Data Engineer

Ledgy; United Kingdom; On-site; GBP 50,000 - 70,000; Full time

Job summary

A modern equity management firm based in the UK is seeking a Data Engineer to build robust data pipelines and architectures. The role requires strong experience in DBT, SQL, and Python. You will optimize data infrastructure and collaborate with teams to drive business decisions. Ideal candidates have proficiency in ETL tools such as Fivetran and experience with GCP. Join a value-driven company focused on transparency and impact.

Qualifications

• 2-3+ years experience building production data pipelines and analytics infrastructure.
• Experience implementing and managing ETL/ELT tools.
• Hands-on experience with GCP (BigQuery) ideal.

Responsibilities

• Manage and optimise data infrastructure and ETL pipelines.
• Develop, test and maintain DBT models.
• Create and manage LookML models in Looker.

Skills

DBT

SQL

Python (Pandas)

ETL tools (Fivetran, Airbyte)

GCP (BigQuery)

Looker

Automation tools (n8n)

SaaS data sources (HubSpot, Stripe)

Job description

At Ledgy, we’re on a mission to make Europe a powerhouse of entrepreneurship by building a modern, tech‑driven equity management and financial reporting platform for private and public companies. In 2025, we aim to be the leading provider for European IPOs and reporting for share‑based payments. We are a value‑based company focused on humility, transparency, ambition and impact, all to deliver the best experience for our customers and end users.

As a Data Engineer at Ledgy, you will build robust data pipelines, design scalable data architecture, and collaborate with teams to deliver insights that drive business decisions. Reporting directly to the Head of Operations & AI, you’ll play a key role in shaping our data engineering strategy.

Responsibilities

• Manage and optimise data infrastructure and ETL pipelines using Fivetran, Airbyte and Google Cloud Platform, ensuring reliable data flow from multiple sources into our analytics ecosystem.
• Develop, test and maintain DBT models that transform raw data into analytics‑ready datasets following best practices.
• Create and manage LookML models in Looker to enable self‑service analytics for stakeholders across the company.
• Drive continuous improvement of our data engineering practices, tooling and infrastructure as a key member of the Operations team.

Qualifications

• 2‑3+ years experience building production data pipelines and analytics infrastructure with DBT, SQL and Python (Pandas, etc.).
• Experience implementing and managing ETL/ELT tools such as Fivetran or Airbyte.
• Hands‑on experience with GCP (BigQuery) is ideal.
• Proficiency in Looker, including LookML development.
• Strong plus if you have experience using n8n or similar automation tools.
• Experience with SaaS data sources (HubSpot, Stripe, Vitally, Intercom).
• Familiarity with AI‑powered development tools (Cursor, DBT Copilot) and a strong interest in leveraging cutting‑edge tools to improve workflow.
• Strong problem‑solving skills and ability to debug complex data issues.
• Excellent communication skills with the ability to explain technical concepts to non‑technical stakeholders.

Job Details

• Seniority level: Mid‑Senior level
• Employment type: Contract
• Job function: Information Technology and Engineering
• Industries: Construction, Software Development, IT Services and IT Consulting
• Locations: London, England, United Kingdom; Liverpool, England, United Kingdom

Referrals increase your chances of interviewing at Ledgy by 2×.