Senior Engineering Manager-People Analytics
This is the employer's own posting, not a copy on a job board.
What we know
Is it still open?
Confirmed still open
Last checked 1d ago — checked against the employer's own applicant tracking system, which is the company answering directly.
We re-read the employer's own applicant tracking system and the posting was still there. That is the company answering directly.
How old is it?
Posted 47d ago
The date the source published, not the day we noticed it (2026-08-24). Last seen at its source 3h ago.
We have tracked this listing since 9 Oct 2026 (1 days). The employer's own board has carried it every time we have read it, most recently 3 hours ago.
Is it remote?
The listing says yes
The location field doesn't say remote, so our assessment is based on the title or the description. Read the listing before applying.
Who may apply?
United States
The description states no restriction of its own. This is the source's own tag.
Pay not stated
Similar roles pay $182.7k–240.4k/yr
Middle 50% of 214 listings that do state pay — Engineering · Manager · United States · USD/year. This employer has published no salary; this is what comparable listings we hold disclose, never converted between currencies or periods. How this is calculated.
Skills named in the ad
Recognised terms only, from a fixed vocabulary — this is what CV matching compares against.
Carried by 1 source
-
Greenhouse employer's own board first seen 1d ago · last seen 3h ago
The listing
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