analysts, operations).

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