Data Engineer at Age Bold

Los Angeles, California, United States -

Full Time

Start Date

Immediate

Expiry Date

02 Feb, 26

Salary

200000.0

Posted On

04 Nov, 25

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Data Engineering, Python, SQL, Data Pipelines, Cloud Data Warehouses, ETL, Data Modeling, HIPAA Compliance, Collaboration, Growth Mindset, Healthcare Data, Spark, Databricks, Data Testing, Data Observability, Machine Learning

Industry

Wellness and Fitness Services

Description

Bold is the leading healthy aging platform, offering personalized, evidence-based exercise programs for Medicare members that help prevent falls, reduce musculoskeletal pain, and increase physical activity levels. Innovative Medicare plans rely on Bold to deliver engaging, clinically sound exercise programs that members love to use and that achieve significant health outcomes. Bold is backed by leading investors, including Rethink Impact, Andreessen Horowitz, and Khosla Ventures. Data Engineer Location — [Hybrid, LA] Bold is the leading healthy aging platform, offering personalized, evidence-based exercise programs for Medicare members that help prevent falls, reduce musculoskeletal pain, and increase physical activity levels. Innovative Medicare plans rely on Bold to deliver engaging, clinically sound exercise programs that members love to use and that achieve significant health outcomes. Bold is backed by leading investors, including Rethink Impact, Andreessen Horowitz, and Khosla Ventures. Bold is looking for a Data Engineer to join our LA team and play a central role in building the data infrastructure that powers our member experience, partner analytics, and machine learning initiatives. You’ll help shape how data flows across the company—from ingestion of healthcare data to powering insight-driven decision-making and personalization. As part of our mission-driven team, you’ll have the opportunity to influence the architecture, tools, and practices that will enable Bold to scale securely and intelligently. This is a full-time hybrid role located in LA and will report to the Engineering Manager. As a key member of our Data & Engineering team, here’s what you’ll do: Key Outcomes: Design, build, and maintain scalable data pipelines that power analytics, reporting, and machine learning across the company. Partner with engineering, product, and data science teams to ensure data is reliable, well-modeled, and actionable for decision-making. Architect and implement our modern data stack — leveraging tools such as Snowflake, dbt, Dagster, and Databricks — to handle large, complex healthcare datasets. Develop and enforce data quality, observability, and governance practices that ensure integrity and compliance in a HIPAA-regulated environment. Integrate with healthcare and partner systems (e.g., eligibility feeds, EHRs, claims data) to expand the data ecosystem that drives clinical and engagement insights. Contribute to the design of our data models, transformation logic, and warehouse schema to support both operational and analytical needs. Collaborate on the evolution of Bold’s AI/ML capabilities by building and maintaining reliable, well-documented data pipelines for model training and deployment. The most important skills for the role are*: 4–7+ years of experience in data engineering or a closely related role. Proficiency in Python and SQL, with experience developing data pipelines in modern orchestration frameworks (e.g., Dagster, Airflow, Prefect). Experience with cloud data warehouses (e.g., Snowflake, BigQuery, Redshift) and transformation tools such as dbt. Familiarity with ETL/ELT best practices, data modeling (e.g., star/snowflake schemas), and pipeline performance optimization. Comfort working in a HIPAA-compliant cloud environment (AWS preferred). Strong communication skills and the ability to collaborate across teams to translate business questions into scalable data solutions. A growth mindset — you’re curious, resourceful, and excited to help shape Bold’s evolving data platform. In addition to the above, it would be great if you also had: Experience working with healthcare data (claims, eligibility, EHR) or other regulated data environments. Familiarity with Spark, Databricks, or large-scale distributed data processing. Experience implementing data testing and observability tools (e.g., Great Expectations, Monte Carlo, Datafold). Background in supporting data science or ML engineering workflows. Prior experience in a fast-paced startup environment, navigating ambiguity and helping define data strategy. *We know people from historically underrepresented communities are less likely to apply if they don’t meet all of the above criteria. Please apply anyway! We want people who are fast learners, eager to take on new challenges, and will help us build a best-in-class company that will change what it means to age. Interested? Great! Here’s what you should know: At Bold we know that our people are indispensable to achieving our mission, and we are building an inclusive environment that enables everyone to do their best work. In that spirit, we deliberately hire people from all walks of life — including, but not limited to, race, gender identity, sexual orientation, and disability status. If you’re motivated by our mission and eager to contribute to our team and culture, we’d love to hear from you. Compensation: We’re committed to an inclusive, consistent, and equitable approach to compensation and anticipate that this position will earn between $160k–200k annually. The exact salary will depend on the amount of relevant and transferable experience you bring to the role. You will also receive meaningful equity in the form of a stock option grant. Benefits include: Comprehensive health, dental, and vision insurance 12 weeks of paid parental leave Company-sponsored life insurance Unlimited PTO 401(K) after 6 months of employment Monthly fitness stipend One-time stipend for home office setup Age Bold, Inc. is an equal opportunity employer. We are committed to a safe and supportive work environment in which all employees have the opportunity to participate and contribute to the success of the business. We do not discriminate on the basis of age, race, religion, sex, gender identity, sexual orientation, pregnancy status, national origin, disability, veteran status, or any other factor prohibited by law.

Responsibilities

Design, build, and maintain scalable data pipelines that power analytics, reporting, and machine learning across the company. Collaborate with engineering, product, and data science teams to ensure data is reliable and actionable for decision-making.