At a Glance
- Tasks: Lead a high-performing data engineering team and build scalable data platforms.
- Company: Join Quilter, a forward-thinking company focused on data-driven solutions.
- Benefits: Enjoy competitive salary, private medical insurance, and generous holiday allowance.
- Other info: Embrace a diverse and inclusive culture with excellent career growth opportunities.
- Why this job: Make a real impact by transforming raw data into actionable insights.
- Qualifications: Degree in a technical field or equivalent experience; strong team management skills required.
The predicted salary is between 70000 - 90000 € per year.
About the Role
The role sits within the Chief Data Office (CDO) and reports to the Head of Data Platforms. This role accelerates Quilter’s data strategy by defining engineering standards, building scalable data platforms, and leading a high‑performing data engineering team. The Data Engineering Manager plays a pivotal role in delivering business value through enabling actionable insights. This position partners with colleagues and stakeholders across the organisation to transform raw data into usable, reliable, high‑quality data products. It requires a blend of technical expertise, business acumen, and team leadership skills to create a data‑driven culture across the organisation.
Team Management & Growth
- Lead a team of data engineers through coaching, mentorship, and technical guidance.
- Support individual career development and performance feedback, creating growth opportunities for your team.
- Foster a collaborative, inclusive, and high‑performance team culture.
Technical Oversight & Delivery
- Define data engineering standards and best practices to ensure robust, efficient, and secure product delivery.
- Guide the design and implementation of scalable data pipelines and data products.
- Review architecture and code, provide technical direction, and resolve complex engineering challenges by being hands‑on when needed.
- Ensure delivery of high‑quality, reliable solutions aligned with business goals and engineering best practices.
Cross‑Functional Collaboration
- Partner with product managers, data scientists, analysts, and business stakeholders to understand requirements and prioritise work.
- Work closely with platform and data analysis teams to develop delivery processes that continually improve business outcomes.
- Translate business needs into actionable engineering detailed plans and ensure timely delivery of key projects.
- Communicate clearly across technical and non‑technical teams to align on priorities and progress.
Operational Excellence
- Promote operational stability and reliability of data pipelines and systems through monitoring, alerting, and incident response.
- Advocate for high standards in data quality, governance, and compliance by collaborating with platform and data governance teams.
- Drive continuous improvement in development workflows and team productivity.
Qualifications
- Degree in a technical discipline (e.g., computer science, engineering, maths, physics) or evidence of equivalent practical experience.
About You
- Proven experience in managing and growing technical teams within a complex business environment.
- Strong technical hands‑on experience in building and maintaining data pipelines on Databricks and Fabric environments within Azure.
- Experience implementing batch and stream pipelines in a kappa architecture.
- Experience implementing data quality frameworks, SLAs, and observability tooling.
- Familiarity with data governance practices (lineage, cataloguing, access control).
- Ensuring compliance with regulatory requirements (e.g., GDPR, data retention controls).
- Setting technical direction and establishing engineering standards.
- Managing roadmaps, sprint planning, and delivery across multiple projects or squads.
- Experience of data engineering across multiple layers and modelling techniques including a Kimball and Data Vault.
Skills
- Strategic thinker with a curious mindset and strong problem‑solving skills.
- Ability to communicate complex concepts in a clear, concise manner.
- Databricks: Delta Lake, Unity Catalog, Workflows, Notebooks, Clusters, MLflow.
- Azure: ADLS Gen2, Azure Data Factory, Event Hubs/Kafka, Key Vault, Functions, Synapse.
- Spark: strong knowledge of Spark internals, optimisation, partitioning, performance tuning.
- Languages: Python, SQL, optionally Scala.
- CI/CD: Azure DevOps pipelines with asset bundles for data engineering deployments.
- Orchestration: ADF, Databricks Workflows, or other scheduling frameworks.
- Knowledge of Data Modelling: Kimball, Data Vault.
Inclusion & Diversity
We value diversity and strive to promote inclusivity in all aspects of our culture. We believe in equal opportunities for all, ensuring that no applicant encounters less favourable treatment based on anything but their skills, qualifications, experience, and potential. We celebrate the unique contributions of a diverse workforce and create a respectful, nurturing environment where every colleague can thrive.
Core Benefits
- Holiday: 182 hours (26 days).
- Quilter Incentive Scheme: All employees are eligible to participate in the incentive scheme, to incentivise business performance and their contribution.
- Pension Scheme: A non‑contributory company pension scheme that can be boosted through personal contributions.
- Private Medical Insurance: Single cover as standard with options to increase cover to include your partner or children.
- Life Assurance: 4× your salary.
- Income Protection: 75% of salary, less state benefits, payable after 26 weeks of absence.
- Healthcare Cash Plan: Jersey employees only.
- In addition to our core benefits, we offer a range of flexible benefits to UK employees that you can choose from and pay for conveniently via a salary deduction.
Data Engineering Manager employer: Quilter
Quilter is an exceptional employer that fosters a collaborative and inclusive work culture, particularly for the Data Engineering Manager role based in Southampton or London. With a strong emphasis on employee growth through mentorship and career development opportunities, Quilter also offers competitive benefits such as a generous holiday allowance, a non-contributory pension scheme, and private medical insurance, ensuring that employees feel valued and supported in their professional journey.
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, attend meetups, and engage in online forums. You never know who might have the inside scoop on job openings or can refer you directly.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those involving data pipelines and engineering standards. This will give potential employers a taste of what you can bring to the table.
✨Tip Number 3
Prepare for interviews by brushing up on both technical and soft skills. Be ready to discuss your experience with tools like Databricks and Azure, but also practice explaining complex concepts in simple terms to non-technical folks.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, it shows you’re genuinely interested in joining our team at Quilter.
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 align with the Data Engineering Manager role. Highlight your technical expertise, team management experience, and any relevant projects you've led. We want to see how you can bring value to our team!
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 makes you a perfect fit for this role. Don't forget to mention your leadership style and how you foster a collaborative team culture.
Showcase Your Technical Skills:In your application, be sure to highlight your hands-on experience with tools like Databricks and Azure. We love seeing specific examples of how you've built and maintained data pipelines or implemented data quality frameworks. This is your moment to impress us with your technical prowess!
Apply Through Our Website:We encourage you to apply directly through our website. It’s the best way to ensure your application gets into the right hands. Plus, it shows us you're serious about joining our team at StudySmarter!
How to prepare for a job interview at Quilter
✨Know Your Data Engineering Standards
Before the interview, brush up on the latest data engineering standards and best practices. Be ready to discuss how you would define these for a team and ensure robust product delivery. This shows that you’re not just technically savvy but also understand the importance of quality in data management.
✨Showcase Your Leadership Skills
Prepare examples of how you've successfully led teams in the past. Think about specific instances where you coached or mentored team members, and how you fostered a collaborative culture. This will demonstrate your ability to grow and manage a high-performing team, which is crucial for this role.
✨Communicate Clearly Across Teams
Practice explaining complex technical concepts in simple terms. You’ll likely need to collaborate with non-technical stakeholders, so being able to translate technical jargon into understandable language is key. Prepare scenarios where you’ve done this effectively in previous roles.
✨Be Ready for Technical Challenges
Expect to face some hands-on technical questions or challenges during the interview. Brush up on your experience with Databricks, Azure, and data pipeline architectures. Being prepared to solve problems on the spot will showcase your technical expertise and confidence in handling complex engineering tasks.
