Sr. Manager, Data & Analytics

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.

Four Pillars of This Role

* Platform Leadership:
Own the architecture and roadmap for the modern data stack, from source systems through to consumption layers.

* Team Building:
Hire, grow, and inspire both data engineers and analytics engineers, fostering a culture of quality, curiosity, and ownership.

* AI Integration:
Embed AI tooling natively into the team's workflows for build, testing, documentation, and monitoring of our data platform.

* Business Partnership:
Translate commercial priorities into robust data infrastructure that is agile, trusted, and scalable.

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, Git Hub Copilot, Claude) to accelerate delivery and reduce toil.

* Intelligent data pipelines:
Implement AI-native patterns-LLM-generated documentation, anomaly detection, data quality monitoring, and automated root-cause analysis.

* 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.

What you'll need to know/have:

* 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, Big Query, 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

It would be great if you also had:

* Familiarity with semantic layer tools (e.g. Metric Flow, Cube), data cataloging (e.g. Atlan, Datahub), and data observability platforms

* Experience with streaming data (Kafka, Flink, or Kinesis) and batch processing

* Exposure to data mesh or data product organizational models

Additional

Job Description

BENEFITS

As a full-time, regular teammate, you are eligible for the following benefits, beginning the first of the month following your start date.

Benefits include:

* 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

* 14 weeks of 100% paid leave for…