At a Glance
- Tasks: Lead a dynamic team in delivering top-notch data engineering solutions and drive continuous improvement.
- Company: Join PEI Group, a diverse and inclusive employer with a collaborative culture.
- Benefits: Flexible working arrangements, competitive salary, and opportunities for professional growth.
- Other info: Embrace a start-up mentality and thrive in an evolving, unstructured environment.
- Why this job: Make a real impact by leading innovative data projects in a fast-paced environment.
- Qualifications: 8+ years in data engineering, with strong leadership and technical skills.
The predicted salary is between 80000 - 100000 € per year.
As a Data Engineering Manager, you will provide technical and delivery leadership to a multi‑disciplinary team of data engineers, QA engineers, data analysts, and Dynamics 365 developers. You will drive coding standards, delivery excellence, and continuous improvement across the data platform. This is a leadership‑focused role with an 80% managerial and 20% hands‑on split.
Roles and Responsibilities
- Collaborate with Product, Project, and Business stakeholders to plan, prioritise, and deliver data initiatives on time and to a high standard, with adherence to standard processes.
- Manage the delivery pipeline across multiple workstreams, balancing capacity, dependencies, and competing priorities while maintaining a high bar for quality.
- Own and enforce coding standards, pull request review policies, testing practices, and branching strategies across the team.
- Drive data quality, governance, and platform reliability — including data cataloguing, lineage tracking, PII handling, and data quality SLA ownership.
- Optimise data solutions for maintainability, quality, performance, security, and scalability.
- Provide technical leadership and direction across Databricks and Dynamics 365 workstreams, setting clear expectations and objectives for individuals and the wider team.
- Hire, mentor, and performance‑manage engineers and analysts at all career levels, fostering growth, accountability, and a culture of continuous learning.
- Collaborate cross‑functionally with data science, product, finance, and business operations teams to deliver data‑driven solutions.
- Contribute hands‑on through architecture reviews, code reviews, prototyping, and debugging complex production issues — leading by example and staying close to the technology without being on the critical path.
- Drive a continuous improvement process — introduce tooling, automation, and process changes grounded in real data analysis and team feedback.
- Research and evaluate new technologies and trends in data engineering, recommending pragmatic improvements and innovations.
- Prioritise and manage ad‑hoc requests in parallel with ongoing projects.
About You
Requirements Qualification & Experience
- 8+ years of hands‑on experience in data engineering or software development, with significant exposure to data platforms and pipelines.
- A minimum of 3 years of people‑management experience; has built and operated teams of highly skilled engineers and analysts.
- Experience with hiring, mentoring, upskilling, and performance management.
- Proven track record of successfully managing and leading multi‑disciplinary engineering teams.
- Solid understanding of the software and data delivery lifecycle.
Technical Skills
- Strong experience with Databricks (PySpark/Spark SQL, Delta Lake, Unity Catalog, medallion architecture, Databricks Workflows).
- Working knowledge of Microsoft Dynamics 365 data structures, Dataverse, and common integration patterns (Synapse Link for Dataverse, Dataverse APIs).
- Solid understanding of the Azure data ecosystem (Azure Data Factory, ADLS Gen2, Azure DevOps, Key Vault).
- Strong grasp of testing methodologies, CI/CD pipelines, and data quality automation.
- Experience embedding data governance practices — cataloguing, lineage, RBAC, and regulatory compliance (e.g. GDPR).
Personal Attributes
- Exceptional delivery management skills, including planning, executing, and delivering complex data projects across multiple workstreams.
- Ability to operate in an Agile environment with a start‑up mentality and comfort in an evolving, unstructured environment.
- Must be a compelling and clear communicator, able to represent the team to internal and external audiences with differing levels of technical fluency.
- Driving a high‑performance, collaborative, and inclusive team culture in a fast‑paced environment.
At PEI we value diverse talent and welcome applications from everyone – regardless of background. We are an equal opportunity employer and our inclusive culture at PEI is reflected in every stage of the recruitment journey. Please inform us at initial stages of the recruitment process if you require any reasonable adjustments and we can accommodate this. PEI Group supports flexible working arrangements, and we welcome career returners.
Data Engineering Manager employer: PEI Group
At PEI, we pride ourselves on being an exceptional employer that fosters a collaborative and inclusive work culture, particularly for our Data Engineering Manager role. With a strong emphasis on employee growth, we offer ample opportunities for mentoring and professional development, alongside flexible working arrangements that cater to diverse needs. Our commitment to innovation and continuous improvement ensures that you will be at the forefront of cutting-edge data solutions in a dynamic environment, making your contributions both meaningful and rewarding.
StudySmarter Expert Advice🤫
We think this is how you could land Data Engineering Manager
✨Tip Number 1
Network like a pro! Reach out to your connections in the data engineering field and let them know you're on the hunt for a Data Engineering Manager role. You never know who might have the inside scoop on an opening or can put in a good word for you.
✨Tip Number 2
Show off your skills! Prepare a portfolio that highlights your past projects, especially those involving Databricks and Azure. When you get the chance to chat with potential employers, share specific examples of how you've driven coding standards and improved data quality.
✨Tip Number 3
Ace the interview by being ready to discuss your leadership style. Since this role is all about managing teams, think about how you've mentored engineers and fostered a culture of continuous learning. Be prepared to share stories that showcase your ability to lead and inspire.
✨Tip Number 4
Don't forget to apply through our website! It’s the best way to ensure your application gets seen. Plus, it shows you're genuinely interested in joining our team and contributing to our mission of delivering top-notch data solutions.
We think you need these skills to ace Data Engineering Manager
Some tips for your application 🫡
Tailor Your CV:Make sure your CV reflects the skills and experiences that match the Data Engineering Manager role. Highlight your leadership experience and technical expertise in data platforms, as we want to see how you can drive our team forward.
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 your background aligns with our mission at StudySmarter. Be genuine and let your personality come through!
Showcase Your Achievements:When detailing your past roles, focus on specific achievements that demonstrate your ability to lead teams and deliver high-quality data solutions. Numbers and outcomes speak volumes, so don’t shy away from sharing those!
Apply Through Our Website:We encourage you to apply directly through our website for the best chance of getting noticed. It’s the easiest way for us to keep track of your application and ensure it reaches the right people!
How to prepare for a job interview at PEI Group
✨Know Your Data Engineering Stuff
Make sure you brush up on your technical skills, especially around Databricks and Azure. Be ready to discuss your hands-on experience with data platforms and pipelines, as well as how you've implemented coding standards and data governance in past roles.
✨Showcase Your Leadership Skills
Since this role is heavily focused on management, prepare examples of how you've successfully led multi-disciplinary teams. Talk about your experience in hiring, mentoring, and fostering a culture of continuous learning within your teams.
✨Be Ready for Scenario Questions
Expect questions that assess your problem-solving abilities in real-world scenarios. Think about how you would manage competing priorities or handle ad-hoc requests while maintaining high-quality standards across multiple workstreams.
✨Communicate Clearly and Confidently
As a Data Engineering Manager, you'll need to communicate effectively with both technical and non-technical stakeholders. Practice explaining complex concepts in simple terms, and be prepared to discuss how you would represent your team to various audiences.
