Head of Enterprise Data & Analytics (Hybrid)

Archer•San Jose, CA

1d•$219,000 - $300,000•Hybrid

About The Position

Archer is an aerospace company based in San Jose, California building an all-electric vertical takeoff and landing aircraft with a mission to advance the benefits of sustainable air mobility. We are designing, manufacturing, and operating an all-electric aircraft that can carry four passengers while producing minimal noise. Our sights are set high and our problems are hard, and we believe that diversity in the workplace is what makes us smarter, drives better insights, and will ultimately lift us all to success. We are dedicated to cultivating an equitable and inclusive environment that embraces our differences, and supports and celebrates all of our team members. Head of Enterprise Data & Analytics Role Overview: The Head of Enterprise Data Management & Analytics is a senior leadership role responsible for defining and executing the company’s enterprise data strategy. This role will build and oversee a team of data architects, data scientists, and data engineers focused on enterprise-wide data assets and their exposure, ensuring data is trusted, governed, scalable, and analytics-ready to support business growth, regulatory requirements, and strategic decision-making. As a small but rapidly scaling public company, this role requires a hands-on leader who can balance strategy with execution, build foundational capabilities, and partner closely with business and technology leaders.

Requirements

Bachelor’s degree in Computer Science, Data Science, Engineering, or a related field (Master’s preferred)
10+ years of experience in data management, analytics, or related roles, with increasing leadership responsibility
Proven experience leading teams of data architects and/or data scientists
Strong expertise in enterprise data architecture, data warehousing, and analytics platforms (cloud-based preferred)
Experience establishing data governance and quality frameworks in a regulated or public company environment
Ability to operate effectively in a fast-paced, high-growth setting
Familiarity with SOX, financial reporting data requirements, and audit support
Hands-on experience with modern data stacks (e.g., cloud data warehouses, BI tools, orchestration frameworks)
Demonstrated success scaling data capabilities alongside rapid business growth
Excellent written and verbal communication skills

Responsibilities

Define and execute the enterprise data management and analytics strategy aligned with business objectives and growth plans.
Serve as the senior leader for enterprise data architecture, data governance & privacy, analytics, and data science capabilities.
Establish operating models, standards, and best practices suitable for a growing public company.
Build, lead, and mentor a high-performing team of data architects and data scientists.
Own the enterprise data architecture, including data models, integration patterns, and analytics platforms.
Ensure scalable, secure, and reliable data pipelines across internal and external data sources.
Partner with engineering and IT teams on cloud data platforms, tooling, and technology roadmaps.
Drive simplification and modernization of data systems as the company scales.
Establish and oversee enterprise data governance, including data ownership, stewardship, metadata, and lineage.
Ensure data quality, consistency, and integrity across enterprise systems.
Partner with Legal, Finance, and Compliance teams to support public company requirements (e.g., SOX, audit readiness, regulatory reporting).
Define and enforce policies for data privacy, security, and appropriate use.
Lead the development of enterprise analytics, business intelligence, and reporting capabilities to support executive, operational, and functional decision-making.
Oversee data science initiatives that drive insights, forecasting, optimization, and business value.
Ensure analytics solutions are scalable, well-documented, and embedded into business workflows.
Promote a data-driven culture across the organization.
Act as a trusted advisor to senior leaders across Finance, Operations, Engineering, Sales, and other functions.
Translate business needs into data and analytics solutions with measurable impact.
Communicate complex data concepts clearly to technical and non-technical audiences.
Prioritize initiatives based on business value, risk, and resource constraints.