Lead Data Engineer

Lead Data Engineer (with Data Analytics Background)

Location: City Of London

Employment Type: Full-time

Salary: £90,000 - £100,000k

Sector: Fintech / Payments

Overview

We are looking for a highly skilled LeadData Engineer with a strong foundation in data analytics to join a growing team. The ideal candidate will have previously worked as a Data Analyst and since transitioned into a more engineering-focused role. You'll help us scale our data infrastructure, design and build robust data models, and contribute directly to our data platform's evolution.

This is a hands-on role where you'll be expected to hit the ground running, contribute to ongoing projects with minimal hand-holding, and help us maintain (and improve) the current team's velocity.

Key Responsibilities

• Design, develop, and maintain data models to support analytical and operational use cases.
• Write efficient, production-grade SQL to build data pipelines and transformations.
• Develop and maintain data workflows and automation scripts in Python.
• Collaborate with analysts, engineers, and stakeholders to deliver high-quality data solutions.
• (Optional but highly valued) Contribute to our infrastructure as code efforts using tools like Terraform.
• Work with modern data warehousing technologies such as Snowflake to ensure scalable and high-performing solutions.

Skills & Experience

• 5+ years of experience in data roles, ideally transitioning from Data Analyst to Data Engineer.
• Proven expertise in SQL and building complex data models.
• Strong proficiency in Python for data processing, ETL, and workflow automation.
• Experience with cloud data platforms (Snowflake experience highly desirable).
• Exposure to or experience with Terraform or similar infrastructure-as-code tools is a strong plus.
• Comfortable working in fast-paced environments and able to contribute quickly without extensive onboarding.

Nice to Have

• Experience with modern data stack tools (e.g., dbt, Airflow, etc.).
• Understanding of CI/CD pipelines and data infrastructure automation.
• Familiarity with data governance, security, and best practices in a cloud environment.