Angi
Senior Product Manager, Data Infrastructure
Remote - United States · Senior
Sponsorship not specified$150k-$235kDetected 19 days ago
Data EngineeringAgentic AIProduct ManagementRecruitingLeadershipCommunicationPublic Speaking
Stay score
odds of building a lasting career here
55Sponsors, lottery-bound
Cap-exempt (no lottery)0
Sponsors this role65
Entry-level history0
PERM / green-card track0
Lottery odds (Level IV)94
Fits your clock70
Sponsors, but it's cap-subject — you still face the weighted lottery (~61% per draw at Level IV). Good if you win; have a cap-exempt backup on your list.
Lottery odds assume a STEM candidate.
Personalize to your clock →Employer immigration record
from this employer's Department of Labor filings
Green-card filing pattern in this occupation
Context, not a finding about this posting: of this employer's 5 green-card filings in this occupation, 100% were for a worker who already held the job.
Green-card follow-through: 40%
Of 5 labor certifications old enough to have been used, 3 expired without the employer filing the next step. Median time from filing to decision: 497 days.100% of their filings were for a worker who already held the job.Only certifications past the 180-day window are counted — recent ones cannot have expired yet.
Files H-1B transfers
3 transfer filings in the last year, covering 3 workers. Median labor-condition decision: 432 days. An employer that already files transfers is one that can take over an existing H-1B.
Sourced from Department of Labor LCA, PERM and prevailing-wage disclosure data. Employer matching is by name, so figures may be split across an employer's legal entities. Absence of a filing means none appears in our copy of the data, not that none exists.
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About the role
- Every layer of this platform exists to make it easier for a homeowner to hire an Angi Pro, on one certified source of truth that people and AI agents can trust equally.
- The team's strategy is built around one idea: this platform should feel like a self-service product, not a ticket queue, for the engineers and analysts who depend on it, and increasingly for the AI agents who depend on it too.
- This role stewards that platform's product direction.
Responsibilities
- Manage governed platform access - give engineers, analysts, and services safe, auditable access to shared data, and make the safe path the easy path.
- Drive data ingestion and replication - define what self-service ingestion looks like for teams who want to bring their own data onto the platform, and build toward that.
- Optimize compute cost efficiency - find where cost comes from habit rather than real need, and bring it down without anyone losing the developer experience they rely on.
- Build the platform's AI-ready substrate - make agentic workflows safe by default, with the same governed access and audit trail for an agent as for a person.
- Use AI agents in your own daily work, set clear norms so the engineers and peers around you feel safe experimenting with agents and agentic workflows.
- Protect the team's focus and drive real rigor without micromanaging how the work gets done. Steward outcomes, not tasks.
- Build trust across engineering, domain teams, and leadership through empathetic, transparent, and clear communication when addressing complex challenges.
- Work closely with Data Engineering's other delivery teams - Data Mesh Enablement and Managed Data Products - and with the team building Angi's agentic workflows, toward one overall technical strategy.
- Data Mesh Enablement and Managed Data Products - and with the team building Angi's agentic workflows, toward one overall technical strategy.
- Our AI tools are designed to complement, not replace, human decision-making.
Nice to have
- Experience weighing compute cost against performance and developer experience, and driving that tradeoff to a decision rather than just planning around it.
- A proactive approach to navigating and understanding new technical systems, key contacts, and open questions independently.
- work hard and take time when you need it.
- The rare opportunity to work with sharp, motivated teammates solving some of the most unique challenges and changing the world.
- We value diversity
- We know that the best ideas come from teams where diverse points of view uncover new solutions to hard problems.
- Our hiring process may utilize artificial intelligence (AI) tools to assist in candidate screening and assessment.
Compensation
- The base salary band for this position ranges from $150,000 - $235,000, commensurate with experience and performance.
- Compensation may vary based on factors such as geographic location.
Benefits
- This position will be eligible for a competitive year end performance bonus & equity package.
- Full medical, dental, vision package to fit your needs.
- Flexible vacation policy; work hard and take time when you need it.
- Pet discount plans & retirement plan with company match (401K).
- Oversee legacy system retirement - close out systems that are no longer the source of truth, with clear ownership handed off at every step.
- We welcome and value individuals who bring diverse life experiences, educational backgrounds, cultures, and work experiences.
Company info
- Founded in 1995 as Angie's List and rebranded in 2021
- Global company with 9 brands in 8 countries and employees worldwide
- Homeowners have turned to us for 300 million home projects and counting
- access to shared data, orchestration, data ingestion, and the retirement of systems the company has outgrown.
- this platform should feel like a self-service product, not a ticket queue, for the engineers and analysts who depend on it, and increasingly for the AI agents who depend on it too.
- Angi is moving toward AI agents as a normal way of building and operating, and every agent that touches company data comes through this platform first.
- Data Infrastructure builds the platform that every other data team stands on: access to shared data, orchestration, data ingestion, and the retirement of systems the company has outgrown.
This listing is sourced directly from Angi's careers page and normalized into a canonical job model.