Senior Engineering Manager-People Analytics at SoFi

Job description

Employee Applicant Privacy Notice Who we are: Shape a brighter financial future with us. Together with our members, we’re changing the way people think about and interact with personal finance. We’re a next-generation financial services company and national bank using innovative, mobile-first technology to help our millions of members reach their goals. The industry is going through an unprecedented transformation, and we’re at the forefront. We’re proud to come to work every day knowing that what we do has a direct impact on people’s lives, with our core values guiding us every step of the way. Join us to invest in yourself, your career, and the financial world. Role Summary: This role will lead the data engineering function supporting People Analytics, including AI-assisted workforce analytics on Snowflake. This is a player-coach role requiring hands-on technical leadership plus people leadership, with strong business partnership and the ability to balance speed, quality, governance, and innovation. What you’ll do: Manage and develop data engineers Manage, coach, and grow a team of data engineers. Set expectations for quality, collaboration, delivery, and technical ownership. Create a strong engineering culture where people solve hard problems, move quickly, and enjoy the work. Collaborate with cross-functional teams, such as other data engineers, people analysts, data scientists, and business stakeholders, to translate requirements into production-ready deliverables, and communicate technical trade-offs to non-technical partners. Stay hands on Write and review production code. Lead design reviews, code reviews, and technical problem solving. Step into critical pipelines, models, or AI workflows when needed. Build scalable People data foundations Design and maintain sustainable data models, pipelines, semantic layers, and testing frameworks. Establish team practices for documentation, lineage, data quality, and observability. Own engineering standards Set standards for SQL, Python, dbt, Airflow, Snowflake, testing, documentation, CI/CD, and release management. Ensure the team ships work that is reliable, maintainable, secure, and understandable. Enforce data governance policies and practices to maintain data integrity, security, and compliance with relevant regulations. Support AI enabled analytics Own technical delivery for AI-assisted workforce analytics and internal tools. Translate business needs into scalable technical designs, delivery plans, and engineering milestones. Partner with People Analytics, People leaders, Legal, Compliance, and other stakeholders to deliver trusted workforce insights. Partner on semantic models, evaluation datasets, testing, and quality controls for AI-assisted analytics Balance speed and rigor Create enough process to protect quality, privacy, and trust for sensitive People data without slowing the team unnecessarily. What you’ll need: A bachelor's degree in Computer Science, Data Science, Engineering, or a related field. 7+ years in data engineering, analytics engineering, or data platform engineering. 5+ years managing or formally leading engineers. Proficiency in data engineering tech stack: Python / SQL / dbt / Airflow / Gitlab . Experience designing dimensional models, semantic layers, data marts, or analytical data products. Experience with data quality, testing, lineage, observability, and production support. Strong ability to translate business needs into technical architecture. Experience with sensitive or regulated data and access controls. Proven ability to coach engineers and build healthy technical culture Strong communication with technical and non technical stakeholders Proficiency in relational and cloud database platforms such as Snowflake, Redshift, or GCP. Thorough knowledge of data modeling, database design, data architecture principles, data operations, and CI/CD. Strong analytical and problem-solving abilities, with the capability to simplify complex issues into actionable plans. Preferred Experience People analytics, HR data, compensation, talent, workforce planning, or Workday experience Experience building AI, LLM, RAG, or natural language analytics products Experience with Snowflake Cortex AI, Streamlit, semantic models, or evaluation frameworks Experience in fintech, banking, or regulated environments Compensation and Benefits The base pay range for this role is listed below. Final base pay offer will be determined based on individual factors such as the candidate’s experience, skills, and location. To view all of our comprehensive and competitive benefits, visit our Benefits at SoFi page! SoFi provides equal employment opportunities (EEO) to all employees and applicants for employment without regard to race, color, religion (including religious dress and grooming practices), sex (including pregnancy, childbirth and related medical conditions, breastfeeding, and conditions related to breastfeeding), gender, gender identity, gender expression, national origin, ancestry, age (40 or over), physical or medical disability, medical condition, marital status, registered domestic partner status, sexual orientation, genetic information, military and/or veteran status, or any other basis prohibited by applicable state or federal law. The Company hires the best qualified candidate for the job, without regard to protected characteristics. Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records. New York applicants: Notice of Employee Rights SoFi is committed to an inclusive culture. As part of this commitment, SoFi offers reasonable accommodations to candidates with physical or mental disabilities. If you need accommodations to participate in the job application or interview process, please let your recruiter know or email accommodations@sofi.com. We are unable to accommodate remote work from Hawaii, Alaska or Puerto Rico at this time. Internal Employees If you are a current employee, do not apply here - please navigate to our Internal Job Board in Greenhouse to apply to our open roles.

Requirements

Must-haves

Employee Applicant Privacy Notice
Manage and develop data engineers
Manage, coach, and grow a team of data engineers.
Set expectations for quality, collaboration, delivery, and technical ownership.
Create a strong engineering culture where people solve hard problems, move quickly, and enjoy the work.
Stay hands on
Write and review production code.
Lead design reviews, code reviews, and technical problem solving.
Step into critical pipelines, models, or AI workflows when needed.
Build scalable People data foundations
Design and maintain sustainable data models, pipelines, semantic layers, and testing frameworks.
Establish team practices for documentation, lineage, data quality, and observability.
Own engineering standards
Set standards for SQL, Python, dbt, Airflow, Snowflake, testing, documentation, CI/CD, and release management.
Ensure the team ships work that is reliable, maintainable, secure, and understandable.
Enforce data governance policies and practices to maintain data integrity, security, and compliance with relevant regulations.
Support AI enabled analytics
Own technical delivery for AI-assisted workforce analytics and internal tools.
Translate business needs into scalable technical designs, delivery plans, and engineering milestones.
Partner with People Analytics, People leaders, Legal, Compliance, and other stakeholders to deliver trusted workforce insights.

Nice-to-haves

People analytics, HR data, compensation, talent, workforce planning, or Workday experience
Experience building AI, LLM, RAG, or natural language analytics products
Experience with Snowflake Cortex AI, Streamlit, semantic models, or evaluation frameworks
Experience in fintech, banking, or regulated environments

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

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Platform: greenhouse
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