Data Business Analyst (Warehouse & Modelling) - 6 month contract - London/hybrid - Outside IR35

Lead Data Business Analyst (Data Warehouse & Data Modelling)

Our London based client are 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 clients 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.

Skills & Experience

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.

If this role is of interest then please share your profile and I will contact you at my earliest possible convenience.

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.