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Codvo AI · IT - Software Development

Data & Databricks Practice Lead

· Job Posted June 03, 2026
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Job Description

We are looking for a dynamic and visionary Practice Lead to build and scale our Data & AI capabilities with a strong focus on Databricks, Apache Spark, Iceberg, Azure Data Fabric, Amazon EMR, and Redshift. This role is pivotal in driving Lakehouse architecture adoption, cloud-native modernization, and ML engineering across industries such as Oil & Gas, Medtech, Retail CPG, and Fintech. You will lead a cross-functional team of architects, engineers, and ML specialists to deliver high-impact solutions that combine technical excellence, cost efficiency, and governance maturity.

Job Responsibility

  • Define and execute the strategic roadmap for the Data & AI practice, aligning with evolving trends in Lakehouse, cloud-native platforms, and AI engineering
  • Build reusable solution accelerators (e.g., Iceberg ingestion templates, Spark ETL frameworks, MLflow pipelines)
  • Establish and manage strategic partnerships with Databricks, AWS, Azure, and other ecosystem players
  • Represent the practice in industry forums, client workshops, and thought leadership initiatives
  • Architect scalable Lakehouse solutions using Delta Lake or Iceberg, optimized for performance and cost
  • Lead the design of unified batch + streaming pipelines using Spark Structured Streaming and Scala
  • Oversee multi-cloud data platform modernization using Azure Data Fabric, EMR, and Redshift
  • Guide implementation of data governance frameworks using Unity Catalog, Azure Purview, and Iceberg metadata
  • Mentor and grow a high-performing team of data engineers, ML engineers, and platform specialists
  • Define career paths, training plans, and certification goals aligned with Databricks, AWS, and Azure
  • Foster a culture of innovation, experimentation, and continuous improvement
  • Engage with clients to understand business challenges and translate them into scalable data solutions
  • Lead solutioning, proposal development, and delivery for strategic engagements
  • Ensure delivery excellence through performance optimization (Photon, EMR Autoscaling) and cost engineering

Requirements

  • 10+ years of experience in data engineering, architecture, and platform modernization
  • 3+ years of hands-on experience with Databricks, Apache Spark, Iceberg, and Scala
  • Deep expertise in cloud-native data platforms (Azure Data Fabric, Amazon EMR, Redshift)
  • Proven track record in building ML pipelines, implementing MLOps (MLflow), and integrating Redshift ML
  • Strong understanding of data governance, observability, and schema evolution
  • Excellent leadership, communication, and stakeholder management skills

Nice to have

  • Certifications in Databricks, Azure Data Engineering, or AWS Big Data
  • Experience in vertical-specific data solutions (e.g., predictive maintenance in Oil & Gas, real-time analytics in Retail)
  • Familiarity with data mesh architectures, time travel, and audit compliance frameworks
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