At a Glance
- Tasks: Lead a high-performing data engineering team and deliver innovative data solutions.
- Company: Dynamic tech company in London with a focus on data excellence.
- Benefits: Competitive day rate, hybrid work model, and opportunities for professional growth.
- Other info: Join a collaborative environment with a focus on innovation and continuous improvement.
- Why this job: Make a significant impact by shaping the future of data engineering.
- Qualifications: Extensive experience in data engineering leadership and strong technical skills.
The predicted salary is between 115000 - 115000 £ per year.
Head of Data Engineering
Location
London
Contract Length
6 months
Day Rate
£575 per day
Work Pattern
- Hybrid (2 days per week in office)
- Overview
We are seeking an experienced Head of Data Engineering to lead the development and delivery of a modern enterprise data platform.
This role will be responsible for defining and executing the data engineering strategy, ensuring scalable, secure, and reliable data solutions that support reporting, analytics, machine learning, and AI initiatives.
The successful candidate will combine strong technical leadership with hands-on knowledge of modern cloud-based data platforms, data architecture, and engineering best practices.
You will work closely with senior stakeholders, architects, analysts, data scientists, and technology teams to deliver business value through high-quality data products and services.
Key Responsibilities
- Data Engineering Leadership
- Lead, mentor, and develop a high-performing team of data engineers.
- Establish engineering standards, best practices, and ways of working.
- Drive a culture of collaboration, accountability, innovation, and continuous improvement.
- Support recruitment, onboarding, capability development, and succession planning.
- Data Platform Strategy & Delivery
- Define and execute the data engineering roadmap and platform strategy.
- Oversee the design, development, testing, deployment, and support of data pipelines and integrations.
- Ensure delivery of scalable, resilient, and secure data solutions aligned with business priorities.
- Drive Agile delivery practices and effective backlog management.
- Collaborate with business and technical stakeholders to translate requirements into robust technical solutions.
- Platform Ownership & Operations
- Act as the technical owner of the data platform.
- Ensure platform availability, scalability, performance, and reliability.
- Implement monitoring, alerting, and observability capabilities across data services.
- Lead incident management, root cause analysis, and service improvements.
- Drive platform optimisation initiatives focused on performance, resilience, and cost efficiency.
- Data Governance & Quality
- Embed data quality controls throughout data pipelines and engineering processes.
- Support data governance, security, compliance, and metadata management initiatives.
- Ensure appropriate lineage, documentation, and operational standards are maintained.
- Partner with business stakeholders to resolve data quality issues and improve data trust.
- Stakeholder Management
- Build strong relationships with senior business and technology stakeholders.
- Communicate progress, risks, dependencies, and delivery outcomes effectively.
- Provide technical leadership and strategic guidance across data-related initiatives.
- Manage relationships with external suppliers and delivery partners where required.
- Engineering Excellence
- Promote automation, reusability, and operational efficiency.
- Champion Data Ops, Dev Ops, CI/CD, and infrastructure automation practices.
- Contribute to the evolution of enterprise data architecture and engineering standards.
- Identify opportunities to improve delivery velocity, platform resilience, and operational effectiveness.
Essential Experience
- Significant experience in Data Engineering, Data Platform Engineering, or Data Architecture leadership roles.
- Proven experience leading and developing engineering teams.
- Strong track record delivering enterprise-scale data platform and data engineering initiatives.
- Experience operating within Agile delivery environments.
- Excellent stakeholder management and communication skills.
- Experience managing multiple priorities within complex organisations.
- Technical Skills
• Microsoft Azure Data Platform technologies, including
- Azure Data Factory (ADF)
- Azure Synapse Analytics
- Microsoft Fabric
- Databricks
- Strong SQL and data modelling expertise.
- Python and modern data engineering frameworks.
- ETL/ELT development and orchestration.
- CI/CD pipelines and Dev Ops practices.
- Data monitoring, observability, and operational support.
- Cloud-native data architecture and modern data platform design.
- Desired Attributes
- Strong leadership and people management capabilities.
- Strategic thinker with a delivery-focused mindset.
- Excellent problem-solving and decision-making skills.
- Ability to influence senior stakeholders and drive change.
- Passion for engineering excellence and continuous improvement.
- Strong commercial awareness and business acumen.
- Contract Details
Location
London
Contract
9 Months
Rate
£575 per day
Working Arrangement
Hybrid (2 days per week in office)
Head of Data Engineering employer: Careerwise
Careerwise is an excellent employer that fosters a collaborative work culture, offering flexible working arrangements with just two days a week in the vibrant city of London. Employees benefit from continuous professional development opportunities and are encouraged to innovate in their roles, making it a rewarding environment for those passionate about data quality and governance.
StudySmarter Expert Advice🤫
We think this is how you could land Head of Data Engineering
✨Tap into Online Data Science Communities
Join online communities focused on data science like Kaggle, LinkedIn groups, or Reddit threads. These are goldmines for temporary gigs, as you can network with professionals and potentially hear about opportunities at companies like Careerwise before they're even advertised!
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Got some cool data science projects? Showcase them on platforms like GitHub or create a personal portfolio website. This visibility is crucial for landing temporary roles—let recruiters see your actual skills in action, which can set you apart from the crowd.
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We think you need these skills to ace Head of Data Engineering
Some tips for your application 🫡
Highlight Your Data Projects:When applying for a temporary data science role at Careerwise, make sure to showcase any relevant projects you've worked on. Whether it's a personal project, an academic undertaking, or contributions to an open-source initiative, detailing these experiences can really set you apart and demonstrate your practical skills.
Emphasise Your Analytical Skills:In your CV and cover letter, focus on the specific analytical skills that are key to data science. Mention any experience with statistical tools, programming languages like Python or R, and data visualisation software. Don't forget to include any certifications that may bolster your expertise!
Show Your Flexibility:Since this is a temporary role, it's important to convey your adaptability and willingness to learn. In your cover letter to Careerwise, emphasise how quickly you can get up to speed with new tools or projects. Highlight any previous experiences where you've had to adjust to new environments or challenges.
Craft a Unique Data-Driven Cover Letter:Instead of the usual generic cover letter, spice it up with some data! Maybe you’ve improved a process by 20% in a past role or cleaned a dataset with over a million entries. Use these stats to your advantage to grab Careerwise’s attention and show the tangible impact of your work.
How to prepare for a job interview at Careerwise
✨Showcase Your Analytical Skills
For a data science gig, it's crucial to demonstrate your analytical abilities. Be ready to discuss previous projects and the methodologies you used. Think about how you can quantify your impact—did your analysis improve efficiency or save costs? These are the stories that will stick with interviewers at Careerwise.
✨Brush Up on Technical Skills
You might face technical questions on tools relevant to data science, like Python, R, or SQL. Prepare to solve a problem live—perhaps they'll ask you to write a simple query or code snippet. It’s cool to talk about them, but we need to show we can do it in practice, especially in a temporary role where quick results matter.
✨Highlight Your Adaptability
Since this is a temporary position, emphasise your ability to learn quickly and adapt to new tools or workflows. Share examples of how you've thrived in fast-paced environments before, and how you can hit the ground running at Careerwise.
✨Prepare a Portfolio of Your Work
Bring your portfolio to the table—showcase projects where you've leveraged data science techniques to solve problems. Whether it’s a GitHub repository or a set of case studies, having tangible examples of your work will help you stand out and show what you bring to the team at Careerwise.
