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Made Tech
Made Tech

Data Analyst

Lakes Hybrid 2-5 yrs exp£37k – £45k / year
Data analysisData visualizationPower BITableauQuicksight
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Requirements

Candidates should have proficiency in statistical analysis, data mining, and data modeling, along with experience using tools like Power BI or Tableau. Strong communication skills and the ability to work with both technical and non-technical stakeholders are essential, as is eligibility for UK security clearance.

Job Description

Data Analyst

Department: Technology

Employment Type: Permanent

Location: Any UK Office Hub (Bristol / London / Manchester / Swansea)

Compensation: £37,000 - £45,000 / year



Description

About Made Tech
Our aim at Made Tech is to use human-centred technology to improve our society. We believe putting people at the heart of designing, building and delivering public services leads to better outcomes 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

About the role
As a 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 contributor 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. 
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 & Synthesis
  • Apply statistical, qualitative, and data mining techniques tailored to research contexts.
  • Synthesize data to deliver actionable insights and articulate impacts on decision-making.
  • Engage effectively with skeptical colleagues to build consensus and buy-in.
Data Management
  • Maintain data accuracy, accessibility, and storage using common data sources.
  • Adhere to team data governance, security, and ethical standards.
  • Support continuous improvement, documentation, and process automation (desirable).
  • Utilize and learn data management tools to maintain integration and efficiency.
Data Modeling, Cleansing & Enrichment
  • Design conceptual, logical, and physical data models using best practices.
  • Perform data cleansing and standardization to resolve quality issues.
  • Gain exposure to ETL tools to ensure data interoperability across datasets.
  • Collaborate with data professionals to refine modeling and integration practices.
Data Visualization
  • Create visually appealing representations tailored to audience requirements.
  • Apply visualization tools (e.g. Tableau, Power BI, Matplotlib, Seaborn).
  • Follow core design and accessibility principles to produce clear, accurate visuals.
  • Incorporate peer feedback to refine visualization quality.
Quality Assurance, Validation & Linkage
  • Conduct data profiling, validation checks, and multi-source data linkage.
  • Prepare datasets by managing missing values, duplicates, and advanced cleansing.
  • Communicate data limitations to assist stakeholders in informed decision-making.
  • Participate in peer reviews to uphold data accuracy standards.
Statistical Methods & Data Analysis
  • Execute statistical techniques including hypothesis testing, regression analysis, and clustering.
  • Analyze data via programming languages/software to share insights with technical and non-technical audiences.
  • Explore and apply emerging statistical methodologies to real-world problems.
Business Skills
  • Manage expectations and interact across technical and business stakeholder groups.
  • Maintain active updates, respond to inquiries, and foster collaborative environments.
  • Translate basic business requirements into technical solutions.
  • Simplify complex data insights into clear presentations for various audiences.
Logical & Creative Thinking
  • Break down problems logically and generate structured solutions.
  • Make informed decisions, prioritize tasks, and resolve issues efficiently.
  • Demonstrate adaptability, curiosity, and a strong continuous learning orientation.


Skills, Knowledge & Expertise

  • Proficiency in applying various analytical methods such as statistical analysis, data mining, and qualitative analysis.
  • 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.
  • Effective communication skills to engage and gain buy-in from sceptical colleagues.
  • Familiarity with common data sources and general knowledge of data organisation and storage practices. 
  • Understanding of data governance standards and a commitment to following data quality practices set by the team.
  • Ability to contribute to improvements in data management practices by supporting documentation, learning from team training, and actively participating in discussions
  • Experience with using data management tools, with a willingness to learn more about maintaining efficiency and integration.
  • Basic understanding of data governance policies, with a focus on following data security and ethical standards.
  • An interest in learning how to automate data management activities to streamline processes and improve accuracy (desirable).
  • Experience with conceptual, logical, and physical data modelling. Ability to adhere to data modelling standards and best practices.
  • Experience in resolving data quality issues and ensuring data accuracy through cleansing and standardisation techniques.
  • Basic experience with ETL tools for data integration and storage, with a focus on learning how to ensure data interoperability with other datasets. 
  • Some experience working with other data professionals, with a focus on learning and improving data modelling and integration practices through teamwork. 
At this point, we hope you're feeling excited about Made Tech and the job opportunity. 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.

SC Eligibility 
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' 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.

Support in applying
If you need this job description in another format, or other support in applying, please email talent@madetech.com.

We believe we can use tech to make public services better. We also believe this can happen best when our own team represents the society that actually uses the services we work on. We’re collectively continuing to grow a culture that is happy, healthy, safe and inspiring for people of all backgrounds and experiences, so we encourage people from underrepresented groups to apply for roles with us.

When you apply, we’ll put you in touch with a member of our talent team who can help with any needs or adjustments we may need to make to help with your application. We’ve put together this blog as a resource to share more about reasonable adjustments and some examples of what this could include. We also welcome any feedback on how we can improve the experience for future candidates.

Life at Made Tech
We’re committed to building a happy, inclusive and diverse workforce. You can get a sense of what it’s like working here from our blog, where we talk about mental health, communities of practice and neurodiversity as well as our client work and best practice.

Like many organisations, we use Slack to chat to each other. The Slack groups that have formed give an idea of the diversity within Made Tech. If you’d like to speak to someone from one of these groups about their experience as an employee, please let one of the Made Tech Talent Team know.
The groups are:
  • antiracist-activists
  • disability
  • lgbtqiaplus-allies-and-activists
  • neurodiversity
  • parents-carers
  • Womxn-in-tech


Job Benefits

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:
30 days Holiday - we offer 30 days of paid annual leave
Flexible Working Hours - we are flexible with what hours you work
Flexible Parental Leave - we offer flexible parental leave options
Remote Working - we offer part time remote working for all our staff
Paid counselling - we offer paid counselling as well as financial and legal advice

Skills

Data analysisData visualizationPower BITableauQuicksightStatistical analysisData miningData modelingETL toolsData cleansingData governanceHypothesis testingRegression analysisClusteringMatplotlibSeaborn