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Azure Databricks Tech Lead

Avanade
Bengaluru, IND
Full-time
Lead · 10–12 years experience
Onsite
Discovered 2 weeks ago

Full Job Posting

Key Responsibilities

  • Own technical delivery of Azure Databricks engagements — from solution design through build, testing, deployment, and go-live — across one or more concurrent projects.
  • Lead and mentor a team of data engineers, guiding design decisions, code quality, and best practices on Databricks-based builds.
  • Translate solution architecture into detailed technical design and implementation plans, working closely with Architects and Project/Program Managers.
  • Build and review Azure Databricks pipelines and components: Lakehouse (Delta Lake), Unity Catalog, Databricks SQL, Workflows, and integrations with the broader Azure data ecosystem.
  • Drive engineering standards — coding practices, CI/CD, testing, and performance optimization — across the delivery team.
  • Troubleshoot and resolve complex technical issues during build and post-go-live stabilization; own production support escalations where needed.
  • Track and report delivery progress, risks, and technical dependencies to project/program leadership.
  • Support estimation and technical inputs for ongoing and upcoming project phases within the practice.
  • Contribute to reusable delivery accelerators, patterns, and best practices for the Data & AI practice.
  • Required Skills & Experience
  • 10–12 years in data engineering/technical delivery roles, with strong recent hands-on experience delivering Azure Databricks-based solutions.
  • Deep hands-on expertise with Databricks: Lakehouse/Delta Lake, Unity Catalog, Databricks SQL, Workflows, and cluster/compute optimization.
  • Strong grounding in modern data estate patterns — data lake and data warehouse architecture (medallion architecture, dimensional modeling).
  • Experience leading or being a key technical contributor on data migration projects — legacy on-prem or cloud platforms to Azure Databricks.
  • Solid experience across the broader Azure data ecosystem: Azure Data Factory, Azure Synapse Analytics, ADLS Gen2, Azure SQL.
  • Strong SQL, data modeling, and performance tuning skills; strong hands-on Spark/PySpark expertise.
  • Working knowledge of data governance and security practices — Unity Catalog, role-based access, data lineage.
  • Proven experience leading a delivery team — technical mentoring, code/design reviews, and hands-on problem-solving under project timelines.
  • Comfortable working directly with project/program managers and client technical teams during delivery.
  • Preferred / Good to Have
  • At least 3 years of hands-on experience specifically on Azure Databricks.
  • Databricks certifications: Databricks Certified Data Engineer Professional or Databricks Certified Associate Developer for Apache Spark.
  • Exposure to CI/CD and DevOps practices for data platforms (Azure DevOps, GitHub Actions).
  • Exposure to AI/ML integration on Databricks (MLflow, Databricks Model Serving) or broader GenAI/agentic data use cases.
  • Experience working across multiple industry domains (manufacturing, BFSI, consumer goods, energy, healthcare, or others).
  • Experience working in a global delivery / SI environment with distributed teams across geographies.

Qualifications

  • 10–12 years in data engineering/technical delivery roles, with strong recent hands-on experience delivering Azure Databricks-based solutions.

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