At a Glance
- Tasks: Lead data analysis projects and collaborate with teams to drive business improvements.
- Company: Dynamic company focused on data-driven solutions and innovation.
- Benefits: Flexible working hours, competitive salary, and opportunities for professional growth.
- Other info: Join a supportive team that values continuous improvement and knowledge sharing.
- Why this job: Make a real impact by transforming data into actionable insights for businesses.
- Qualifications: Experience in data analysis, strong communication skills, and familiarity with SQL.
The predicted salary is between 45000 - 55000 £ per year.
- Description
- Business Discovery & Analysis
- Lead and facilitate discovery activities to understand business problems, opportunities and desired outcomes before defining solution requirements.
- Identify opportunities to improve business capabilities through better use of enterprise data.
- Lead current and future state analysis across business processes, information flows and data domains.
- Present options, trade-offs and recommendations to support informed business decisions.
- Collaborate with Analytics and AI teams to define business requirements that enable analytical and AI-driven solutions.
- Elicit, analyse and validate business requirements using a range of techniques including workshops, interviews, process analysis, document analysis and data analysis.
- Define business processes, business rules, KPI definitions, data requirements and acceptance criteria that enable successful delivery.
- Challenge assumptions and help stakeholders refine their thinking to ensure solutions address the underlying business need.
- Identify, document and evaluate functional and non-functional requirements, ensuring they are clear, complete and testable.
- Data Analysis & Governance
- Define conceptual and logical data requirements and models.
- Work with Data Architects to understand information models and data flows and analyse data lineage and source-to-target data flows to support successful solution design and delivery.
- Help define business data definitions, critical data elements and KPI definitions.
- Support business data ownership, stewardship and governance activities, such as definition and maintenance of business metadata, business glossaries and critical data definitions.
- Identify data quality issues and support improvements to trusted business information.
- Delivery & Collaboration
- Collaborate with Product Owners and delivery teams to support backlog refinement, epic decomposition, story mapping and the definition of clear acceptance criteria.
- Collaborate with delivery teams to refine and prioritise requirements, ensuring the highest-value outcomes are delivered first.
- Ensure requirements remain traceable throughout the delivery lifecycle and support clarification where required.
- Support business readiness, user acceptance testing and solution adoption where appropriate.
- Manage multiple initiatives simultaneously, balancing priorities while maintaining quality and stakeholder confidence.
- Identify and communicate risks, assumptions and dependencies throughout delivery.
Responsibilities
- Stakeholder Management
- Build trusted relationships with business and technical stakeholders, acting as the trusted Business Analysis lead for your initiatives.
- Facilitate workshops and discussions that build consensus, resolve ambiguity and support effective decision making.
- Communicate clearly and proactively, ensuring stakeholders remain informed of progress, decisions, risks and dependencies.
- Act as the conduit between business stakeholders and delivery teams, ensuring information flows effectively in both directions.
- Continuous Improvement
- Apply agreed Business Analysis standards, templates and governance processes consistently across projects.
- Identify opportunities to improve delivery, requirements quality and stakeholder collaboration, sharing recommendations with the wider team.
- Support colleagues through knowledge sharing, peer reviews and mentoring where appropriate.
- Contribute lessons learned and practical improvements to Business Analysis ways of working.
Qualifications
- Capability, Knowledge, and Experience Technical
- Proven experience delivering Business Analysis on complex data, reporting or analytics initiatives, with strong analytical skills with experience using SQL to support analysis and validation; experience of working with modern data platforms such as Azure Databricks, Snowflake, Microsoft Fabric.
- Experience defining reporting, analytics and operational data requirements, including KPI definitions and business rules.
- Good understanding of data management principles, including data governance, data quality, data modelling, data lineage, data architecture and analytics.
- Familiarity with the Software Development Lifecycle and delivery approaches including Agile, Scrum and Waterfall.
- Demonstrable experience delivering Business Analysis within Agile delivery teams, with the ability to become productive quickly in a complex environment.
- General
- Excellent communication, facilitation and stakeholder management skills.
- Strong workshop facilitation and requirements elicitation techniques.
- Ability to analyse complex problems and translate them into clear, structured and actionable requirements.
- Comfortable working across both business and technical teams.
- Experience producing high-quality Business Analysis artefacts including Business Requirements Documents, Epics, User Stories, Process Models and Requirement Traceability.
- Strong organisational skills with the ability to manage multiple priorities simultaneously.
- Experience within Financial Services or Insurance is desirable.
- Understanding of GDPR and data management principles.
Education & Qualifications
- Educated to degree level in a relevant field or able to demonstrate equivalent professional experience
- Related Business Analyst or Project Management professional qualifications are beneficial but not essential
Data Analysis employer: Zensar Technologies
Zensar Technologies is an exceptional employer that fosters a culture of innovation and collaboration, making it an ideal place for professionals seeking to make a significant impact in global transformation initiatives. With a strong commitment to employee growth, Zensar offers extensive training and development opportunities, ensuring that team members can advance their careers while working on cutting-edge Salesforce CRM modernization projects. Located in the vibrant UK tech landscape, employees benefit from a dynamic work environment that encourages creativity and teamwork.
StudySmarter Expert Advice🤫
We think this is how you could land Data Analysis
✨Get Involved in Data Science Meetups
Tap into local data science meetups or workshops to connect with fellow enthusiasts and professionals. These events are goldmines for networking, and sometimes even lead directly to job openings at companies like Zensar Technologies!
✨Show Off Your Projects
Start building a public portfolio showcasing your data science projects on platforms like GitHub or personal websites. Highlight unique analyses or models you've developed. This not only demonstrates your skills but also gets your name out there for roles like Data Analysis at Zensar Technologies.
✨Leverage Professional Networks
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 Zensar Technologies.
✨Apply Directly through Our Website
When you find a suitable opening like Data Analysis at Zensar Technologies, make sure to apply directly through our website. It gives you an edge and shows you're keen to join our team. Plus, who doesn’t love a direct application? It’s easier than navigating through job boards!
We think you need these skills to ace Data Analysis
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 Zensar Technologies, 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 Zensar Technologies. 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 Zensar Technologies
✨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 Zensar Technologies!
✨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.
