Data & Databricks Practice Lead (India - Remote)

Job Title: Data & Databricks Practice Lead Location: Remote About Us At Codvo, we are committed to building scalable, future-ready data platforms that power business impact. We believe in a culture of innovation, collaboration, and growth, where engineers can experiment, learn, and thrive. Join us to be part of a team that solves complex data challenges with creativity and cutting-edge technology. Role Summary 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. Key Responsibilities Strategic Leadership & Practice Growth • 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. Technical Architecture & Delivery Oversight • 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. Team Leadership & Capability Building • 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. Client Engagement & Business Impact • 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. Required Skills & Experience • 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. Preferred Qualifications • 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. Why Join Us? • Be at the forefront of Lakehouse innovation and AI-driven transformation. • Work with cutting-edge technologies and shape the future of data platforms. • Lead a high-impact practice with global reach and industry relevance.