Sr. Manager, Data & Analytics

Specialized Bicycle ComponentsMorgan Hill, CA
$119,628 - $208,153

About The Position

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.

Requirements

  • 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

Nice To Haves

  • 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

Responsibilities

  • 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.

Benefits

  • Competitive pay with annual performance-based reviews
  • 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 birthing parents and 8 weeks of 100% paid leave for non-birthing parents, plus a Specialized bike for your new baby
  • Up to $9,000 annually in Career Development & Degree Assistance
  • Up to $250 annually in Fitness & Wellness Reimbursement
  • Industry Pro-Deal Discounts and Perks
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