Direct the evolution of a multi-tenant data architecture that balances scalability, performance, and cost across multiple products and customers
Define and govern EXOL’s canonical enterprise data model. Ensure consistency, versioning, and backward compatibility across all services
Lead the design of batch and streaming ingestion patterns, transformation layers (dbt), and lakehouse components
Establish standards for pipeline orchestration, configuration management, and automated promotion across environments
Embed access controls, metadata management, and data retention policies directly into the platform design
Provide structured, trusted datasets to internal analytics teams and external customer-facing workloads
Lead and develop a global data engineering team (including India-based GCC), fostering a culture of design reviews and engineering excellence.

Bachelor’s degree in computer science or related field
Minimum 8 years in data engineering; 3+ years leading teams
Hands-on expertise in multi-tenant data models, modern lakehouse patterns, and SQL-based transformation frameworks
Ability to debug complex pipeline failures and make cost/performance trade-offs in shared environments
Proven track record of managing global delivery and communicating technical roadmaps to non-technical stakeholders
Preferred Tech Stack: Experience with GCP (BigQuery), Snowflake, dbt, and managed orchestration (Airflow/Composer)
Specialization: Familiarity with metadata-driven governance and AI/BI enablement.

Senior Manager, Data Engineering, Data Platform

Key skills