Data Engineering Manager

Data Engineering Team Lead

London x2 days a month

A fast-growing technology company is looking for an experienced Data Engineering Team Lead to guide and grow its core data infrastructure. This is a key leadership role for someone excited about building scalable systems, managing a high-performing team, and collaborating across disciplines to support advanced analytics, product development, and data-driven decision-making.

Role Overview

You'll take ownership of the data engineering function, ensuring the systems in place are robust, efficient, and capable of handling the company’s growing analytical and operational needs. From mentoring engineers to optimizing pipelines and advising on architecture, this role balances technical execution with strategic oversight.

In this role, you’ll:

• Lead and support a team of data engineers working on the company’s key data platforms
• Design and implement reliable, high-throughput data pipelines to serve diverse analytical and product use cases
• Work closely with analysts, data scientists, and business stakeholders to align data systems with evolving needs
• Promote engineering best practices around version control, testing, observability, and documentation
• Guide improvements to data quality, reliability, and governance through policy and tooling
• Stay current with emerging technologies and make informed recommendations to modernize infrastructure
• Ensure delivery timelines are met while fostering a positive and inclusive team culture

What we’re looking for:

• Hands-on experience building and maintaining cloud-based data systems (e.g., Redshift, BigQuery, Snowflake)
• Strong coding skills in languages commonly used for data work (e.g., Python, Java, Scala)
• Deep understanding of ETL/ELT tools and workflow orchestration platforms (e.g., Airflow, Fivetran, dbt)
• Proficiency with SQL and solid grounding in data modeling concepts
• Familiarity with cloud services and architectures (AWS, GCP, or Azure)
• Proven experience managing or mentoring engineers and driving delivery in an agile environment
• Solid grasp of data security, access control, and compliance principles
• Exposure to real-time or streaming systems such as Kafka or Kinesis
• Knowledge of ML infrastructure or working with data for predictive modelling
• Comfort with infrastructure automation tools like Terraform or Kubernetes

If this role interests you and you would like to learn more, please apply here or contact us via (feel free to include a CV for review).