Senior Data Analyst

Made Tech wants to positively impact the country's future by using technology to improve society, for everyone. We want to empower the public sector to deliver and continuously improve digital services that are user‑centric, data‑driven and freed from legacy technology. A key component of this is developing modern data systems and platforms that drive informed decision‑making for our clients. You will also work closely with clients to help shape their data strategy As a Senior Data Analyst, you may play one or more roles according to our clients' needs. The role is very hands‑on and you'll support as a senior contributor role for a project, focusing on: Data analysis and reporting: Conducting in-depth data analysis, generating reports, and providing actionable insights for client projects. Data and BI visualisation: Producing BI dashboards using industry‑standard tools - Power BI, Tableau, Quicksight etc. Client interaction: Collaborating with clients to understand their needs, translating these into analytical solutions, and presenting findings in a clear, actionable manner. Mentoring junior analysts, leading data‑focused projects, and setting best practices in data analysis. You’ll need to have a drive to deliver outcomes for users. You’ll make sure that the wider context of a delivery is considered and maintain alignment between the operational and analytical aspects of the engineering solution. Key responsibilities Analysis and synthesis Application of analytical techniques: Proficiency in applying various analytical methods such as statistical analysis, data mining, and qualitative analysis. Ability to select and apply appropriate techniques based on the context and research data. Synthesis of research data: Experience in synthesising research data to present actionable insights and solutions. Ability to articulate the impact of their analysis on decision‑making and problem‑solving. Engagement with sceptical colleagues: Effective communication and persuasion skills to engage and gain buy‑in from sceptical colleagues. Ability to foster collaboration and address concerns to ensure adherence to best practices. Advisory and critique skills: Capability to advise on the choice and application of analytical techniques and critique colleagues' findings to ensure high standards in data analysis. Data Management Understanding of data sources and storage: Knowledge of various data sources, data organisation, and storage practices. Commitment to maintaining data integrity and accessibility. Advocacy for data governance: Experience in advocating for data governance standards and influencing team adherence to data quality practices. Continuous improvement: Ability to communicate and implement continuous improvements in data management practices through documentation, training, and regular team engagement. Toolset management: Proficiency in defining and supporting common toolsets for data management, ensuring efficiency and seamless integration. Automation of data management: Experience in automating data management activities to streamline processes and increase accuracy. (desirable) Compliance with data governance policies: Understanding and ensuring compliance with data governance policies, maintaining data security and ethical standards. Data modelling, cleansing, and enrichment Data modelling expertise: Proficient in conceptual, logical, and physical data modelling. Ability to adhere to data modelling standards and best practices. Data cleansing and standardisation: Experience in resolving data quality issues and ensuring data accuracy through cleansing and standardisation techniques. Use of data integration tools: Skilled in using ETL tools for data integration and storage. Ensures data interoperability with other datasets. Collaboration with data professionals: Experience collaborating with other data professionals to improve modelling and integration standards and patterns. Interpretation of requirements: Ability to interpret data visualisation requirements and create meaningful, visually appealing representations tailored to the audience. Proficiency in visualisation tools: Experience with tools such as Tableau, Power BI, and Python libraries like Matplotlib and Seaborn. Knowledge of selecting appropriate visualisation types. Application of visualisation standards: Application of design principles to create clear, accurate, and accessible visualisations. Awareness of accessibility considerations. Mentorship in visualisation: Experience in reviewing and advising junior members to improve the quality and efficiency of data visualisations. Data Quality Assurance, Validation, and Linkage Data quality assurance: Experience in implementing processes for data quality assessment and improvement, including data profiling, cleansing, and standardisation. Data validation and linkage: Ability to perform data validation checks and integrate data from various sources to ensure consistency and accuracy. Data cleansing and preparation: Proficiency in defining data cleansing processes and preparing data for analysis by handling missing values, outliers, and duplicates. Communication of data limitations: Skilled in articulating data constraints and limitations to stakeholders, providing context for informed decision‑making. Peer review and quality control: Experience in conducting peer reviews to validate data outputs, ensuring high standards of accuracy and reliability. Statistical Methods and Data Analysis Knowledge of statistical methodologies: Proficient in various statistical methods, such as hypothesis testing, regression analysis, clustering, and time series analysis. Ability to select appropriate techniques based on project requirements. Data analysis and interpretation: Experience in using statistical software or programming languages to perform data analysis and generate insights. Skilled in communicating findings to technical and non‑technical stakeholders. Application of emerging theory: Willingness to explore and apply new statistical methodologies or practices to solve practical problems and adapt to emerging theories. Skills, knowledge and expertise Communication Stakeholder communication: Experience in effectively engaging with a diverse range of stakeholders, including technical and business individuals. Ability to manage expectations and facilitate productive discussions. Active and reactive communication: Proficiency in handling both proactive communication (updates, insights) and reactive communication (responding to inquiries, addressing concerns) to maintain a collaborative atmosphere. Interpretation of stakeholder needs: Ability to understand and translate stakeholder requirements into technical solutions. Experience in bridging the gap between technical and non‑technical stakeholders. Presentation and sharing of insights: Skilled in presenting complex data in a clear, understandable manner tailored to diverse audiences, including senior management. Logical and creative thinking Problem‑solving approach: Ability to apply logical and creative thinking to resolve complex problems by breaking them down and generating innovative solutions. Decision‑making and action‑taking: Skilled in making informed decisions, prioritising tasks, and taking appropriate actions to resolve issues efficiently. Adaptability and learning orientation: Demonstrates adaptability in strategies and a commitment to continuous learning and improvement. Interpretation of stakeholder needs: Ability to understand and translate stakeholder requirements into technical solutions. Experience in bridging the gap between technical and non‑technical stakeholders. Presentation and sharing of insights: Skilled in presenting complex data in a clear, understandable manner tailored to diverse audiences, including senior management. At this point, we hope you’re feeling excited about Made Tech and the job opportunity. Even if you don’t feel that you meet every single requirement, we still encourage you to apply. Get in touch with our talent team if you’d like an informal chat about the role and your suitability before applying. We are hiring for this role directly, so will not respond to any CVs sent via external recruitment agencies. An increasing number of our customers are specifying a minimum of SC (security check) clearance in order to work on their projects. As a result, we're looking for all successful candidates for this role to have eligibility. Eligibility for SC requires 5 years' continuous UK residency and 5 year' employment history (or back to full‑time education). Please note that if at any point during the interview process it is apparent that you may not be eligible for SC, we won't be able to progress your application and we will contact you to let you know why. We are always listening to our growing teams and evolving the benefits available to our people. As we scale, as do our benefits and we are scaling quickly. We've recently introduced a flexible benefit platform which includes a Smart Tech scheme, Cycle to work scheme, and an individual benefits allowance which you can invest in a Health care cash plan or Pension plan. We’re also big on connection and have an optional social and wellbeing calendar of events for all employees to join should they choose to. Here are some of our most popular benefits listed below: Paid counselling - we offer paid counselling as well as financial and legal advice Our hiring process is designed to be thorough, transparent, and supportive, guiding candidates through each step. The exact process may vary slightly depending on the role but these are the typical steps candidates can expect. We’ll keep you updated throughout the process and provide helpful feedback at each stage. No matter the outcome, we make sure the feedback is useful and supportive, so you feel informed and can learn from the experience. Register your interest to be notified of any roles that come along that meet your criteria. #J-18808-Ljbffr