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- Tasks: Lead a team of data engineers to build innovative data solutions.
- Company: Join Zoopla, a top UK property brand loved by millions.
- Benefits: Enjoy flexible working, generous leave, and wellness perks.
- Why this job: Shape the future of data while making a real impact on home decisions.
- Qualifications: Experience in data engineering management, Python, SQL, and AWS required.
- Other info: Hybrid work model with 2 days in the Tower Bridge office.
The predicted salary is between 48000 - 84000 £ per year.
Get AI-powered advice on this job and more exclusive features.Hybrid Working Pattern – 2 days per week from Tower Bridge officeZoopla is one of the UK\’s most instantly recognisable property brands. In fact, we\’re known and loved by over 91% of the nation (and we\’re working hard on the other 9%). Our mission is to help the nation make better home decisions – by connecting everyone to their home and giving them personalised insights to help with moving, managing or financing. Over 50 million people visit Zoopla every month to access exclusive data and information on every UK property, search over 500,000 homes for sale and rent, find the best agents and secure the latest mortgage deals.We\’re a growing, dynamic team that embraces innovation and isn\’t afraid to push the boundaries. We\’re only just starting our journey to redefine the digital property landscape, with much more to explore and achieve. Join us, and transform the way the nation makes home decisions.We are looking for a Data Engineering Manager to lead our data platform team, build next-generation data solutions, and shape the future of data at Zoopla.Hybrid Working Pattern – 2 days per week from Tower Bridge officeZoopla is one of the UK\’s most instantly recognisable property brands. In fact, we\’re known and loved by over 91% of the nation (and we\’re working hard on the other 9%). Our mission is to help the nation make better home decisions – by connecting everyone to their home and giving them personalised insights to help with moving, managing or financing. Over 50 million people visit Zoopla every month to access exclusive data and information on every UK property, search over 500,000 homes for sale and rent, find the best agents and secure the latest mortgage deals.We\’re a growing, dynamic team that embraces innovation and isn\’t afraid to push the boundaries. We\’re only just starting our journey to redefine the digital property landscape, with much more to explore and achieve. Join us, and transform the way the nation makes home decisions.We are looking for a Data Engineering Manager to lead our data platform team, build next-generation data solutions, and shape the future of data at Zoopla.As a Data Engineering Manager at Zoopla, you will:
Manage and grow a team of talented data engineers/analytics engineers (5 – 8 engineers), providing coaching, mentorship, and career development supportOwn the strategy, delivery, and health of our data platform infrastructure and pipelines, ensuring they are scalable, reliable, and aligned with business goalsCollaborate with cross-functional teams across Product, Software Engineering, Data Science, and Analytics to enable data-driven decisionsDrive the adoption of modern data engineering best practices, including CI/CD, observability, versioning, and testing in data workflowsArchitect and evolve our data platform, including data warehousing (Redshift), lakehouse (Databricks), and orchestration (Airflow, Step Functions) capabilitiesLead efforts around data governance/cataloging, compliance, and security, ensuring data is trustworthy and well-managed
Requirements
Essential skills & experience:
Proven experience in a technical leadership or engineering management role, with responsibility for people management and project deliveryStrong hands-on experience in Python and SQL (bonus: Spark and DBT)Good familiarity with AWS services (e.g. Lambda, S3, Redshift, Glue – Databricks is a plus)Track record of designing and implementing scalable data platforms and ETL/ELT pipelinesKnowledge of data warehousing and data lake architectures, and modern orchestration tools (e.g. Step Functions, Airflow)Experience with infrastructure as code (e.g. Terraform)Understanding of data governance and data quality practicesAbility to communicate technical concepts clearly and influence senior stakeholders
Desirable:
Experience building data pipelines and lakehouse solutions using Databricks on AWSLed and managed teams of 5+ data engineers, delivering high-impact data projects
Benefits
Everyday Flex – greater flexibility over where and when you work25 days annual leave + extra days for years of serviceDay off for volunteering & Digital detox dayFestive Closure – business closed for period between Christmas and New YearCycle to work and electric car schemesFree Calm App membershipEnhanced Parental leaveFertility Treatment Financial SupportGroup Income Protection and private medical insuranceGym on-site in London – or membership in regional offices7.5% pension contribution by the companyDiscretionary annual bonus up to 10% of base salary
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Data Engineering Manager employer: Zoopla
Contact Detail:
Zoopla Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Engineering Manager
✨Tip Number 1
Familiarise yourself with Zoopla's mission and values. Understanding their focus on helping people make better home decisions will allow you to align your experience and vision with theirs during discussions.
✨Tip Number 2
Network with current or former employees of Zoopla, especially those in data roles. They can provide insights into the company culture and expectations, which can be invaluable during interviews.
✨Tip Number 3
Stay updated on the latest trends in data engineering, particularly around AWS services and modern orchestration tools. Being able to discuss recent developments will demonstrate your passion and expertise in the field.
✨Tip Number 4
Prepare to showcase your leadership skills by thinking of specific examples where you've successfully managed teams or projects. Highlighting your ability to mentor and develop talent will resonate well with the hiring team.
We think you need these skills to ace Data Engineering Manager
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights relevant experience in data engineering and management. Focus on your leadership skills, technical expertise in Python, SQL, and AWS services, and any successful projects you've led.
Craft a Compelling Cover Letter: In your cover letter, express your passion for data engineering and how you align with Zoopla's mission. Mention specific examples of how you've driven data solutions and collaborated with cross-functional teams.
Showcase Technical Skills: Clearly outline your hands-on experience with data platforms, ETL/ELT pipelines, and orchestration tools. If you have experience with Databricks or Terraform, make sure to highlight that as well.
Prepare for the Interview: Anticipate questions about your management style and how you handle team dynamics. Be ready to discuss your approach to data governance and how you ensure data quality and compliance.
How to prepare for a job interview at Zoopla
✨Showcase Your Leadership Skills
As a Data Engineering Manager, you'll be expected to lead a team. Be prepared to discuss your previous experiences in managing teams, providing mentorship, and how you've supported career development for your team members.
✨Demonstrate Technical Expertise
Make sure to highlight your hands-on experience with Python, SQL, and any relevant tools like Spark or DBT. Be ready to discuss specific projects where you designed scalable data platforms or implemented ETL/ELT pipelines.
✨Understand the Business Context
Zoopla is focused on helping people make better home decisions. Familiarise yourself with their mission and think about how your role can contribute to this goal. Prepare examples of how you've aligned technical strategies with business objectives in the past.
✨Prepare for Cross-Functional Collaboration
Collaboration is key in this role. Be ready to discuss how you've worked with cross-functional teams, such as Product, Software Engineering, and Data Science, to drive data-driven decisions and improve processes.