At a Glance
- Tasks: Lead data analysis and bridge business needs with technical teams for data warehousing.
- Company: Dynamic London-based client offering a hybrid work environment.
- Benefits: Competitive pay, flexible working, and opportunities for professional growth.
- Other info: Join a collaborative team focused on innovative data solutions.
- Why this job: Make a real impact by shaping data strategies that drive business decisions.
- Qualifications: Strong SQL skills and experience in data modelling and stakeholder management.
The predicted salary is between 50000 - 60000 £ per year.
Lead Data Business Analyst (Data Warehouse & Data Modelling)
Our London based client is currently looking for a Lead Data Business Analyst to act as the bridge between business stakeholders and technical data teams to define, document, and validate requirements for their enterprise data warehouse.
The Data Business Analyst will ensure that data models and warehouse structures accurately support business reporting, analytics, and strategic decision-making.
The successful Data BA will be required to visit the client’s central London office twice a week.
Key Responsibilities
- Elicit, analyse, and translate business requirements into detailed data requirements, including source‑to‑target mappings and logical, conceptual, and physical data models.
- Collaborate with data architects and data engineers to design and enhance dimensional data models, including fact and dimension tables using star and snowflake schemas.
- Produce and maintain data warehouse documentation, including entity relationship diagrams (ERDs), data dictionaries, business glossaries, and metadata.
- Analyse source systems to understand data structures, assess data quality, evaluate data lineage, and perform impact analysis for proposed changes.
- Validate data models, ETL/ELT pipelines, and warehouse structures against business requirements through testing and User Acceptance Testing (UAT).
- Partner with business stakeholders, BI developers, data engineers, project managers, and product owners to prioritise requirements and manage the delivery backlog.
- Identify opportunities to improve existing data models, resolve data inconsistencies, and recommend best practices for data governance and modelling.
- Support the definition of business rules, data standards, and reporting requirements to ensure consistent use of enterprise data.
Essential
- Strong understanding of data warehousing principles, including dimensional modelling, star and snowflake schemas, normalisation and denormalisation.
- Extensive experience in data modelling using industry‑standard modelling tools.
- Strong SQL skills for data analysis, profiling, reconciliation, and validation.
- Proven experience gathering and documenting business and data requirements.
- Experience producing source‑to‑target mappings, ERDs, and functional specifications.
- Excellent stakeholder management and communication skills with the ability to engage both business and technical audiences.
- Experience working in Agile environments, including user story creation, backlog refinement, sprint planning, and UAT support.
- Experience with cloud‑based data platforms, particularly Snowflake.
- Understanding of ETL/ELT frameworks and tools such as dbt and Apache Airflow.
- Knowledge of data governance, metadata management, and data lineage concepts.
- Experience supporting Business Intelligence and reporting solutions.
- Familiarity with modern analytics engineering practices.
- Preferred Background
- Demonstrated experience delivering enterprise data warehouse or analytics platform projects.
- Ability to communicate complex technical concepts in business‑friendly language and facilitate collaboration across cross‑functional teams.
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Data Business Analyst (Warehouse & Modelling) - 6 month contract - London/hybrid - Outside IR35 employer: LGBT Great
LGBT Great is an exceptional employer that prioritises inclusivity and employee well-being, making it a fantastic place for professionals in the insurance sector. With a strong focus on career development, employees benefit from comprehensive training opportunities and a supportive work culture that values collaboration and innovation. Located in a vibrant area, the company also offers competitive salaries, private medical insurance, and generous annual leave, ensuring a rewarding work-life balance.
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We think this is how you could land Data Business Analyst (Warehouse & Modelling) - 6 month contract - London/hybrid - Outside IR35
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We think you need these skills to ace Data Business Analyst (Warehouse & Modelling) - 6 month contract - London/hybrid - Outside IR35
Some tips for your application 🫡
Highlight Your Data Projects:When applying for a temporary data science role at LGBT Great, make sure to showcase any relevant projects you've worked on. Whether it's a personal project, an academic undertaking, or contributions to an open-source initiative, detailing these experiences can really set you apart and demonstrate your practical skills.
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Show Your Flexibility:Since this is a temporary role, it's important to convey your adaptability and willingness to learn. In your cover letter to LGBT Great, emphasise how quickly you can get up to speed with new tools or projects. Highlight any previous experiences where you've had to adjust to new environments or challenges.
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How to prepare for a job interview at LGBT Great
✨Showcase Your Analytical Skills
For a data science gig, it's crucial to demonstrate your analytical abilities. Be ready to discuss previous projects and the methodologies you used. Think about how you can quantify your impact—did your analysis improve efficiency or save costs? These are the stories that will stick with interviewers at LGBT Great.
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You might face technical questions on tools relevant to data science, like Python, R, or SQL. Prepare to solve a problem live—perhaps they'll ask you to write a simple query or code snippet. It’s cool to talk about them, but we need to show we can do it in practice, especially in a temporary role where quick results matter.
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✨Prepare a Portfolio of Your Work
Bring your portfolio to the table—showcase projects where you've leveraged data science techniques to solve problems. Whether it’s a GitHub repository or a set of case studies, having tangible examples of your work will help you stand out and show what you bring to the team at LGBT Great.
