At a Glance
- Tasks: Lead and develop a Data Engineering team while tackling impactful technical challenges.
- Company: Innovative SaaS company transforming data into actionable insights.
- Benefits: Competitive salary, direct exposure to leadership, and clear progression opportunities.
- Other info: Work on cutting-edge AI products with real commercial impact.
- Why this job: Shape the future of data engineering in a high-growth AI-focused environment.
- Qualifications: Experience leading Data Engineering teams with strong SQL and Python skills.
The predicted salary is between 85000 - 85000 £ per year.
London (4 days per week in the office) | £85,000 + Benefits
This is a rare opportunity to build and lead a Data Engineering function within a rapidly growing AI and data-focused technology business.
You'll take ownership of engineering standards, team development, and platform-critical data infrastructure while remaining hands-on with the most impactful technical challenges.
The Company
They are an innovative Saa S organisation that helps businesses transform complex data into actionable insights.
Operating across a range of industries, they deliver advanced data and AI solutions that support commercial decision-making and customer growth.
With multiple products already in market and further AI-driven solutions under development, they are investing heavily in their data capabilities as they continue to scale.
This is a high-growth environment where technology plays a central role in the company's success.
The Role
As Lead Data Engineer, you will be responsible for establishing and leading the Data Engineering function while working closely with senior stakeholders across technology, product, and data teams.
Key responsibilities include
- Defining Data Engineering standards, processes, and best practices across the organisation.
- Leading, mentoring, and developing a growing team of Data Engineers.
- Designing and delivering scalable ETL and ELT pipelines across operational, analytical, and AI workloads.
- Taking ownership of cloud-based data platforms and modern data architecture.
- Driving improvements in data modelling, platform performance, and engineering quality.
- Leading CI/CD practices, deployment processes, and engineering governance.
- Collaborating with Data Science and AI teams to productionise machine learning outputs.
- Identifying opportunities to leverage AI-enabled development tools across the engineering lifecycle.
- Implementing monitoring, validation, and governance frameworks to ensure reliable data delivery.
- Your Skills & Experience
- Commercial experience leading or managing Data Engineering teams.
- Strong SQL and Python development skills.
- Expertise building and maintaining scalable ETL and ELT pipelines.
- Strong understanding of data modelling and modern data architecture principles.
- Experience working with Azure, AWS and/or GCP cloud platforms.
- Knowledge of Git, CI/CD, Dev Ops practices, and deployment workflows.
- Experience improving engineering standards, processes, and team capabilities.
- Ability to work effectively with technical and non-technical stakeholders.
- Interest in AI-enabled engineering practices and modern data platforms.
- What They Offer
- Direct exposure to senior technology leadership.
- Opportunity to build and shape an entire Data Engineering function.
- Work on cutting-edge AI and data products with real commercial impact.
- Clear progression opportunities as the business continues to grow and expand.
- #J-18808-Ljbffr
Lead Data Engineer 199727 employer: Harnham
Join a leading UK-based media organisation at the forefront of digital transformation, where your role as Director of Streaming Product and Growth will be pivotal in shaping the future of their subscription services. With a strong emphasis on innovation and a collaborative work culture, you'll have access to significant growth opportunities, competitive salary packages, and a performance-based bonus structure, all while working in a dynamic environment that values data-driven decision making and customer-centric strategies.
StudySmarter Expert Advice🤫
We think this is how you could land Lead Data Engineer 199727
✨Get Involved in Data Science Meetups
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We think you need these skills to ace Lead Data Engineer 199727
Some tips for your application 🫡
Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!
Quantify Your Achievements:Employers love numbers! When drafting your CV, highlight your achievements with quantifiable results. For instance, mention how your data analysis led to a certain percentage increase in efficiency or revenue at a previous job or project. These details can really make your application pop!
Craft a Tailored Cover Letter:For a full-time role at Harnham, your cover letter should reflect your passion for data science and your excitement about the specific projects or values of the company. Dive into why you’re a good fit, how your skills align with their needs, and any unique perspectives you can bring to the team.
Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at Harnham. Mention any standout courses you've completed that equipped you with essential skills, such as machine learning certifications or data visualisation courses. This shows your commitment to continuously developing your skills in the field!
How to prepare for a job interview at Harnham
✨Brush Up on Your Statistics
For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!
✨Showcase Your Projects
Prepare a killer portfolio showcasing your data science projects. We should include details about the datasets used, the tools and techniques applied, and the impact of your findings. If we can walk them through a particularly challenging project or a cool visualisation that had real-world implications, it’ll really make us stand out!
✨Get Comfortable with Python and R
Most data science positions require us to be proficient in programming languages like Python and R. We should practice common libraries like pandas, NumPy, and scikit-learn, and be ready for live coding exercises or algorithm questions. Showing off our coding chops can really impress the interviewers at Harnham!
✨Prepare for Case Studies
Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.
