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Databricks Engineer

Databricks Engineer

TTC GroupEllore, Republic Of India, IN
2 days ago
Job description

Role : Databricks Engineer

Position : Remote

Type : Contract

Duration : 3 - 6 months (extendable)

Role Overview

We are seeking a Mid-Level Databricks Engineer with strong data engineering fundamentals and hands-on experience building scalable data pipelines on the Databricks platform. The ideal candidate will be comfortable working with distributed data processing, designing Delta Lake architectures, implementing CI / CD for data workloads, and optimizing Spark jobs for performance and reliability.

Required Skills

  • Strong hands-on experience in building data pipeline using scripting language includes Python, PySpark and SQL
  • Strong working experience with Databricks (Unity Catalog is plus) and Azure Data Factory (ADF)
  • Hands-on working experience with Azure DevOps Repo and CI / CD
  • Strong understanding of modern Data Architecture, Data Warehousing concepts, Data Modelling and ETL / ELT processes
  • Understanding of Agile ways of working
  • Any experience working in DBT is a plus
  • Working with Retail Domain is a plus

Platform Engineering & Operations

  • Configure and optimize Databricks clusters, including autoscaling, cluster sizing, and runtime selection.
  • Manage databases, schemas, and Delta Lake tables, including vacuuming, Z-ordering, partitioning, and optimization.
  • Work with catalogs, Unity Catalog (UC), and access controls for secure data governance.
  • Monitor and troubleshoot performance issues across jobs, clusters, and workflows.
  • CI / CD & DevOps

  • Implement CI / CD pipelines for Databricks workflows using GitHub Actions / Azure DevOps / GitLab.
  • Work with Databricks Repos and Git workflows (branching, PRs, code reviews).
  • Version and promote data pipelines across environments.
  • Cloud & Integration

  • Integrate Databricks with cloud services such as :
  • Azure : ADLS Gen2, Key Vault, ADF, Event Hub, Synapse
  • AWS : S3, Glue, IAM, Lambda, Kinesis (depending on cloud environment)
  • Work with data ingestion frameworks, messaging systems, and event-driven architectures.
  • Quality, Testing & Documentation

  • Implement unit tests and integration tests using pytest, SQL tests, or dbx testing frameworks.
  • Maintain pipeline documentation, data dictionaries, and technical design artifacts.
  • Ensure high data quality, reliability, and observability.
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    Engineer • Ellore, Republic Of India, IN

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