Data Warehouse, ETL & Data Modelling Specialist

About the Role

We are seeking an experienced Data Warehouse, ETL & Data Modelling Specialist to join our customer in London. In this SME-level role, you will be responsible for designing and maintaining robust, scalable data infrastructure, ensuring the quality and integrity of data across multiple pipelines, and providing expert input into data design and governance practices.

You will act as the key liaison between development teams and data storage solutions, ensuring data is segregated, controlled, and fit for purpose before it is reposited into the warehouse. This is a hands-on role involving deep technical work in ETL/ELT, data modelling (especially logical and conceptual), data validation, and quality assurance.

Key Responsibilities

ETL/ELT Design and Maintenance:

Design, implement, and optimize scalable ETL/ELT processes for structured and semi-structured data.
Monitor, troubleshoot, and improve existing pipelines for performance and reliability.

Data Quality & Source Validation:

Validate the integrity, lineage, and accuracy of incoming data from source systems.
Perform root cause analysis for data inconsistencies or quality issues.

Data Governance & Segregation:

Enforce best practices for data segregation, access control, and retention.
Define and manage metadata, data catalogs, and data classification processes.

Logical & Conceptual Data Modelling:

Develop logical and conceptual data models to support business requirements and reporting structures.
Work with BI developers, data analysts, and architects to translate models into physical schemas.

Collaboration & Cross-functional Liaison:

Partner with software developers to ensure data is clean, well-documented, and properly integrated.

Review developer code and practices before data is moved to production environments or repositories.

Code & Process Quality Assurance:

Perform peer code reviews to enforce standards and best practices in SQL

Act as a Subject Matter Expert for data warehousing, ETL, and modelling domains.

Required Skills & Experience

5+ years in data engineering, data warehousing, or similar roles.
Proven expertise in building and optimizing ETL pipelines using tools like SQL, Python, dbt, Informatica, Talend, or Apache NiFi.
Strong understanding of data warehousing concepts
Solid knowledge of logical and conceptual data modelling tools
Deep experience with relational databases
Familiarity with data governance, data quality frameworks, and access controls.
Strong communication skills for stakeholder engagement and cross-functional collaboration.

This is a hybrid working inside IR35 assignment