At a Glance
- Tasks: Design and build enterprise-scale data pipelines and solutions for real-world challenges.
- Company: Join Guidant Global, a diverse and inclusive workplace that values every employee.
- Benefits: Hands-on experience with meaningful projects and opportunities for personal growth.
- Other info: Be part of a team that values diversity and fosters innovative solutions.
- Why this job: Tackle complex data problems and shape better data practices in a collaborative environment.
- Qualifications: Strong Python and Spark skills, with experience in data engineering lifecycle.
The predicted salary is between 60000 - 80000 £ per year.
Working Environment
Data engineering work is grounded in real operational needs, often involving imperfect data, technical constraints and organisational complexity. Engineers work closely with delivery teams and stakeholders to understand problems end to end and deliver robust, production-grade solutions. Collaboration, pragmatism and persistence are valued, alongside strong engineering craft.
What You'll Be Doing
- Design, build and improve enterprise-scale data pipelines, platforms and services
- Lead complex data engineering work end to end, from problem definition through build and operational use
- Work directly with technical and non-technical stakeholders to translate real problems into effective data solutions
- Engineer data integrations across diverse systems, including legacy and modern platforms
- Build production-grade data solutions using strong software and data engineering practices
- Improve data quality, lineage and metadata as first-class engineering concerns
- Diagnose and resolve complex data and platform issues in constrained environments
- Provide technical leadership and raise standards through example and delivery
Your Experience
To be successful in this role, you will bring:
- Significant hands-on experience as a senior or lead data engineer on complex, real-world systems
- Strong Python and Spark skills, with evidence of building and maintaining production data pipelines
- Deep understanding of the data engineering lifecycle: ingestion, transformation, storage and serving
- Experience designing data models that support operational and analytical use
- Understanding of data governance, security and compliance built into systems by design
- Confidence working with messy data, legacy constraints and organisational complexity
- Ability to influence through technical delivery rather than formal authority
In Return
You'll work on meaningful data engineering challenges that support real outcomes across the organisation. This is an opportunity to stay hands‑on, tackle difficult data problems, and shape better data practices through delivery rather than abstraction. As an organisation and as a team, Guidant Global are committed to fostering an equitable, diverse and inclusive workplace, where every employee and contractor feels valued and empowered throughout their time with us. We actively seek to recruit talent from all backgrounds, and to draw on a rich blend of experiences, perspectives and creativity. We believe that when people are respected and included, they are motivated to bring their best and whole selves to work, leading to innovative solutions and exceptional outcomes for all parties.
Lead Data Engineer employer: The Client
At Guidant Global, we pride ourselves on being an excellent employer, particularly for the Delivery Manager (AI) role. Our dynamic work culture fosters innovation and collaboration, allowing you to thrive in a fast-paced environment while contributing to meaningful AI projects. With a strong commitment to diversity and inclusion, we offer ample opportunities for professional growth and development, ensuring that every team member feels valued and empowered to make a significant impact.
StudySmarter Expert Advice🤫
We think this is how you could land Lead Data Engineer
✨Get Involved in Data Science Meetups
Tap into local data science meetups or workshops to connect with fellow enthusiasts and professionals. These events are goldmines for networking, and sometimes even lead directly to job openings at companies like The Client!
✨Show Off Your Projects
Start building a public portfolio showcasing your data science projects on platforms like GitHub or personal websites. Highlight unique analyses or models you've developed. This not only demonstrates your skills but also gets your name out there for roles like Lead Data Engineer at The Client.
✨Leverage Professional Networks
Join professional bodies related to data science, like the Data Science Society or similar organisations. Getting involved can lead to mentorship opportunities and insider knowledge about full-time positions at companies like The Client.
✨Apply Directly through Our Website
When you find a suitable opening like Lead Data Engineer at The Client, make sure to apply directly through our website. It gives you an edge and shows you're keen to join our team. Plus, who doesn’t love a direct application? It’s easier than navigating through job boards!
We think you need these skills to ace Lead Data Engineer
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 The Client, 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 The Client. 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 The Client
✨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 The Client!
✨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.
