Data Engineering Manager

TL;DR

Data Engineering Manager: Leading a team to design, build, and maintain scalable, high-quality data pipelines and models for analytics and decision-making with an accent on engineering excellence and strategic roadmap delivery. Focus on guiding engineers through complex challenges, championing best practices, and ensuring data accuracy and reliability.

Location: Hybrid role, based in London

Company

hirify.global is an equal opportunity employer committed to building world-class data platforms in a regulated environment.

What you will do

• Lead and manage a team of talented data engineers.
• Drive the design, build, and maintenance of scalable, high-quality data pipelines and models.
• Set standards for engineering excellence and champion best practices.
• Shape and deliver the data engineering roadmap, collaborating with architects, analysts, and business leaders.
• Provide clear direction, coaching, and performance management to your team.
• Prioritise delivery, manage risk, and uphold high standards of data quality and operational stability.

Requirements

• Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field.
• Proven experience in data engineering, with a strong track record of building scalable pipelines, integrations, and transformations.
• Demonstrated ability managing and leading data engineering teams.
• Strong proficiency in Scala, Python, SQL, Snowflake, and DBT.
• Deep understanding of data modelling, ETL/ELT processes, and data warehousing concepts.
• Experience working with cloud-based data platforms (AWS, Azure, or GCP) and familiarity with containerisation (Docker, Kubernetes).
• Excellent problem-solving skills and a history of delivering innovative, practical data solutions.
• Strong interpersonal skills with the ability to collaborate across technical and non-technical teams.

Nice to have

• Experience crafting or scaling modern data platforms in a cloud-native environment.
• Exposure to advanced orchestration, observability, or data quality tooling.
• Familiarity with DevOps practices and CI/CD for data engineering.
• Experience operating within a regulated or production-critical environment.

Culture & Benefits

• Hybrid working model.
• Commitment to diversity, equity, and inclusion, ensuring an authentic working culture.
• Equal opportunity employer with inclusive job design.
• Provision for reasonable adjustments to support candidates with disabilities or caring responsibilities.
• Collaborative and high-performing team culture.