At a Glance
- Tasks: Analyse data, create reports, and develop BI dashboards to drive client insights.
- Company: Join a tech company dedicated to improving public services through innovative solutions.
- Benefits: Enjoy 30 days holiday, flexible remote work, and paid counselling support.
- Other info: Be part of a diverse team committed to inclusivity and continuous learning.
- Why this job: Make a real impact on society while developing your data skills in a supportive environment.
- Qualifications: Experience with data analysis tools and a passion for problem-solving.
The predicted salary is between 37000 - 45000 ÂŁ per year.
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.
Key Responsibilities
- 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.
Skills, Knowledge & Expertise
- Analysis and synthesis
- Application of analytical techniques: Proficiency in applying various analytical methods such as statistical analysis, data mining, and qualitative analysis.
- Synthesis of research data: Experience in synthesising research data to present actionable insights and solutions.
- Engagement with sceptical colleagues: Effective communication skills to engage and gain buy‑in from sceptical colleagues.
- Good understanding of data sources and storage: Familiarity with common data sources and general knowledge of data organisation and storage practices.
- Awareness of data governance: Understanding of data governance standards and a commitment to following data quality practices set by the team.
- Continuous improvement: Ability to contribute to improvements in data management practices by supporting documentation, learning from team training, and actively participating in discussions.
- Toolset support: Experience with using data management tools, with a willingness to learn more about maintaining efficiency and integration.
- Interest in automation: An interest in learning how to automate data management activities to streamline processes and improve accuracy (desirable).
- Compliance with data governance policies: Basic understanding of data governance policies, with a focus on following data security and ethical standards.
- Data cleansing and standardisation: Experience in resolving data quality issues and ensuring data accuracy through cleansing and standardisation techniques.
- Exposure to data integration tools: Basic experience with ETL tools for data integration and storage.
- Collaboration with data professionals: Some experience working with other data professionals, with a focus on learning and improving data modelling and integration practices through teamwork.
- Understanding visualisation requirements: Ability to understand data visualisation needs and create simple, visually appealing representations suited to the audience.
- Good working knowledge of visualisation tools: Experience using tools like Tableau, Power BI, or Python libraries (e.g., Matplotlib, Seaborn).
- Awareness of visualisation standards: Understanding of design principles to create clear and accurate visualisations.
- Willingness to learn from peers: Open to feedback and guidance from senior team members to improve the quality of your visualisations.
- Data quality assurance: Familiarity with data quality assessment techniques, such as data profiling and cleansing.
- Data validation and linkage: Experience performing basic data validation checks and combining data from different sources.
- Data cleansing and preparation: Experience in data preparation, including handling missing values and duplicates.
- Communication of data limitations: Ability to discuss data limitations with guidance from others.
- Participating in peer reviews: Willingness to participate in peer reviews to improve data accuracy.
- Knowledge of statistical methods: Familiarity with common statistical techniques like hypothesis testing, regression analysis, and basic clustering.
- Data analysis and interpretation: Experience using statistical software or programming languages for data analysis.
- Willingness to learn new methodologies: Interest in exploring and applying new statistical techniques.
- Stakeholder communication: Some experience working with different types of stakeholders, both technical and business‑focused.
- Willingness to engage in active and reactive communication: Comfortable sharing updates and responding to inquiries.
- Interpretation of stakeholder needs: Ability to understand basic stakeholder requirements and help translate them into technical solutions.
- Presentation skills: Experience presenting data and insights.
- Problem‑solving skills: Ability to apply logical thinking to break down simpler problems.
- Decision‑making and action‑taking: Experience in making informed decisions and prioritising tasks.
- Adaptability and learning orientation: Willingness to adapt to new challenges and a strong desire to learn and improve continuously.
Job Benefits
- 30 days Holiday – we offer 30 days of paid annual leave + bank holidays.
- 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.
We are always listening to our growing teams and evolving the benefits available to our people. As we scale, we are also providing a flexible benefits platform which includes a Smart Tech scheme, Cycle to Work scheme, and an individual benefits allowance which can be invested 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. We believe we can use tech to make public services better. 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. We’re committed to building a happy, inclusive and diverse workforce.
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' of continuous UK residency. 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 an equal‑opportunity employer. All qualified applicants will receive equal consideration for employment.
Data Analyst in Bristol employer: Made Tech
Contact Detail:
Made Tech Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Analyst in Bristol
✨Tip Number 1
Network like a pro! Reach out to people in the industry, attend meetups, and connect with potential colleagues on LinkedIn. You never know who might have the inside scoop on job openings or can refer you directly.
✨Tip Number 2
Prepare for interviews by practising common data analyst questions. Get comfortable explaining your analytical process and showcasing your problem-solving skills. Mock interviews with friends can really help boost your confidence!
✨Tip Number 3
Show off your skills with a portfolio! Create a few projects that highlight your data analysis and visualisation abilities. This gives you something tangible to discuss during interviews and shows employers what you can do.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen. Plus, we love seeing candidates who are genuinely interested in joining our mission to improve public services with tech.
We think you need these skills to ace Data Analyst in Bristol
Some tips for your application 🫡
Tailor Your CV: Make sure your CV is tailored to the Data Analyst role. Highlight relevant skills and experiences that match the job description, especially in data analysis and visualisation. We want to see how you can contribute to our mission!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you're passionate about using technology to improve society. Share specific examples of how you've used data to drive decision-making in past roles.
Showcase Your Technical Skills: Don’t forget to mention your proficiency with tools like Power BI or Tableau. We love seeing candidates who are eager to learn and adapt, so if you have experience with data management tools, let us know!
Apply Through Our Website: We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you’re considered for the role. Plus, it shows you’re keen on joining our team!
How to prepare for a job interview at Made Tech
✨Know Your Data Tools
Familiarise yourself with the data visualisation tools mentioned in the job description, like Power BI and Tableau. Be ready to discuss your experience with these tools and how you've used them to create impactful dashboards or reports.
✨Showcase Your Analytical Skills
Prepare examples of how you've applied various analytical techniques in past projects. Whether it's statistical analysis or data mining, be ready to explain your thought process and the outcomes of your analyses.
✨Engage with Clients
Since client interaction is key, think of instances where you've successfully collaborated with clients or stakeholders. Highlight how you translated their needs into actionable insights and how you communicated your findings clearly.
✨Demonstrate Continuous Learning
Express your eagerness to learn and adapt, especially regarding new methodologies and data governance practices. Share any recent courses or training you've undertaken that relate to data management or analysis.