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Databricks Developer
Job Description

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1

About the Role

We are looking for an experienced Databricks Developer to join our team. The ideal candidate has hands-on experience with Delta Lake, MLflow, Unity Catalog and can deliver production-ready solutions. You will work closely with cross-functional teams to build, customize, and optimize our Databricks environment.

2

Key Responsibilities

  • Design, develop, and maintain Databricks solutions aligned with business requirements.
  • Collaborate with product managers, designers, and other engineers to deliver features end-to-end.
  • Configure and customize modules including Delta Lake, MLflow, Unity Catalog, SQL Analytics.
  • Build integrations using PySpark, Spark SQL, Delta Live Tables.
  • Write clean, well-documented, and testable code following best practices.
  • Participate in code reviews, sprint planning, and retrospectives.
  • Troubleshoot and resolve Databricks-related issues and performance bottlenecks.
  • Create and maintain technical documentation for all implementations.
  • Stay current with the latest Databricks releases, features, and best practices.
  • Mentor junior team members and contribute to knowledge sharing.
3

Must-Have Qualifications

  • 3+ years of hands-on experience with Databricks.
  • Strong understanding of project lifecycle and Agile methodologies.
  • Proficiency with PySpark, Spark SQL, Delta Live Tables, Databricks REST API.
  • Experience with RESTful API design and third-party integrations.
  • Excellent problem-solving skills and attention to detail.
  • Strong written and verbal communication skills in English.
  • Experience with version control systems (Git).
  • Ability to work independently in a remote-first environment.
4

Nice-to-Have Skills

  • Certifications such as Databricks Certified Data Engineer Associate, Databricks Certified ML Associate.
  • Experience with SQL Analytics, Workflows.
  • Experience with CI/CD pipelines and DevOps practices.
  • Familiarity with cloud platforms (AWS, Azure, or GCP).
  • Experience mentoring or leading small teams.
  • Contributions to open-source projects or technical blogs.
5

Interview Tips

Technical Assessment

Ask the candidate to walk through a recent Databricks project. Focus on architecture decisions and trade-offs.

Problem Solving

Give a real-world scenario involving Databricks and evaluate their debugging approach and logical thinking.

Culture Fit

Assess communication style, timezone flexibility, and experience working with distributed teams.

Code Review

Share a code sample with deliberate issues. See how they identify problems and suggest improvements.

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