At a Glance
- Tasks: Lead a data transformation project for a global food manufacturer using Azure technologies.
- Company: Join a leading global food manufacturing company focused on innovation.
- Benefits: Competitive salary, flexible working options, and opportunities for professional growth.
- Other info: Collaborate with a talented offshore team and engage with senior stakeholders.
- Why this job: Make a real impact by driving critical data initiatives in a dynamic environment.
- Qualifications: Experience in data engineering and strong leadership skills required.
The predicted salary is between 70000 - 90000 £ per year.
This role provides a unique opportunity to lead a critical data transformation workstream for a global food manufacturing leader, driving data readiness across enterprise platforms while leading a hybrid onsite-offshore analytics pod leveraging modern Azure-based data technologies.
Your responsibilities:
- The Onsite Data Lead will play a critical role in driving Customer’s data transformation programme by anchoring an analytics data pod supporting in-flight business-critical initiatives.
Impact Summary:
- Lead end-to-end delivery of a business-critical data workstream already in execution, accelerating outcomes rather than starting from scratch.
- Enable data readiness for operations, testing, cutover, and go-live across multiple enterprise platforms.
- Orchestrate integration across ERP (SAP S/4HANA), planning, MES and supply chain systems, ensuring unified and consistent data.
- Drive data lake, analytics, and reporting capabilities using Azure / Power BI ecosystem.
- Act as the single point of leadership onsite, coordinating with senior stakeholders and leading a 4-member offshore pod.
Key responsibilities:
- Lead and accelerate an existing data workstream, ensuring continuity and delivery pace.
- Define and drive the data readiness roadmap for testing, rehearsal, cutover, and operations.
- Identify and manage data objects across domains (master, transactional, production, supply chain).
- Coordinate data collection, cleansing, structuring and validation across multiple systems.
- Ensure data consistency across platforms (SAP, MES, planning, etc.).
- Work with business stakeholders (finance, supply chain, plant ops) and SMEs.
- Lead and govern offshore team delivery (Technical Lead, BA, Developers).
- Track and manage data quality, completeness, risks and dependencies.
- Engage with vendors, implementation partners, and program leadership teams.
- Provide day-to-day leadership, stakeholder management, and escalation handling.
Essential skills/knowledge/experience:
- Strong experience in Data Engineering / Data Management / Data Migration programs.
- Proven leadership in data delivery within large transformation programmes.
- Hands-on experience with Azure data stack (ADLS Gen2, ADF / Fabric, SQL, Power BI).
- Exposure to ERP & manufacturing ecosystems (SAP S/4HANA, MES, Planning systems).
- Strong understanding of:
- Data structures (master, transactional, operational data).
- Data quality, governance, and lifecycle.
- Experience managing onsite–offshore delivery models.
- Ability to engage business + IT stakeholders across functions.
- Strong programme execution, problem-solving, and escalation management.
Data Lead in Huntingdon employer: Vallum Associates
As a Data Lead at our global food manufacturing company, you will thrive in a dynamic work culture that prioritises innovation and collaboration. We offer competitive benefits, including professional development opportunities and a supportive environment that encourages growth and learning. Join us in a location that fosters creativity and teamwork, where your contributions will directly impact our data transformation initiatives and drive meaningful change across the organisation.
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We think this is how you could land Data Lead in Huntingdon
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We think you need these skills to ace Data Lead in Huntingdon
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!
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Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at Vallum Associates. 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 Vallum Associates
✨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!
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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 Vallum Associates!
✨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.
