At a Glance
- Tasks: Lead data strategy and governance for impactful government programmes.
- Company: People-first digital consultancy focused on user-centred services.
- Benefits: Competitive salary, inclusive culture, and opportunities for professional growth.
- Other info: Collaborative environment with a focus on continuous learning and innovation.
- Why this job: Shape the future of data in public services and drive meaningful change.
- Qualifications: Experience in data leadership and strong technical expertise in cloud services.
The predicted salary is between 61408 - 75000 £ per year.
About Scrumconnect
At Scrumconnect, we are a people-first digital consultancy that partners with government and private sector organisations to design, build, and deliver user‑centred digital services. We bring together multidisciplinary teams of consultants, designers, engineers, researchers, and data specialists to solve complex challenges and create meaningful outcomes for millions of users. We are passionate about delivering high‑quality digital solutions that improve public services, drive innovation, and create lasting impact. Our culture is built on collaboration, continuous learning, inclusivity, and excellence.
About the Role
Scrumconnect is seeking an experienced Data Lead to lead the development and execution of a strategic data vision for a large‑scale government programme supporting services used by millions of citizens. This role will be responsible for assessing the current data landscape, defining the future‑state architecture and operating model, and creating a roadmap that enables data‑driven decision making, operational excellence, and regulatory compliance. The successful candidate will provide both strategic leadership and technical direction while helping shape and scale the data capability required to deliver long‑term transformation. Working closely with senior stakeholders, delivery teams, architects, and data specialists, you will ensure that data platforms, governance frameworks, and analytical capabilities align with organisational objectives and government standards.
Key Responsibilities
- Data Strategy & Governance
- Lead the development and execution of the overall data strategy.
- Assess and document current ('as‑is') data capabilities, platforms, processes, and governance arrangements.
- Define the target ('to‑be') data architecture, operating model, and roadmap.
- Establish and maintain data governance frameworks, standards, policies, and best practices.
- Ensure alignment with wider government data strategies and organisational objectives.
- Promote a culture of data‑driven decision making across programmes and stakeholders.
- Technical Leadership & Architecture
- Provide technical leadership across data engineering, analytics, and data science initiatives.
- Define and evolve data architecture, engineering standards, tools, and methodologies.
- Design scalable, secure, and resilient cloud‑based data solutions.
- Oversee the implementation of data platforms, ETL/ELT pipelines, and analytical solutions.
- Ensure data services meet both functional and non‑functional requirements, including security, performance, and scalability.
- Drive continuous improvement of data engineering and analytical capabilities.
- Team Leadership & Delivery
- Define the optimal team structure, skills, and capabilities required to deliver the data strategy.
- Lead multidisciplinary teams including data engineers, analysts, data scientists, and architects.
- Mentor and support team members to foster technical excellence and professional growth.
- Collaborate with delivery partners and stakeholders to identify and onboard specialist expertise when required.
- Ensure successful delivery of strategic data initiatives within agreed timelines and budgets.
- Data Quality, Compliance & Security
- Implement robust data quality, lineage, metadata, and governance practices.
- Ensure compliance with GDPR, security policies, government standards, and regulatory requirements.
- Establish monitoring and reporting mechanisms to maintain data integrity and reliability.
- Support audits, risk assessments, and compliance activities.
- Champion secure‑by‑design and privacy‑by‑design principles across all data initiatives.
- Stakeholder Engagement
- Build strong relationships with senior stakeholders across business and technical teams.
- Translate complex technical concepts into clear business outcomes and recommendations.
- Present strategic plans, progress updates, and key insights to executive audiences.
- Facilitate workshops and decision‑making sessions to drive alignment and delivery.
Essential Skills & Experience
- Data Leadership
- Significant experience leading data engineering, analytics, or data science functions within complex organisations.
- Proven track record of developing and delivering enterprise‑wide data strategies.
- Experience establishing data governance frameworks and operating models.
- Technical Expertise
- Strong experience with AWS cloud services and modern data platforms.
- Expertise in designing and implementing scalable data architectures and engineering solutions.
- Experience with ETL/ELT frameworks, data integration, and pipeline automation.
- Strong understanding of data modelling, data warehousing, and transformation methodologies.
- Experience supporting data science and machine learning initiatives from experimentation through production deployment.
- Strong understanding of data security, governance, and operational best practices.
- Public Sector Experience
- Experience delivering data initiatives within government or highly regulated environments.
- Strong understanding of GDPR, information governance, data protection legislation, and public sector compliance requirements.
- Familiarity with Government Digital Service (GDS) standards and ways of working.
- Communication & Leadership
- Excellent stakeholder management and communication skills.
- Ability to influence senior leaders and drive strategic decision‑making.
- Experience building, leading, and mentoring high‑performing data teams.
- Strong facilitation, collaboration, and workshop leadership capabilities.
Technical Environment
- Cloud & Data Platforms
- AWS
- Amazon S3
- AWS Glue
- AWS Lambda
- Amazon Redshift
- AWS Lake Formation
- Data Engineering & Analytics
- SQL
- Python
- ETL/ELT frameworks
- Data Warehousing solutions
- Data Modelling methodologies
- Performance & Digital Analytics
- Google Analytics
- Google BigQuery
- Google Looker Studio
- Google Tag Manager
Desirable Experience
- Experience within benefits, welfare, citizen services, or wider public sector domains.
- Previous experience delivering services through public sector frameworks.
- Security clearance (BPSS, SC, or DV) or willingness to undergo clearance.
- Experience working within Agile multidisciplinary delivery teams.
- Experience defining and scaling enterprise data capabilities and operating models.
Data Lead in London employer: Scrumconnect Consulting
At Scrumconnect, we pride ourselves on being a people-first digital consultancy that fosters a collaborative and inclusive work culture. As a Data Lead, you will have the opportunity to shape strategic data initiatives that impact millions of citizens while working alongside talented multidisciplinary teams. We offer continuous learning opportunities, a commitment to professional growth, and the chance to make a meaningful difference in public services, all within a supportive environment that values innovation and excellence.
StudySmarter Expert Advice🤫
We think this is how you could land Data Lead in London
✨Get Involved in Data Science Meetups
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✨Show Off Your Projects
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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 Scrumconnect Consulting.
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We think you need these skills to ace Data Lead in London
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 Scrumconnect Consulting, 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 Scrumconnect Consulting. 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 Scrumconnect Consulting
✨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 Scrumconnect Consulting!
✨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.
