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Strategic Leader

2 weeks ago


Belgaum, Karnataka, India beBeeDataEngineer Full time ₹ 1,50,00,000 - ₹ 2,00,00,000

We are seeking a senior leader to build, scale, and deliver data and AI capabilities across the organization using Databricks Unified Analytics Platform. This role involves technical vision, solution architecture, team building, partnership development, and delivery excellence.

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Key Responsibilities:

  • Capability Development
  1. Develop and enhance Databricks-based offerings and accelerators.
  2. Define best practices and architectural standards.
  3. Collaborate with alliance teams to strengthen partnerships.
Technical Leadership
  1. Provide architectural guidance for Databricks solution design and implementation.
  2. Lead solutioning efforts.
  3. Conduct technical reviews.
  4. Ensure adherence to design standards.
Delivery Oversight
  1. Support delivery teams with technical expertise.
  2. Drive quality assurance.
  3. Performance optimization.
  4. Project risk mitigation.
Talent Development
  1. Build and grow a high-performing Databricks capability team.
  2. Define skill development pathways and certification goals.
  3. Mentor architects, developers, and consultants.
  4. Drive community of practice initiatives.
Business Development Support
  1. Engage with sales and pre-sales teams to position Databricks capabilities.
  2. Contribute to account growth by identifying new opportunities.
  3. Participate in client presentations, workshops, and technical discussions.

This role requires strong collaboration with cross-functional teams and works closely with clients, alliance partners, internal stakeholders, and sales teams to drive adoption of lakehouse architectures, data engineering best practices, and AI/ML modernization.

Requirements:

  • 12–15 years of experience in data engineering, analytics, and AI/ML.
  • 3–5 years of hands-on experience with Databricks (on Azure, AWS, or GCP).
  • Expertise in Spark (PySpark/Scala), Delta Lake, Unity Catalog, MLflow, and Databricks notebooks.
  • Familiarity with hyperscaler ecosystems (Azure Data Lake, AWS S3, GCP GCS, ADF, Glue, etc.).
  • Strong understanding of MLOps and AI/ML lifecycle management.
  • Certifications in Databricks are preferred.