Senior Analytics Engineer

Norm Ai; United States; Presencial; USD 120.000 - 160.000; Jornada completa

Ventajas ofrecidas por este puesto de trabajo

Competitive salary

401(k) match

Health insurance

Free lunch

Parental leave

Relocation assistance

Bar fee reimbursement

Descripción de la vacante

Norm Ai seeks a Senior Analytics Engineer to own analytics data products across internal business functions and turn prototypes into production-grade models and metrics. You will design reusable models, establish metrics, access controls, tests, and Lightdash guidance while working with stakeholders to define requirements and validate results.

The role emphasizes production-level data products, governance, and collaboration with GTM and Finance, reporting directly to the Director of Data.

Formación

• Familiarity with AI coding agents; verify outputs and know when not to use a tool.
• Experience delivering a metrics or semantic layer used by people and tools with safe data access controls.
• 5+ years of analytics engineering or equivalent, including production dbt with tests, CI, incremental models, and docs.
• Strong SQL and some Python to understand pipelines and build transformation tasks.
• Clear technical writing for model documentation and metric definitions.

Responsabilidades

• Own analytics data products across internal functions.
• Design and maintain reusable intermediate models, 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 results, and publishing them.
• Reconcile concepts across source systems and publish mappings, unmatched records, assumptions, and quality checks.
• 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 data layers and collaborate with data engineering.

Conocimientos

SQL

Python

dbt

Analytics engineering

Lightdash

Modeling

Data governance

Communication

Stakeholder discovery

Herramientas

Lightdash

dbt

AWS

Athena

Iceberg

Spark

Descripción del empleo

• 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
• 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
• 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

Benefits

• Competitive salary and equity
• 401(k) plan with a highly competitive employer matching contribution
• Top-tier health, dental, hospital, accident and vision insurance
• Free lunch provided when working from the office
• Paid parental leave
• Relocation reimbursement to move to NYC
• State bar fee reimbursement

Familiarity with and regular use of AI coding agents. You verify their output and know when they are not the right toolExperience delivering a metrics or semantic layer used by both people and tools, with safe access controls for sensitive data5+ years of analytics engineering or equivalent experience, including contribution to a production dbt project with tests, CI, incremental models, and documentationStrong SQL skills and enough Python experience to understand existing pipelines and build transformation tasksClear technical writing. You treat model documentation and metric definitions as part of the data productStrong dimensional modeling judgment: you can design conformed entities and facts at the correct grain, and make clear decisions when source systems use conflicting definitionsExperience with Lightdash, or another semantic layer managed as codeExperience with legal, private equity, or financial services data, including restricted or client-sensitive informationAWS knowledge and familiarity with tools like Athena, Iceberg, and SparkExperience setting standards or mentoring on a small team