Lead the enterprise data hub by managing the data warehouse and building reliable, optimised pipelines to ingest and transform data from systems across GTM, Product, Finance, and HR
Drive an enterprise-wide data governance strategy by partnering cross-functionally to align on KPIs, key data definitions and ensure quality, security, and compliance.
Prioritize and manage the data roadmap through sprint planning and balancing immediate stakeholder needs with scalable long-term architecture
Implement best practices for data modeling, testing, and documentation to maintain clean, scalable, and auditable transformations.
Deliver GTM-ready data by building trusted pipelines for metrics like pipeline health, bookings, churn, and customer lifetime value.
Develop and execute a data strategy that enables advanced analytics and AI/ML use cases across the business.
Lead and mentor a hub team of data and analytics engineers, setting priorities, CI/CD standards, and fostering a culture of reliability and innovation.
Stay ahead of industry trends in modern data stack tools, orchestration and AI-driven data transformation.

8+ years of experience in data/analytics engineering or enterprise data management
Demonstrated ability to design and implement data governance frameworks and lead cross-functional stakeholders to align on KPIs, data standards, and strategic roadmaps.
Proven expertise managing cloud data warehouses (e.g., Snowflake) and scaling enterprise data platforms.
Hands-on experience with the modern data stack, including dbt for data transformation, orchestration tools (Airflow, Dagster), and ingestion tools (Fivetran, etc.).
Experience implementing access controls, role-based permissions, and data masking to protect sensitive information across systems
Strategic mindset with exposure to AI/ML, capable of identifying opportunities to leverage advanced analytics for business impact.
Experience leading sprint prioritization, roadmap management, and mentoring high-performing data teams.
Business acumen in SaaS or technology companies, with familiarity in metrics such as ARR, churn, pipeline health, and customer lifetime value.

Senior Manager, Enterprise Data

Key skills