Senior Analytics Engineer

Your purpose in our mission

We’ve raised $17.8 million in Series A funding led by Google Ventures and joined by Khosla Ventures. They believe in our vision that the law should be accessible to everyone. We need you to enable a self-service data culture where teams can access insights independently.

Your manager and team

Our org structure is made up of pods with distinct areas of focus to keep us all working on the most impactful things for our customers all of the time. Some of our team members work across multiple pods. Our structure was conceived with impact, autonomy and velocity in mind and we'd love to share more with you throughout our interview process. Initially reporting to Alex Denne, our Head of Growth (PLG), you’ll be empowered to elevate Genie through the power of data. Both Alex and Nitish, our Co-Founder & CTO will collaborate with you and enable you when you need them to, and will inspire you to push yourself outside your comfort zone.

This is what you’ll be doing

As a Senior Analytics Engineer at Genie AI you’ll get the chance to immerse yourself within the world of law, legal contracts and AI at a fast-paced and autonomous startup. We’re big enough to disrupt the legaltech industry, but small enough that you can make a massive impact on the team. Some of your key day-to-day duties will include:

• Design, build, and maintain the data models which power business insights
• Develop metrics frameworks and dimensions that standardize how we measure business performance
• Work with stakeholders across marketing, sales, product, operations, and machine learning to translate business questions into data solutions
• Enable key stakeholders to share and present data insights across the business
• Enable robust experimental results that remove opinion from discussion—this will ensure high-impact growth/work is done
• Build and maintain a semantic layer that makes data accessible to non-technical users
• Create documentation and training to enable self-service analytics across teams
• Implement and maintain dbt models that transform our raw data into reliable, tested datasets
• Help establish data governance and quality practices as we scale

This is how we’ll set you up for success and the outcomes we expect from you

Over your first 90 days, you can expect us to help point you in the right direction to set you up for success. During the interview process, we can talk you through a high-level overview of your 90-day plan.

By the end of your first three months, we expect you to be:

Month 1: Understand business needs, audit data sources (Mixpanel, Segment, MongoDB, BQ, etc.), map stakeholder requirements, and develop a roadmap towards a simple but modern data stack. You’ll create a few high-value dashboards by working and playing with the data we already have.

Month 2: Implement core data models in BigQuery (probably) or Snowflake/Databricks, create initial dashboards, establish a metrics framework, and set up dbt transformations for key entities.

Month 3: Enable self-service analytics, implement automated reverse ETL for marketing activation campaigns, refine dashboards based on feedback, and deliver actionable insights to growth, sales, finance, and product stakeholders.

We’ll continually develop and measure success on the below criteria

• Insight Activation: Business decisions across growth, product, sales, and strategy are consistently made using data from our analytics platform
• Self-Service Analytics: Teams can answer their own data questions without your involvement using well-designed dashboards and data models
• Single Customer View: Creation of a unified customer data model that connects behavior across platforms and enables personalization within both growth and marketing comms, and product/ML via AI
• Metrics Standardization: Core business metrics are clearly defined, documented, and consistently calculated across the company (grey areas are known to everyone)
• Data Culture: Increased use of data in decision-making, with more teams requesting access to and using analytics tools
• Technical Foundation: Implementation of a sustainable, documented modern data stack that can evolve with our business needs

It can be tough here because

• We don’t structure your work for you. We give you the what and you come up with the how
• We don’t try to get things perfect the first time. We get things to ‘good enough’ and then we continuously iterate
• This is a generalist analytics role—we need you to be good at a lot of data areas rather than specializing in one

But we think you’ll love

• The autonomy and trust we give you to deliver your best work
• Learning from some of the brightest minds in the field of AI
• The exhilaration of a fast-paced startup

The skills you need to succeed in this role

The ideal candidate will have 5+ years of experience and:

• Advanced SQL: Expert-level SQL for complex data modeling and transformation
• Data modeling/transformation: Strong experience with dbt for transforming raw data into analytics-ready datasets
• Cloud data warehouses: Experience with BigQuery (preferred) or Snowflake/Redshift
• Business communication: Proven ability to translate data insights into business outcomes
• Data visualization: Experience creating intuitive dashboards that tell clear data stories
• BI tools: Proficiency with modern tools like Looker, Holistics, PowerBI, or Tableau
• Metrics definition: Experience defining standardized business metrics and dimensions
• Python: Basic programming skills for data transformation and analysis
• Version control: Experience with Git for managing data transformation code
• Product Analytics: Experience with tools like Segment, Snowplow, Mixpanel, or Amplitude

Nice to have:

• Cloud platforms: Familiarity with GCP (preferred) or AWS services
• Data quality: Experience with testing and validating data transformations
• ETL/ELT tools: Familiarity with tools like Fivetran or Stitch
• Reverse ETL: Understanding of how to activate data in marketing tools

(Don’t worry about ticking every single box on the list to be considered for this role.)

The data challenges we'll solve together

We're excited to discuss with you the specific data problems we're working to solve—from unifying user journey data across multiple touchpoints to creating actionable customer segments that drive growth.

You'll help us answer questions like:

• What behaviors predict our highest-value customers?
• How do we measure product adoption across 120,000+ companies and a range of AI features?
• What engagement patterns lead to contract renewals?

You'll work with data from Mixpanel, MongoDB, Segment, Stripe, and more to build a unified view that powers everything from marketing campaigns to product decisions.

Unleash your magic: our interview process

1. Meet our Talent Acquisition Lead, Char, to assess your motivations and baseline skills
2. Complete our take-home task
3. Business/Analytics interview with Alex Denne (Head of Growth) and Rafie Faruq (Co-Founder & CEO)
4. Engineering interview with Nitish Mutha (Co-founder & CTO) and Emile Joubert (Snr Software Engineer - Machine Learning)
5. Culture interview with Char (Talent Acquisition Lead) and Rosie Dent-Spargo (Product Design Lead)

Our benefits

• Generous Stock Options
• Private Healthcare
• Fully Remote Working
• Unlimited Book Budget
• Home Office Setup
• Learning and Development Budget
• Unlimited Holiday
• Parental Leave
• Free access to Genie AI

About Genie AI

Genie AI is a machine learning startup with a mission to enable everyone to draft quality legal documents. We’re redefining the business model of law, disrupting a £750bn industry!

We can’t wait to meet you! Bring your authentic self, and let’s make some legal magic together!