Analytics Engineer

Ffern Ltd.; London; Hybrid; GBP 50,000 - 75,000; Full time

Job summary

A rapidly growing company is seeking a mid-senior Analytics Engineer to take ownership of projects within their analytics pipeline. This role will involve building scalable data models, improving pipeline reliability, and ensuring high-quality data access for various stakeholders. The ideal candidate should possess strong SQL skills and have familiarity with dbt and BI tools. Join a fun and laid-back team while enjoying a competitive salary and excellent benefits.

Benefits

Private healthcare

25 days holiday + bank holidays

Flexible remote work schedule

Team meals and outings

State-of-the-art workplace

Ffern membership

Qualifications

• 3+ years in Analytics Engineering or similar data role.
• Strong SQL skills and experience with dbt.
• Ability to communicate with technical and non-technical stakeholders.

Responsibilities

• Build clean, reusable data models and define business-critical metrics.
• Improve pipeline reliability with strong CI/CD practices.
• Create dashboards for decision-making and self-serve analytics.

Skills

SQL

Analytics Engineering

Data Modeling

CI/CD

Communication

Tools

dbt

BI Tools (Lightdash, Looker, Tableau)

Python

Dagster

Airflow

Job description

The Role

Ffern is hiring a mid or senior Analytics Engineer to own projects within our analytics pipeline. The role will focus on building clean, scalable dbt models, improving pipeline reliability and helping stakeholders across the business access trusted, high-quality data. You'll report directly into our Head of Data and work closely with cross-functional teams to maintain robust processes in our fast-growing environment.

Key responsibilities

• Work directly with cross-functional teams to understand business needs and translate them into clean, reusable data models
• Define and maintain business-critical metrics and KPIs across domains
• Build dashboards and reporting layers to support decision-making and self-serve analytics
• Improve pipeline reliability and maintainability with strong CI/CD and testing coverage
• Monitor performance and runtime across the data platform, and make improvements where needed
  

Your Profile

• ~3+ years in an Analytics Engineering or similar data role (e.g. Analyst or Data Engineer)
• Strong SQL and experience building with dbt
• Solid understanding of transforming raw data into clean, business-ready datasets
• Ability to communicate clearly with both technical and non-technical stakeholders
• Experience with BI tools such as Lightdash, Looker or Tableau
• Comfortable with version control, testing frameworks, and CI/CD in a data context
• Familiarity with Python and orchestration tools like Dagster or Airflow is highly desirable
• Experience with Ecommerce and/or Subscription services is desirable

The Interview Process

1. Meet & Greet Call with a Talent Partner
2. Call with the Hiring Manager and live challenge
3. Take home task and task presentation with Head of Data and key stakeholders
4. Founder Interview

At the final stage, we would like to invite to the studio to meet the wider team.

What We Offer

• Competitive salary: Experience dependent
• Healthcare: Private healthcare offered as standard
• Holidays: 25 days holiday + bank holidays, growing by 1 day per year spent with us
• Remote work: All full-time London studio roles are three days a week in the studio, with two days flexible (team lunch at a top Hackney eatery if you come in on the flexible days)
• Ffern membership: All of our team are members of the Ffern ledger
• Team dynamic: Fun, laid-back and sociable team with regular team meals, breakfasts, drinks and outings
• Beautiful work environment: We work from a pair of sunlit studio spaces off Columbia road with state-of-the-art kit, MacBooks and breakout spaces

*N.B. Ffern is growing fast, with a plethora of exciting projects on the horizon. This means our roles are somewhat flexible. If you don't tick every box, but feel passionate about what you could bring to the table, please do apply.