Data Lead

Leatherhead
3 months ago
Applications closed

Related Jobs

View all jobs

Data Engineering Lead

Data Strategy Lead

Data Engineer (AWS) - £55k - ID38964

Senior Data Engineer - £55k - ID38964

Data Analytics Manager (App & Retention ) 12 Months FTC

Senior Manager Data Strategy and Insights

Data Lead

24-Month Contract

£62.50 P/ Hour (Outside IR35)

Need BPSS Clearance, Eligible for it; Living in the UK for 5 Years.

Client Hub Office 20%, Remote 20%, Leatherhead 60%

Job Description

We are constructing a multi-disciplinary technology team to deliver a critical path within a public sector Programme. This is an opportunity to join a large-scale EI programme delivering significant benefit to a large public sector department undertaking one of the largest current procurements in the public sector.

A critical role within this team is the Data Lead, who will report to the Senior Transition Manager and support develop, test and transition for the six mobilisations.

Role is for meticulous, thorough and organised data analyst who can work with BAs to ensure data dictionary is created (and mapped to current), development and test data requirements are met, data sources are identified and managed through version control, data migration and/or transition approaches and plans are thorough and delivered and all data products created or revised for handover to BAU Data Lead

Responsibilities
• Data Lead will identify, create and maintain Data Dictionary required to deliver new requirements, ensuring this is mapped to ‘as-is’ Data Dictionary to enable data migration and transition planning to be executed.
• Data Lead will review contractual specifications, detailed business requirements and functional requirements to provide a change/update/remove gap analysis of current vs new
• Data Lead will coordinate new data sources with client counterpart(s) ensuring, these are stored and utilised consistent with the security marking and/or commercial sensitivity (for contractual data sets such as Schedules of Rates) and available to development team.
• Data Lead will advise and assist in creating of synthetic data for development and testing if actual data sets not available or not appropriate for the environment
• Data Lead will identify, create and lead required governance and stakeholder relationships required to ensure data used in development and testing is accurate, appropriate and handled correctly.
• Data Lead will support Senior Transition Manager and Technical Project Manager in ensuring detailed transition planning has clear, realistic and achievable data migration and data transition tasks and milestones to support operational go lives, exit of suppliers and exit of hypercare (priority will be the transition of open work orders from incumbent to new suppliers, requiring planning, multi-organisational governance and reconciliation)
• Data Lead will support Senior Transition Manager in working directly with client in planning operational transition, ensuring client make appropriate decisions required to effect the transition (including but not limited to handling of open work orders, invoicing of part-complete or incomplete work orders by exiting incumbent)
• Data Lead will prepare all required data for transition to live
• Data Lead will take the lead in any required hypercare data reconciliation exercises.
• Data Lead will support Project Coordinator and Technical PM in identifying data risk, issues and assumptions for RAID log.
• Data Lead will support Technical PM in Quality Gateway management, including providing any data products required for the gateway assessments.

Experience Requirements
• Experience of working in a Programme environment involve data migration and transition, or a project where data is being collated, refined, and remodelled in preparation for a similar but distinct environment, taking existing data and cleansing and restructuring for migration from one IT platform to another.
• Experience of data used in CAFM software and/or delivering FM contracts.
• Experience of working with SQL and MS Excel Pivots/Macros
• Experience of gathering and presenting analytics, reports, and findings back to internal and external stakeholders
• Experience of producing materials outlining the transition of data from source to source.
• Experience of systemised processes/ workflows ensuring there is a clear synergy between data flows and business flows.
• Experience being responsible for the integrity of the data being put forward to developers for use in varying systems.
• Experience leveraging data for business insights and decision-making while ensuring data integrity and security is upheld.
• Experience of working in fast-paced projects with fixed go-live dates

Technical Skills/Knowledge
• Intermediate in MS Excel, including working understanding of macros and Pivot tables
• Basic understanding of SQL a benefit
• Some experience using Jira KANBAN or other digital KANBAN
• Good working knowledge of software, integration and hosting technologies (Azure and IaaS virtualized)

Get the latest insights and jobs direct. Sign up for our newsletter.

By subscribing you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

Jobs

Portfolio Projects That Get You Hired for Data Science Jobs (With Real GitHub Examples)

Data science is at the forefront of innovation, enabling organisations to turn vast amounts of data into actionable insights. Whether it’s building predictive models, performing exploratory analyses, or designing end-to-end machine learning solutions, data scientists are in high demand across every sector. But how can you stand out in a crowded job market? Alongside a solid CV, a well-curated data science portfolio often makes the difference between getting an interview and getting overlooked. In this comprehensive guide, we’ll explore: Why a data science portfolio is essential for job seekers. Selecting projects that align with your target data science roles. Real GitHub examples showcasing best practices. Actionable project ideas you can build right now. Best ways to present your projects and ensure recruiters can find them easily. By the end, you’ll be equipped to craft a compelling portfolio that proves your skills in a tangible way. And when you’re ready for your next career move, remember to upload your CV on DataScience-Jobs.co.uk so that your newly showcased work can be discovered by employers looking for exactly what you have to offer.

Jobs Careers

Data Science Job Interview Warm‑Up: 30 Real Coding & System‑Design Questions

Data science has become one of the most sought‑after fields in technology, leveraging mathematics, statistics, machine learning, and programming to derive valuable insights from data. Organisations across every sector—finance, healthcare, retail, government—rely on data scientists to build predictive models, understand patterns, and shape strategy with data‑driven decisions. If you’re gearing up for a data science interview, expect a well‑rounded evaluation. Beyond statistics and algorithms, many roles also require data wrangling, visualisation, software engineering, and communication skills. Interviewers want to see if you can slice and dice messy datasets, design experiments, and scale ML models to production. In this guide, we’ll explore 30 real coding & system‑design questions commonly posed in data science interviews. You’ll find challenges ranging from algorithmic coding and statistical puzzle‑solving to the architectural side of building data science platforms in real‑world settings. By practising with these questions, you’ll gain the confidence and clarity needed to stand out among competitive candidates. And if you’re actively seeking data science opportunities in the UK, be sure to visit www.datascience-jobs.co.uk. It’s a comprehensive hub featuring junior, mid‑level, and senior data science vacancies—spanning start‑ups to FTSE 100 companies. Let’s dive into what you need to know.

Jobs

Negotiating Your Data Science Job Offer: Equity, Bonuses & Perks Explained

Data science has rapidly evolved from a niche specialty to a cornerstone of strategic decision-making in virtually every industry—from finance and healthcare to retail, entertainment, and AI research. As a mid‑senior data scientist, you’re not just running predictive models or generating dashboards; you’re shaping business strategy, product innovation, and customer experiences. This level of influence is why employers are increasingly offering compensation packages that go beyond a baseline salary. Yet, many professionals still tend to focus almost exclusively on base pay when negotiating a new role. This can be a costly oversight. Companies vying for data science talent—especially in the UK, where demand often outstrips supply—routinely offer equity, bonuses, flexible work options, and professional development funds in addition to salary. Recognising these opportunities and effectively negotiating them can have a substantial impact on your total earnings and long-term career satisfaction. This guide explores every facet of negotiating a data science job offer—from understanding equity structures and bonus schemes to weighing crucial perks like remote work and ongoing skill development. By the end, you’ll be well-equipped to secure a holistic package aligned with your market value, your life goals, and the tremendous impact you bring to any organisation.

🍪 We use cookies to enhance your browsing experience on our website. By continuing to use this site, you consent to the use of cookies as described in our Cookie Policy. You can review our Cookie Policy for more information.