Data Engineer (AI Startup)

TN United Kingdom; London; On-site; GBP 45,000 - 75,000; Full time

Job summary

Join a pioneering AI startup that is redefining productivity with its innovative AI Executive Assistant. This role offers you the chance to take ownership of the data infrastructure, ensuring seamless integration and optimization of data pipelines across various platforms. Work in a dynamic environment where your contributions directly impact the company's growth and direction. With a focus on autonomy and responsibility, you'll collaborate with cross-functional teams to drive data initiatives that enhance decision-making and operational efficiency. If you're passionate about data and eager to make a significant impact, this opportunity is perfect for you.

Qualifications

• Experience in maintaining data pipelines and infrastructure.
• Proficiency in SQL and data transformation processes.

Responsibilities

• Own and improve data infrastructure for Fyxer AI.
• Build and maintain data pipelines between sources and warehouse.
• Collaborate with teams to define and monitor key metrics.

Skills

SQL

Data Pipeline Management

Data Transformation

Data Visualization

Stakeholder Collaboration

Education

Bachelor's Degree in Computer Science or related field

Tools

BigQuery

Posthog

Stripe

Intercom

dbt

Job description

Social network you want to login/join with:

• Matt, Cofounder and CTO, is the hiring manager
• We work Mon-Thu in our office in Chancery Lane, London

What are we building? An AI Executive Assistant

In 1930, the economist John Maynard Keynes predicted that we’d only be working 15 hours a week by 2030. Despite automation in agriculture and industry, that hasn’t happened.

Why? The service sector. 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 - sales, professional services firms, recruiters - feel this most acutely. Instead of advising clients, they spend hours on admin. Following up. Scheduling meetings and taking notes on them. Answering repetitive questions over email.

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

Unlike other startups, we’re a pure-play applied AI company, not a SaaS company with AI features hastily bolted on! We make use of the best techniques (fine tuned open source models, tool use, and retrieval augmented generation) and as a result, users send 53% of the email drafts we generate.

How has it been going?

Since launching in March 2024, we’ve gone from $0 to $8m in revenue across thousands of paid users. We did this with a team of 4, and without using any paid marketing until November.

We spent Q4 2024 in San Francisco at HF0, the best AI startup accelerator in the world, learning from experts like the CEO of Instacart, Head of Applied Research at OpenAI and the cofounder of Snowflake.

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.

Requirements

What will I do?

• In short, you’ll own Fyxer AI’s data infrastructure
• Maintain and improve pipelines between our data warehouse (Bigquery) and various data sources, including our production database, Posthog, and the SaaS tools we use - Stripe, Intercom etc, and build new pipelines
• Build improvements to our data transformation process using SQL and dbt, optimising for performance and ease of querying
• Working with stakeholders in the marketing, sales, customer success and product departments to agree metrics that need to be monitored on an ongoing basis, then building data modelling to support this
• Working with data analysts to ensure data is modelled in the correct format to support data visualisation and more detailed analyses

What does our ideal hire look like?

• You’ve worked at an early stage tech company (