Director, Analytics Systems

Responsibilities

• Manage 6-10 engineers (and eventually managers) on Beacon's Analytics Systems Team, coaching them to pursue opportunities to grow their impact at Beacon, and guiding them to overcome challenges along their journey.
• Develop and share a deep understanding of the Analytics Systems Team's activity and products to facilitate continuous improvement of the team's internal processes and integration with Beacon as a whole.
• Act as a steward of Beacon's engineering practices and maintain high bars for engineering quality, productivity, and accountability while motivating the team to continuously raise those bars over time.
• Help your team scope out and prioritize tactical week-to-week work in direct connection with Beacon's wider strategic initiatives, and in coordination with other teams and domains.
• Ensure your team's longer-term development roadmap is outcome-oriented, up-to-date, aligned with the company's objectives and other teams' priorities, and communicated effectively to other stakeholders within Beacon.
• Own project management responsibilities for team initiatives, including defining scope, managing timelines, and ensuring expectations are set both internally and externally.
• Drive product direction and discovery for the Analytics Systems Team, establishing the processes, venues, and cross-functional connections that build deep product intuition across the team, and owning prioritization decisions that ensure the team is consistently working on the highest-impact problems for Beacon's customers and business.
• Craft, iterate, and execute on a forward-looking strategic vision for how Analytics Systems can reshape how Beacon tackles Life Science projects, supports diagnostic workflows, and enables rapid biomarker discovery using real world data.

Requirements

• 6+ years of management experience and familiarity with managing mid- to large-sized analytics engineering teams that have tackled big problems, and can speak to the underlying processes that drove failures and successes encountered by the team along the way.
• Experience and knowledge across analytics engineering (e.g. dbt, SQLMesh), data modeling and pipelines (e.g. Snowflake, Databricks, Argo, Airflow), and BI tooling (e.g., Superset, Looker, Tableau) that allows you assess approaches, guide tradeoffs, and make sound decisions.
• Experience and familiarity working in the medical device space, clinical diagnostics, real-world-data, pharma/biotech or other related fields.
• Worked in a regulated industry before, and have successfully navigated the tension between fast-paced agile development and strict design controls.
• Bias towards simplicity, avoid misallocating complexity, and try to impose structure at the right time - not too early or too late.
• Strong communication and stakeholder management skills, with the ability to align partners around decisions, tradeoffs, and evolving plans, including in regulated or quality-sensitive environments.
• Knack for quickly internalizing the needs of users and the products that serve them, and a track record of translating that understanding into prioritization decisions that consistently direct teams toward the highest-impact work.
• Track record of being able to see around corners, anticipating potential company-wide needs and opportunities, and directly tackling them before they become urgent.
• Keen sense for the bandwidth limitations, technical debt, and non-iterative processes that drag a project down, and you've employed effective strategies for preventing/remedying these issues in the past.

Nice-to-Haves

• Experience evolving data infrastructure to support a centralized feature store and integrating foundation models into core analytical pipelines.

Compensation

• The base salary range for this role is determined based on past experience, specific skills and qualifications. The base salary is one component of the total compensation package, which includes equity, PTO and other benefits.