Tesla

Makes electric cars, robotaxis and grid batteries

Analytics Engineer - People Programs

Data EngineeringPosted on Nov 13

Full-timeNo salary listed

About the Job

Requirements

Strong background in analytics, data science, engineering, or a related quantitative field.
Hands-on proficiency in Python and advanced SQL, including the ability to query data, model scenarios, and prototype solutions independently.
Experience building a trusted data layer with dbt and a cloud warehouse such as Snowflake.
A proven track record of identifying a problem, building the case for change, and driving it to completion.
Experience distilling complex analysis into a clear narrative that secures leadership buy-in.
Ability to think from first principles and take action and ownership in unstructured, multi-country environments.

Responsibilities

Design improvements to Tesla's compensation and benchmarking approach across EMEA by defining requirements, evaluating trade-offs, and prioritizing based on impact and feasibility.
Synthesize HRIS, payroll, cycle, and market data into clear recommendations on ranges, structures, and competitive practice, grounded in the cost of labour rather than peer copying.
Engineer a reliable reporting layer using advanced SQL, dbt, and a cloud warehouse such as Snowflake so fragmented rewards sources become one source of truth for cycles, benchmarks, and leadership reviews.
Build prototypes, internal tools, and integrations in Python so compensation questions are answered faster than a traditional engineering cycle allows.
Partner with Compensation, Benefits, Recruitment, HR, Payroll, Finance, and Legal across EMEA so the analysis respects country-level pay rules, statutory context, and Tesla's rewards philosophy, and so offers and hiring ranges follow the same pay logic.
Instrument pay and related rewards programs, monitor performance after a change, and iterate on the programs.
Translate complex benchmarking and pay findings into a narrative that secures leadership buy-in, and drive cross-functional execution until the solution is in use.

Desired Qualifications

Experience with Databricks, PySpark, Airflow, or continuous integration and continuous delivery (CI/CD).
Applied statistical modelling or use of large language models (LLMs) to retrieve unstructured internal knowledge.

Category	Operations & Business Support
Location	London, England
Requisition ID	289984
Type	Full-time

Job Description

Tesla is seeking an Analytics Engineer, People Programs, to specialise in Compensation & Benefits across EMEA. Your primary focus is compensation and benchmarking - how Tesla pays against the cost of labour, where ranges and structures need to move, and which changes are worth making. Benefits work sits alongside that, where it changes total reward or how a program lands in a country. You will identify gaps, build the case for change with rigorous analysis, and drive it to resolution at scale. You will collaborate with Compensation, Benefits, Recruitment, HR Partners, Payroll, Finance, Legal, data engineering, and leadership across multiple countries - and understand what Tesla actually needs rather than copying what other companies do. You will treat pay programs like products: instrumenting them, measuring their impact, and iterating on data. You will turn findings into a narrative that puts data at the center of the decision. Please note that only 1 role is open, based either in London or Amsterdam.

Job Responsibilities

Design improvements to Tesla's compensation and benchmarking approach across EMEA - define requirements, evaluate trade-offs, and prioritize based on impact and feasibility
Synthesize HRIS, payroll, cycle, and market data into a clear recommendation on ranges, structures, and competitive practice, grounded in the cost of labour rather than peer copying
Engineer a reliable reporting layer - Advanced SQL, dbt, and a cloud warehouse such as Snowflake - so fragmented rewards sources become one source of truth for cycles, benchmarks, and leadership reviews
Build prototypes, internal tools, and integrations in Python so compensation questions are answered faster than a traditional engineering cycle allows
Partner with Compensation, Benefits, Recruitment, HR, Payroll, Finance, and Legal across EMEA so the analysis respects country-level pay rules, statutory context, and Tesla's rewards philosophy, and so offers and hiring ranges follow the same pay logic
Instrument pay and related rewards programs, monitor performance after a change, and iterate - the first version is never the final version
Translate complex benchmarking and pay findings into a narrative that secures leadership buy-in, and drive cross-functional execution until the solution is in use

Job Requirements

Strong background in analytics, data science, engineering, or a related quantitative field
Hands-on proficiency in Python and Advanced SQL - able to query data, model scenarios, and prototype solutions independently
Experience building a trusted data layer with dbt and a cloud warehouse such as Snowflake
Proven track record of identifying a problem, building the case for change, and driving it to completion
Experience distilling complex analysis into a clear narrative that secures leadership buy-in
First-principles thinker who defaults to action and ownership in unstructured, multi-country environments
Experience with Databricks, PySpark, Airflow, or CI/CD is an advantage. So is applied statistical modelling, or using LLMs to retrieve unstructured internal knowledge

About the Company

Tesla

Makes electric cars, robotaxis and grid batteries

Tesla makes electric cars and batteries that store power for homes and utilities, and it develops self-driving software and humanoid robots. In 2023, its Model Y became the first electric vehicle to rank as the world's best-selling car. Buyers order the Model 3 sedan, Model Y SUV, or Cybertruck pickup directly from Tesla instead of through dealers, and they charge on its Supercharger fast-charging network. It also sells Megapack and Powerwall batteries, runs a robotaxi service, and charges drivers a monthly fee for self-driving software that still needs their supervision. Tesla was founded in 2003, with Elon Musk as its lead early investor and a recognized co-founder, and it is based in Austin, Texas.

Company size: 10,001+
Company stage: IPO
Headquarters: Austin, TX
Founded: 2003

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