Analytics Engineer (Product & Marketing)

Some of the basics:

Hiring Manager: Marco Giglio (Data Lead)

What are we building?

Great people are working on overdrive to do a great job, but are held back because their inbox is failing them.

We’re building an AI Productivity tool that eliminates the admin burden for people who work client facing roles. Think real estate, consultants, recruiters - people who spend hours on emails, scheduling, and follow ups. Fyxer AI simplifies these tasks by organizing your inbox, drafting replies in your own voice, and taking crisp meeting notes.

The best part? Unlike a lot of other AI tools, ours actually gets used.

We’ve built the product so it requires little set up & nothing extra for users to learn. It works directly inside Outlook, Gmail, & Zoom.

How It’s Going

Since launching in May 2024, we’ve gone from $0 to $11M+ in revenue, with thousands of paying users.

We raised a $10M Series A in Feb 2025, backed by Marc Benioff (Salesforce) and 20VC, to scale toward $50M.

We’ve been through HF0 in San Francisco, the world’s leading AI startup accelerator, learning directly from leaders at OpenAI, Snowflake, and Instacart.

We’re now in hyper growth mode and data is at the heart of how we scale.

Why This Role Matters

As our first Analytics Engineer with a product & marketing focus, you'll empower the teams closest to our users and growth engine.

You’ll build clean, fast, flexible data models that unlock insight across product usage, user behaviour, marketing performance, monetisation, and retention.

Beyond data modelling, you’ll help answer critical business questions:

• What drives retention across user types?
• Which features correlate with conversion or churn?
• How should we allocate budget across growth channels?
• Where are users dropping off in onboarding or product adoption?

• Own and improve the data pipelines that power analytics and decision-making across the company (BigQuery, dbt, Fivetran, Census).
• Transform raw data into clean, production grade models using SQL and dbt.
• Collaborate closely with product managers, growth marketers, and customer success to define, structure and automate key metrics (e.g., feature adoption, activation, LTV, funnel performance).
• Make architecture decisions that scale as the business grows.

• Define best practices for naming conventions, table ownership, and documentation.

You Might Be a Fit If:

• You’ve owned data pipelines or transformation layers in a high-growth startup (<100 people).
• You’re fluent in SQL, experienced with dbt, and confident working with modern ELT tools (Fivetran, Census).
• You love working at the intersection of data, product and growth not just surfacing numbers, but helping others act on them.
• You’ve worked with teams that obsess over activation, conversion, retention, and CAC/LTV.
• You think about data as a product… well-modeled, easy to query, version-controlled, and documented.

• You’re biased to action, detail-oriented, and can communicate clearly with both engineers and non-technical teams.
• You’ve worked closely with PMs and growth teams on strategic decisions.
• You’re comfortable doing exploratory analysis, not just building clean pipelines.
• You’ve written deep-dive memos or built dashboards that directly informed product or GTM decisions.

Our Data Stack

We use a modern ELT setup:

• BigQuery (warehouse)
• dbt (transformation, deployed via GitHub Actions)
• Fivetran (ingestion)
• Census (reverse ETL
• Metabase (BI/dashboarding)
• Plus: Posthog, Stripe, Hubspot, Intercom, Meta Ads, and our internal production database

Interview Process:

1. Submit your CV no cover letter needed
2. Intro call with someone from the Fyxer AI team (20–30 mins)
3. Meet with Marco - Data Lead (30 mins)
4. Live challenge (60 mins)
5. Final interview (45 mins)
6. Meet the leadership for a final culture + impact chat (30 mins)

• You’ll be the go-to data expert for product and marketing decisions.
• You’ll have real ownership over systems, models and strategy.
• You’ll work with a sharp, fast, ambitious team who deeply value data.