Senior Engineering Manager - Machine Learning Data Enablement
About this role
Upstart requires a Senior Engineering Manager to address data bottlenecks that slow down machine learning innovation across the lending platform. The Machine Learning Data Enablement team owns the entire data lifecycle from source to inference, and this leader will define the strategy to make discovering, evaluating, trusting, and productionizing data much faster. Daily responsibilities include managing engineers across data integration and quality, partnering with machine learning and product teams, and accelerating the onboarding of third-party datasets.
This position exists to transform raw information into a durable competitive advantage by scaling infrastructure and enforcing strict data contracts and SLAs. A successful candidate brings a strong background in distributed systems, production data pipelines, and technical leadership within engineering organizations. Someone who thrives in cross-functional environments and enjoys removing operational friction to empower model development will find this opportunity rewarding.
What you will do
- Lead and scale a high-performing engineering organization spanning data integration, quality, metadata, and machine learning infrastructure.
- Define and execute the technical strategy to increase data evaluation velocity and reduce production cycle times.
- Implement robust data quality frameworks including ingress-level monitoring, drift detection, and reconciliation checks.
- Promote company-wide adoption of data contracts and service level agreements for critical datasets.
- Standardize vendor intake, secure retro ingestion, and build templated integrations to speed up third-party data onboarding.
- Unlock internal data domains by improving metadata coverage, lineage standards, and discoverability.
What you need
- Bachelor's degree in Computer Science, Engineering, Mathematics, or a related field, or equivalent experience.
- Minimum of 8 years of engineering experience, including at least 3 years of direct people management.
- Demonstrated history of owning production data pipelines that support offline training and online inference.
- Proven capability building data systems using modern stacks like Databricks, Spark, Python, SQL, AWS, and streaming frameworks.
- Experience driving complex cross-functional initiatives and negotiating dependencies with business and technical stakeholders.
- Background in designing and enforcing observability, incident loops, and data quality frameworks for production systems.
Nice to have
- 10+ years in data engineering and machine learning platform roles with 5+ years of management experience
- Experience with feature stores and real-time feature delivery
- Strong knowledge of lakehouse architecture and big data processing frameworks
- Familiarity with DevOps and infrastructure-as-code practices such as Kubernetes, Terraform, and CI/CD
- Experience in fintech or other regulated environments
Benefits
- Competitive compensation including base pay, bonus opportunities, and annual equity grants
- Retirement benefits including a 401(k) with a company match of $2 for every $1 contributed up to $15,000 annually
- Employee Stock Purchase Plan with discounted stock purchase options
- Comprehensive medical, dental, vision, and wellness coverage with Health Savings Account contributions
- Paid time off, sick leave, company holidays, and paid family and parental leave
- Annual wellness and productivity allowances for personal development and workspace setup
Skills and tech stack
Questions candidates ask
What is the remote work policy for this role?
Upstart is proudly digital-first, giving most employees the flexibility to work from wherever they thrive across the US and Canada. The company is intentional about in-person connection through team onsites, and employees can choose to work from home or collaborate from offices in Columbus, Austin, the Bay Area, or New York City.
What is the salary range for this position?
The anticipated base salary for this position is expected to be within the range of $195,000 to $270,000 USD. Actual base pay depends on geographic location using the company's compensation regions, alongside job-related skills, experience, and relevant education.
What kind of team will I be leading?
You will lead the ML Data Enablement team, which is a platform team with end-to-end ownership of the data lifecycle powering all machine learning models. The team builds scalable infrastructure, standardized workflows, and quality guarantees across external vendors and internal datasets.
What technologies are used in this stack?
The tech stack includes Databricks, Spark, Python, SQL, AWS, streaming systems, orchestration frameworks, Kubernetes, Terraform, and CI/CD tools.