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Senior Analytics Engineer

New York City · New York City, New York, United States

Live, first seen by us 28 days ago
Pay
$175,000–215,000/year · Base — pay source
Compensation and Benefits Base Salary: $175,000 to $215,000 per year The range displayed in this job posting reflects the minimum and maximum target for new hire salary for this position. Within the range, individual pay is determined by various factors, including job-related skills, experience, and relevant education or training.
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Work setting
Hybrid — work setting source
Location type: Hybrid
From the employer’s posting
Employment
Full-time — employment source
Employment type: Full-time
From the employer’s posting
Team
Data — team source

Before you apply

Sponsorship
Visa sponsorship not confirmed — sponsorship source
Will you now or in the future require sponsorship for employment visa status?
From the employer’s application form

What you’ll work on

Full posting
  • Design and maintain reusable intermediate and gold models, metrics and access controls

  • Turn stakeholder ideas into validated, published production data products

  • Reconcile conflicting source-system concepts and publish mappings and quality checks

  • Diagnose incorrect or stale results across data layers, partnering with data engineering

  • Review modeling changes and help maintain shared standards

From the employer’s posting
Design and maintain reusable intermediate models, business-facing gold models, metrics, access controls, tests, documentation, and Lightdash agent guidance
Turn ideas into production data products by working with stakeholders to define requirements, validating the results, and publishing them
Reconcile concepts that differ across source systems, and publish mappings, unmatched records, assumptions, and quality checks so conflicts stay visible
Diagnose incorrect or stale results across the data layers, and partner with data engineering when the cause sits below the serving layer
Review modeling changes, pair with teammates, and help maintain shared standards

Benefits in the posting

Full benefits wording
  • Benefits: 401(k) with employer match, health, dental, vision coverage, unlimited paid time off, free lunch in office daily, employee referral bonus program
  • Relocation: Financial support to ease your move to New York City, designed to make the transition smooth and stress-free.

From the employer’s posting.

Apply at Norm Ai

Posting record

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Status in our records
Live
First seen by us
Oct 7, 202628 days ago
Recorded sightings
24
Last seen by us
Nov 4, 2026
Employer says posted
Oct 5, 2026

These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.

How this job compares

Pay

Higher than most similar jobs

$175K–$215K against $122K–$190K, the middle half of what similar US postings state.

From 321 postings in the last year. Stated ranges, not salaries paid.

Time since we first saw it

Day 28

Similar jobs usually come down between day 6 and day 47.

From 1,405 similar postings that came down. Coming down is not always a hire.

Norm Ai is hiring

1 open job

Open jobs by the week we first saw them, last 12 weeks.

Hiring record

See how this role fits your experience

Add your resume and we’ll mark which of these tools you already use, and point out anything in the posting that could rule you out.

  • Python
  • SQL
  • AWS
  • dbt
  • Iceberg
  • Spark
Where the posting names them
- Familiarity with and regular use of AI coding agents. You verify their output and know when they are not the right tool - Strong SQL skills and enough Python experience to understand existing pipelines and build transformation tasks - Clear technical writing. You treat model documentation and metric definitions as part of the data product
- Reconcile concepts that differ across source systems, and publish mappings, unmatched records, assumptions, and quality checks so conflicts stay visible - Deliver changes through the full production process, including SQL, dbt tests, Lightdash metadata, access rules, content validation, and AI agent instructions - Diagnose incorrect or stale results across the data layers, and partner with data engineering when the cause sits below the serving layer
- Experience with Lightdash, or another semantic layer managed as code - AWS knowledge and familiarity with tools like Athena, Iceberg, and Spark - Experience with legal, private equity, or financial services data, including restricted or client-sensitive information
Core Qualifications - 5+ years of analytics engineering or equivalent experience, including contribution to a production dbt project with tests, CI, incremental models, and documentation - Strong dimensional modeling judgment: you can design conformed entities and facts at the correct grain, and make clear decisions when source systems use conflicting definitions

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Job description

View original posting ↗

About Norm Ai
Norm Ai, the agentic law company, has a client base with a combined $30 trillion in assets under management.


Norm Ai pioneered Legal Engineering, the process that empowers lawyers to build and supervise domain-specific AI agents with Norm’s proprietary suite of no-code software tools. Norm Ai technology is deployed inside many of the largest and most consequential institutions in the world.


Norm Ai is also the technology behind Norm Law, LLP, a separate but affiliated AI-native law firm built for the era of agentic AI. Norm Law’s attorneys advise leading institutions across private funds, private equity, venture capital, real estate, registered funds, and financial regulation, using the same legal intelligence platform that powers Norm Ai’s products.

AI Fluency:
Norm Ai prefers all team members to be fluent in AI. Successful candidates actively use AI in their day-to-day work to support thinking, creation, and problem-solving. They use it to improve the quality and speed of their work and to continuously refine how work gets done end-to-end.

Candidates should be prepared to demonstrate and discuss their AI usage throughout the interview process, including concrete examples of tools, workflows, and outcomes. We look for practical, hands-on experience, not theoretical familiarity.

This Role:

The Senior Analytics Engineer will own the analytics data products that our internal teams rely on to make decisions. You will turn prototypes and one-off analyses into trusted, production-grade models and metrics. That means reusable models, business-facing metrics, access controls, tests, documentation, and the guidance our Lightdash AI agents need to answer questions correctly.

This role reports directly to the Director of Data and works closely with the rest of the data team and with internal partners such as GTM and Finance. It is a hands-on role that combines modeling judgment with stakeholder discovery.

What You'll Do:

  • Own analytics data products across internal business functions

  • Design and maintain reusable intermediate models, business-facing gold models, metrics, access controls, tests, documentation, and Lightdash agent guidance

  • Turn ideas into production data products by working with stakeholders to define requirements, validating the results, and publishing them

  • Reconcile concepts that differ across source systems, and publish mappings, unmatched records, assumptions, and quality checks so conflicts stay visible

  • Deliver changes through the full production process, including SQL, dbt tests, Lightdash metadata, access rules, content validation, and AI agent instructions

  • Diagnose incorrect or stale results across the data layers, and partner with data engineering when the cause sits below the serving layer

  • Review modeling changes, pair with teammates, and help maintain shared standards

What We're Looking For:

Core Qualifications

  • 5+ years of analytics engineering or equivalent experience, including contribution to a production dbt project with tests, CI, incremental models, and documentation

  • Strong dimensional modeling judgment: you can design conformed entities and facts at the correct grain, and make clear decisions when source systems use conflicting definitions

  • Experience delivering a metrics or semantic layer used by both people and tools, with safe access controls for sensitive data

  • Familiarity with and regular use of AI coding agents. You verify their output and know when they are not the right tool

  • Strong SQL skills and enough Python experience to understand existing pipelines and build transformation tasks

  • Clear technical writing. You treat model documentation and metric definitions as part of the data product

Nice to Haves

  • Experience with Lightdash, or another semantic layer managed as code

  • AWS knowledge and familiarity with tools like Athena, Iceberg, and Spark

  • Experience with legal, private equity, or financial services data, including restricted or client-sensitive information

  • Experience setting standards or mentoring on a small team

Compensation and Benefits

Base Salary: $175,000 to $215,000 per year

The range displayed in this job posting reflects the minimum and maximum target for new hire salary for this position. Within the range, individual pay is determined by various factors, including job-related skills, experience, and relevant education or training.

Equity: Included

Benefits: 401(k) with employer match, health, dental, vision coverage, unlimited paid time off, free lunch in office daily, employee referral bonus program

Relocation: Financial support to ease your move to New York City, designed to make the transition smooth and stress-free.

 

Work Location

Location: New York City

Work model: Hybrid

In-office expectation: 3–4 days per week

 

To learn more about Norm Ai, visit our website.

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Pay
Compensation and Benefits Base Salary: $175,000 to $215,000 per year The range displayed in this job posting reflects the minimum and maximum target for new hire salary for this position. Within the range, individual pay is determined by various factors, including job-related skills, experience, and relevant education or training.
Location & working pattern

New York City, New York, United States

Location: New York City Work model: Hybrid In-office expectation: 3–4 days per week
Work authorization

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