Lead & Mentor: Build, manage, and mentor a high-performing team of data engineers, architects and analysts. Foster a culture of technical excellence, business impact, and deep curiosity.
Strategic Partnership: Serve as a trusted advisor to senior leadership in Product, Hardware/Supply Chain, Clinical, Marketing, Commercial, Membership, Finance, and Sales. Proactively identify opportunities and risks, and influence the GTM strategy through data-driven storytelling.
Roadmap & Execution: Own the data platform roadmap, prioritizing projects that align with company OKRs. Oversee the entire data and ML lifecycle from ideation and data exploration in partnership with the Sr. Director of Data Science in the development of advanced analytics models and the delivery of insights.
Drive Technical Excellence: Establish and enforce best practices for the full data science development lifecycle, from prototyping to productionalizing models. Deliver optimal ML platform and tooling for the team.
Governance: Guarantee Quality & Trust: Champion best practices in data science to ensure the accuracy, reliability, and trustworthiness of all data products and insights delivered by your team. Establish processes for rigorous validation and peer review.
Cross-Functional Collaboration: Work closely with the other data leaders supporting Product teams to ensure a holistic view of the customer journey. Partner with Data Engineering and Business Intelligence teams to advocate for the data infrastructure, tooling, and data governance best practices your team needs to succeed.
Build, operate, and improve Oura’s Data lakehouse: consisting of a global data technology and platform that unifies data across systems to move, process, and store large amounts of data (Terabyte–Petabyte scale) leveraging tools such as Google Big Query, VertexAI, Databricks, Azure, AWS Kinesis, S3, Spark / Glue, Athena, dbt, Iceberg, Snowflake, Docker, workflow engines, and more.
Global Data Residency, Data Mesh Privacy: Ensure that our federated data mesh and processes meet governance policies, privacy, compliance, and security requirements.
Machine Learning Life Cycle: Lead machine learning components that support the handling of datasets, training, testing, and release of new on-device and cloud-based ML models.
Collaborate: Independently collaborate with different stakeholders including Data Scientists, Research Operations, Testing, Firmware, and Hardware to define and implement improvements and new functionality and support internal Data lakehouse consumers in their day-to-day work.
Self-Serve Platform Analytics Platform: Build and maintain a self-serve data infrastructure platform that provides domain teams with the tools and capabilities to create, manage, and consume data products leveraging AI Agents to deliver interactive dashboards.
Analytics Platform Design: Automated insights, predictive analytics, anomaly detection insights.
Data Products: Enable the creation of interoperable, trustworthy data products that can be easily consumed by other domains, often through data pipelines and stores like data lakes or lakehouses.

Requirements

15 + years of leadership experience in data and analytics, including a track record of building and scaling high-performing data teams and cloud-based data platforms.
7+ years of experience hiring, developing, and scaling data teams, including managing managers and fostering leadership growth.
Strong people leader, capable of both strategic leadership and driving execution; experience leading and scaling data and analytics teams north of 20.
Led the data lifecycle from ingestion to delivery
Led data mesh delivery, management and governance
Led Machine Learning (ML) development support and operations
Led data engineering initiatives to build a best-in-class data infrastructure that drives growth across business segments
Established scalable data management and governance frameworks that uphold data quality and integrity in line with industry best practices
Leveraged AI, machine learning, and predictive analytics to enhance efficiency, personalization, and business growth.
Fostered a data-driven culture, enabling data-centric decision-making across all levels of the organization.
Led strategic analytics initiatives that enhance decision-making, operational efficiency, and measurable business outcomes.
Served as a strategic advisor to the executive team, providing data-driven recommendations.
Driven innovation by leveraging emerging data technologies and fostering these capabilities within the team.
Attracted, developed, and inspired top data talent, ensuring alignment with organizational goals.
Familiarity with some of the following: Workflow engines, Stream processing, MLops, Spark, Athena, SQL, dbt, Databricks
A pragmatic, collaborative and goal oriented approach to development.
Strong self-motivation, and a proactive approach to effectively lead and manage your own work.

Benefits

Competitive salary and equity packages
Health, dental, vision insurance, and mental health resources
An Oura Ring of your own plus employee discounts for friends & family
20 days of paid time off plus 13 paid holidays plus 8 days of flexible wellness time off
Paid sick leave and parental leave

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools

data engineeringmachine learningdata governancepredictive analyticsdata lifecycle managementdata meshcloud-based data platformsdata infrastructuredata qualitydata management frameworks

Soft Skills

leadershipstrategic thinkingcollaborationmentoringcommunicationproblem-solvingproactive approachteam buildinginfluencingdata-driven decision making