Lead Data Engineer

Be among the first 25 applicants

• Marco, Lead Analytics Engineer, is the hiring manager
• We work Mon-Thu in our office in Chancery Lane, London, Fri from anywhere

The basics

• Your title will be Lead Data Engineer
• Marco, Lead Analytics Engineer, is the hiring manager
• We work Mon-Thu in our office in Chancery Lane, London, Fri from anywhere

Compensation

£140,000 + equity

What are we building?

Walk around the average office and you'll see people's days taken up by emails, Slack and meetings instead of real work.

People in client facing roles - think estate agents, insurance brokers, recruiters - feel this pain most acutely. Instead of meeting clients, they spend hours doing admin. Following up. Scheduling meetings, then taking notes on them. Answering questions they've been asked a thousand times. Sorting through the mess that is their inbox.

We've built an AI executive assistant that looks at all your emails, messages and meetings, and uses that knowledge to answer your email, schedule meetings, take next steps from meetings and organise your inbox.

How has it been going?

Since launching in April 2024, we've gone from $0 to $18m in ARR and raised a $30m Series B from top SF investors.

What do we value?

We're very intentional about adding new people. We think a small team of exceptional people working hard at a problem they care about will always beat a larger, more unfocused team. That means you'll need to bring an intensity to this role that might not be asked at other companies. But it also means you will be fast tracked into more senior roles and responsibilities far earlier.

We also believe in hiring people who want ownership and autonomy in their work, and giving it to them. Instead of just being handed tickets, you'll own our data infrastructure, proactively suggesting improvements, including tools we use, and how data is modelled and moved between locations.

What will I do?

In short, you'll own Fyxer AI's end-to-end data platform—powering both our technical infrastructure and all commercial marketing analytics.

• Maintain and improve data pipelines between our warehouse (BigQuery) and multiple data sources—including our production database, Posthog, and the full suite of SaaS tools used by our GTM and marketing teams (HubSpot, Zoominfo, Stripe, Intercom, Customer.io, and more)
• Build new, robust integrations to ingest and model marketing and revenue data—transforming messy, multi-channel customer and campaign data into well-structured, analytics-ready tables
• Optimise our data transformation process (dbt, SQL), ensuring not just performance and ease of querying, but also that marketing and sales teams can accurately track campaign ROI, spend attribution, lead scoring, funnel conversion, and churn risk
• Make architecture decisions that ensure our infrastructure is scalable and secure, but also designed to empower marketing analytics—enabling experimentation, rapid reporting, and actionable GTM insights
• Work directly with stakeholders in marketing, sales, customer success and product to define the key commercial metrics and marketing KPIs we need to monitor—then build and maintain the data models to deliver reliable, real-time reporting
• Collaborate with analysts and business users to ensure all data, especially marketing data, is modelled in the right format for easy dashboarding, self-service analytics, and deep-dive analysis
• Drive innovation across our data stack—automate processes, experiment with new approaches, and find ways for data to proactively surface the signals that help our marketing and GTM teams grow faster

What does our ideal hire look like?

• You've worked at an early stage tech company (<100 people) as an analytics engineer or similar
• You have an expert level understanding of SQL and a modern ELT stack. If you don't have both of these, you shouldn't apply
• You are excellent at transforming raw, and often complex, data into production tables for use for visualization and analysis
• You can interface with both technical and non-technical stakeholders and recommend a data structure for their area that is intuitive and easy to use
• Urgency and intensity in your work

Our tech stack

Broadly, we use a fairly typical ELT stack. It's not a requirement to have worked with every tool we use, but the more the better!

• BigQuery as our data warehouse
• Metabase for data visualization
• Fivetran to pipe raw data from third party tools (eg Stripe, which we use for billing) into our data warehouse
• dbt hosted on Github Actions for transformation of raw data into production tables ready for consumption
• Census for reverse ETL
• Third party tools we interested in analysing, such as Posthog, Stripe, Hubspot, Intercom, and Meta

The application process

• Submit your CV (no need for a cover letter)
• An initial call with someone from the Fyxer AI team to review your experience and motivation for joining (15 mins)
• Meet our Co Founder, Archie - (30 minutes)
• Technical Take Home Test
• Hiring Manager interview - Onsite (45 minutes)
• Meet Tom - COO (30 minutes)