Sr. Manager, Data & Analytics

About The Role

We are seeking a Senior Manager of Data & Analytics Engineering to lead our data platform teams and power decision-making across the company. In this senior leadership position, you will own and evolve our end-to-end data platform—from ingestion and transformation to analytics layers that business teams rely on daily. You'll oversee Data Engineering (infrastructure, pipelines, reliability) and Analytics Engineering (data models, metrics, self-serve tooling), while championing an AI-first approach to the way we build, operate, and innovate.

What You Will Do

• Define and own the multi-year roadmap for the data platform, aligning investments in infrastructure, tooling, and headcount with business strategy.
• Lead and grow the Data and Analytics team, cultivating a collaborative, feedback-rich environment with clear career pathways.
• Architect and oversee scalable data pipelines across ingestion, transformation, orchestration, and delivery, for both batch and streaming use cases.
• Champion best practices in analytics engineering, including semantic layer design, dbt modelling standards, data contracts, and metrics governance.
• Partner with business stakeholders to deliver high-quality, self-serve data solutions aligned to business needs.
• Ensure data platform reliability, observability, SLAs, and incident response, treating the platform as a product with real users.
• Drive vendor and tool evaluations for the modern data stack (cloud warehouse, orchestration, cataloging, transformation, reverse ETL, etc.).
• Set and enforce data quality, documentation, and governance standards to build trust across the business.
• AI-assisted development: Champion use of AI coding assistants and LLM-powered tooling (e.g. Cursor, GitHub Copilot, Claude) to accelerate delivery and reduce toil.
• Natural language interfaces: Prototype NL-to-SQL and AI-powered BI tools to empower self-serve analytics for non-technical users.
• AI platform enablement: Build foundational data infrastructure (feature stores, vector stores, model metadata, evaluation datasets) to enable AI and ML experimentation and scale.

Qualifications

• 7+ years in data engineering or analytics engineering, with 3+ years in a senior leadership role managing multiple teams.
• Deep expertise in the modern data stack—cloud data warehouses (Snowflake, BigQuery, or Databricks), dbt, orchestration tools (Airflow, Dagster, or Prefect), and ELT frameworks.
• Strong command of SQL and Python.
• Hands-on experience integrating AI/LLM tooling into engineering workflows or data products.
• Proven ability to define and execute a multi-year data platform strategy.
• Strong stakeholder management, including executive presentations and translating technical concepts to non-technical audiences.
• Experience building and scaling high-performing engineering teams: hiring, mentoring, performance management.
• Track record of delivering trusted, well-documented, and widely adopted data products.

Benefits

• Competitive pay with annual performance-based reviews for continued growth and recognition.
• Comprehensive healthcare plan options, including PPO, EPO, HDHP, and HMO (acupuncture and physical therapy included).
• Health Savings Account (HSA) with employer HSA contributions when enrolled in the High-Deductible Healthcare Plan (HDHP).
• Dental and Vision plans.
• 401(k) Company Matching up to $5,000 annually with immediate 100% vesting and administrative fees paid for by the company.
• Company-paid Life, AD&D, Short-Term Disability, and Long-Term Disability Insurance.
• Employee Assistance Program that provides access to individualized mental well-being care.
• Generous Vacation, Sick, Paid Holidays, and Volunteer Time Off.
• Up to $9,000 annually in Career Development & Degree Assistance.
• Up to $250 annually in Fitness & Wellness Reimbursement.
• Industry Pro-Deal Discounts and Perks.