Data Engineering Manager

Data Engineering Manager

Full-Time 60000 - 80000 £ / year (est.) Home office (partial)
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At a Glance

  • Tasks: Lead a talented Data Engineering team to create reliable data pipelines and solutions.
  • Company: Join a forward-thinking company committed to diversity and innovation.
  • Benefits: Enjoy a competitive salary, hybrid work model, and opportunities for professional growth.
  • Other info: Collaborative environment with a focus on best practices and career development.
  • Why this job: Make a real impact by delivering high-quality data solutions that drive business success.
  • Qualifications: 5+ years in data engineering management with strong technical and people skills.

The predicted salary is between 60000 - 80000 £ per year.

We’re looking for a Data Engineering Manager who will be responsible for leading and developing our small but talented Data Engineering team to meet ever‑increasing demands for reliable, robust data pipelines to ingest data into our Data Platform and supply consistent, trustworthy datasets to other teams across the business. The role will lead and develop a team of data engineers, partner closely with stakeholders across the organisation, and ensure best practices in data quality, governance, and platform reliability. This is a hybrid role, with an expectation to be in the Bristol office 2 days per week. Occasional travel may be required for client or internal meetings, both in the UK and abroad.

Responsibilities

  • Lead and develop the Data Engineering team, ensuring timely, high‑quality delivery aligned to business and client needs.
  • Own the planning and execution of data solutions and products, balancing priorities, resources, timelines and budgets.
  • Ensure the delivery of reliable, scalable and secure data infrastructure that supports both internal and client‑facing use cases.
  • Partner closely with stakeholders across the business to translate requirements into actionable data solutions and manage expectations.
  • Provide expert Data Engineering input to Sales, Client Services and Project Management, supporting commercial and delivery outcomes.
  • Drive best practice across Data Engineering and Architecture, including data quality, testing, observability and documentation.
  • Collaborate with platform and architecture colleagues to evolve and operate the data platform in line with the agreed roadmap.

Skills and Experience

  • 5+ years experience managing high-performing Data and/or Analytics Engineering teams in a commercial environment.
  • Hands‑on experience working in a modern cloud platform. AWS preferred, but experience of Azure and/or GCP is also beneficial.
  • Strong technical experience as a Data or Analytics Engineer.
  • Highly effective people management skills, with a history of supporting Engineers to grow and develop.
  • Excellent organisational and project management skills, with experience balancing workloads against business demands across multiple projects in parallel.
  • Good commercial awareness, conscious of cost optimisation and resource planning.
  • Experience of working within delivery frameworks such as Agile or Lean.
  • Strong skills in Project Management tools such as Jira or Azure DevOps.
  • Demonstrable ability to articulate technical concepts clearly and concisely, including presenting to a blend of technical and non‑technical audience.
  • Excellent verbal and written English.
  • The ability to support and potentially step in on bits of delivery where needed.
  • Experience with modern data tools such as Snowflake, dbt, Airflow and Dagster would be advantageous.

Equal Opportunities

adm-Indicia is proud to be an equal opportunity employer and is committed to creating a diverse environment. We recruit, employ, develop, compensate, and promote regardless of race, religion, colour, national origin, sex, disability, age, veteran status, and other protected status as required by applicable law. Should you need any reasonable adjustments made to this application process, please don't hesitate to let us know.

Data Engineering Manager employer: Indicia Ltd

At Indicia, we pride ourselves on being an exceptional employer, offering a dynamic work culture that fosters innovation and collaboration. Our Bristol office provides a hybrid working environment, allowing for flexibility while ensuring our Data Engineering team thrives in a supportive atmosphere. With a strong focus on employee growth, we provide ample opportunities for professional development and encourage our team members to take ownership of their projects, making a meaningful impact within the organisation.
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Contact Detail:

Indicia Ltd Recruiting Team

StudySmarter Expert Advice 🤫

We think this is how you could land Data Engineering Manager

✨Network Like a Pro

Get out there and connect with people in the industry! Attend meetups, webinars, or even just grab a coffee with someone who’s already in a data engineering role. Building relationships can open doors that a CV just can’t.

✨Show Off Your Skills

Don’t just talk about your experience; demonstrate it! Create a portfolio showcasing your projects or contributions to data solutions. This gives potential employers a tangible sense of what you can bring to the table.

✨Ace the Interview

Prepare for those interviews by practising common questions and scenarios related to data engineering. Be ready to discuss your management style and how you’ve led teams to success. Confidence is key!

✨Apply Through Our Website

We encourage you to apply directly through our website. It’s the best way to ensure your application gets the attention it deserves. Plus, you’ll be one step closer to joining our awesome team!

We think you need these skills to ace Data Engineering Manager

Data Engineering
Team Leadership
Cloud Platforms (AWS, Azure, GCP)
Data Infrastructure
Stakeholder Management
Data Quality Assurance
Project Management
Agile Methodologies
Lean Methodologies
Jira
Azure DevOps
Technical Communication
Modern Data Tools (Snowflake, dbt, Airflow, Dagster)
Organisational Skills
Commercial Awareness

Some tips for your application 🫡

Tailor Your CV: Make sure your CV is tailored to the Data Engineering Manager role. Highlight your experience in managing teams and delivering data solutions, as well as any relevant technical skills. We want to see how your background aligns with what we're looking for!

Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to tell us why you're passionate about data engineering and how you can lead our team. Be sure to mention specific projects or achievements that demonstrate your expertise.

Showcase Your Technical Skills: Don’t forget to highlight your hands-on experience with cloud platforms like AWS, Azure, or GCP. Mention any modern data tools you've worked with, such as Snowflake or Airflow, to show us you’re up to date with industry standards.

Apply Through Our Website: We encourage you to apply through our website for a smoother application process. It helps us keep everything organised and ensures your application gets the attention it deserves. Plus, we love seeing candidates who take that extra step!

How to prepare for a job interview at Indicia Ltd

✨Know Your Data Inside Out

Make sure you’re well-versed in the data tools and technologies mentioned in the job description, like AWS, Snowflake, and dbt. Brush up on your knowledge of data pipelines and be ready to discuss how you've implemented them in past roles.

✨Showcase Your Leadership Skills

As a Data Engineering Manager, you'll need to lead a team. Prepare examples of how you've successfully managed teams in the past, focusing on how you supported their growth and development. Be ready to discuss your approach to balancing workloads and managing expectations.

✨Understand the Business Needs

Familiarise yourself with the company’s goals and how the Data Engineering team fits into the bigger picture. Think about how you can translate business requirements into actionable data solutions and be prepared to share your thoughts during the interview.

✨Prepare for Technical Questions

Expect to face technical questions that assess your problem-solving skills and understanding of data engineering principles. Practice articulating complex concepts clearly, as you’ll need to communicate effectively with both technical and non-technical stakeholders.

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