Senior Data Engineer - Data & ML Platform

United States·San FranciscoHybridsenior

Data EngineerData

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Quick Summary

Key Responsibilities

Build, operate, and improve Oura’s Datalake consisting of systems to move, process, and store large amounts of data (Terabyte–Petabyte scale) leveraging tools such as AWS Kinesis, S3, Spark / Glue,

Technical Tools

Data EngineerData

Our mission at Oura is to empower every person to own their inner potential. Our award-winning products help our global community gain a deeper knowledge of their readiness, activity, and sleep quality by using their Oura Ring and its connected app. We've helped millions of people understand and improve their health by providing daily insights and practical steps to inspire healthy lifestyles.

Empowering the world starts with living our values and empowering our team. As a quickly growing company focused on helping people live healthier and happier lives, we ensure that our team members have what they need to do their best work — both in and out of the office.

We are looking for a Senior Data Engineer to join our Data & ML Platform team, responsible for development, maintenance and support for Oura’s Datalake and adjacent systems, collaborating closely with data scientists, analysts and other departments utilizing the Datalake.

This is a hybrid role based in San Francisco, CA, working onsite 1-2 days per week.

We have offices in San Francisco, San Diego and Los Angeles for those who prefer hybrid or office settings. Oura employees in other major cities (like Boston and New York) occasionally gather informally at local co-working locations.

Responsibilities

~1 min read

→Build, operate, and improve Oura’s Datalake consisting of systems to move, process, and store large amounts of data (Terabyte–Petabyte scale) leveraging tools such as AWS Kinesis, S3, Spark / Glue, Athena, dbt, Iceberg, Snowflake, Docker, workflow engines, and more.
→Design and implement data models and pipelines with a strong focus on data quality, reliability, and governance.
→Ensure that our data platform and processes meet privacy, compliance, and security requirements.
→Build components that support the handling of datasets, training, testing, and release of new on-device and cloud-based ML models.
→Independently collaborate with different stakeholders including Data Scientists, Testing, Firmware, and Hardware to define and implement improvements and new functionality and support internal Datalake consumers in their day-to-day work.
→Write code, mostly in Python and SQL with occasional additions Typescript, Java or some other language.

5+ years of experience developing and operating production systems.
Experience running, monitoring, and debugging production systems at scale on a public cloud. We rely on AWS but experience with other cloud platforms counts too.
Good architectural understanding of event-driven architectures, workflow engines, database, and data warehouse systems.
Ability to design robust data models and pipelines, with attention to data accuracy and integrity.
Experience in building infrastructure and components following best practices such as CI/CD and infrastructure as code.
Demonstrated skills in writing well-structured, testable, and high-performance code.
Familiarity with some of the following: Workflow engines, Stream processing, MLops, Spark, Athena, SQL, dbt, Databricks.
You are self-motivated, proactive, and able to lead and manage your own work effectively.
A pragmatic and goal oriented approach to development.

Real-life experience with Databricks.
Familiarity and experience with the Data Mesh approach
Broad knowledge of software fundamentals, databases, warehouses, and system design with experience on various programming languages