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.
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, 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
It would be great if you also had:
Familiarity with semantic layer tools (e.g. MetricFlow, 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 recognitionComprehensive 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 plans401(k) Company Matching up to $5,000 annually with immediate 100% vesting and administrative fees paid for by the companyCompany-paid Life, AD&D, Short-Term Disability, and Long-Term Disability InsuranceEmployee Assistance Program that provides access to individualized mental well-being careGenerous Vacation, Sick, Paid Holidays, and Volunteer Time Off14 weeks of 100% paid leave for birthing parentsHealth insuranceDental insuranceVision insurance401(k)Paid time off
Additional Information
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.
Specialized · United States, Canada