AI Data Lead

Job Summary

We are looking for a motivated Databricks Technical Lead ready to take us to the next level! If you have experience with Azure, Databricks, and AI data product management, and are looking for your next career move, apply now.

Job Description

We are looking for a Databricks Technical Lead to lead the strategy, governance, productization, and operational excellence of AI-ready data products that enable scalable and reliable AI solutions across the enterprise. This position will be full-time and hybrid in Bengaluru.

What Youll Do

• Own the AI data product roadmap and translate business priorities into a sequenced backlog of reusable data products with defined ownership, service levels, and lifecycle controls
• Partner with dashboard, analytics, and AI delivery teams to identify reporting assets that should evolve into governed AI-ready data products
• Establish data product charters defining purpose, consumers, source ownership, data contracts, access models, and retention requirements
• Implement table-, column-, and row-level access standards, classification, audit trails, and data handling controls using Databricks Unity Catalog and AWS services
• Lead the design and operation of incremental, observable, and cost-efficient data ingestion and curation pipelines across enterprise data sources
• Create and maintain versioned, reproducible training datasets, evaluation datasets, inference inputs, feature tables, and monitoring datasets with clear metadata and documentation
• Define and implement AI-specific data quality standards including completeness, consistency, timeliness, uniqueness, referential integrity, distribution stability, and drift sensitivity
• Establish automated quality controls and enforce readiness gates that prevent model training, deployment, or production promotion when critical data quality requirements are not met
• Develop operational runbooks for recovery, backfills, reprocessing, incident response, and escalation management
• Participate in operational reviews and drive root-cause analysis and corrective actions to improve platform reliability
• Optimize storage, compute utilization, partitioning, scheduling, and overall platform cost efficiency
• Approve data readiness gates for model training, evaluation, deployment, and significant production inference input changes
• Escalate data ownership, quality, access, and cost issues that introduce risk or impede business outcomes
• Drive dashboard-to-data-product transformations and establish governed, reusable data products that support critical AI use cases
• Deliver quality and cost scorecards that provide transparency into data health, reliability, usage, and platform cost drivers

What You’ll Need

Required:

• Bachelor’s degree or higher in Computer Science, Data Science, AI/ML, Applied Mathematics, Engineering, or a related field
• 8+ years of experience in data engineering, data management, AI data foundations, or related technology leadership roles
• Demonstrated ownership of data products or mission-critical data pipelines delivering measurable business impact
• Hands-on experience with AWS, Databricks, Delta Lake, Unity Catalog, data lineage, observability, and production support
• Experience defining and managing data contracts, quality gates, service levels, and data access models
• Strong stakeholder management skills with experience partnering across business leaders, product owners, data and AI engineering teams, security, and platform organizations
• Ability to operate at a senior level, challenge incomplete requirements, evaluate trade-offs, and drive decisions in ambiguous environments
• Strong communication skills with the ability to simplify complex technical concepts for business stakeholders
• Proven ownership mindset with accountability for business and technical outcomes
• Strong judgment balancing speed, quality, security, cost, and maintainability
• Excellent problem-solving skills and ability to adapt in fast-paced, evolving environments
• Commitment to data quality, operational excellence, documentation, and continuous improvement

Preferred:

• Databricks Data Engineer Professional certification
• Databricks Machine Learning Professional certification
• AWS Certified Data Analytics certification
• AWS Solutions Architect Associate certification
• AWS Solutions Architect Professional certification
• Data governance, data management, product ownership, or agile delivery certifications