We’re supporting a large-scale data programme that requires an experienced Data Engineer to help transform complex, unstructured information into clean, reliable datasets suitable for analysis and reporting.

The project involves working with sizeable JSON files and other mixed-format sources, standardising them, and preparing them for downstream use across several internal systems. You’ll be responsible for shaping the structure, improving data quality, and ensuring outputs can be easily consumed by non-technical teams.

What You’ll Work On

Converting varied and unstructured data (including JSON) into well-defined relational formats.

Designing data models that ensure consistency and interoperability across tools.

Preparing datasets for use in spreadsheets, reporting environments, and CRM systems.

Resolving data quality issues: type mismatches, missing values, integrity checks, and formatting problems.

Building repeatable processes and validation steps to support accurate, sustainable reporting.

Partnering with operational and business teams to understand requirements and ensure outputs are fit for purpose.

Skills & Experience Needed

Strong SQL abilities and experience designing relational schemas.

Hands-on Python skills (preferably pandas) for data wrangling and transformation.

Solid understanding of data modelling principles and best practices.

Good working knowledge of Excel and awareness of CRM/enterprise data structures.

Experience with business intelligence/reporting tools (Power BI, Tableau, etc.) is beneficial.

Able to interpret complex datasets, identify patterns/issues, and communicate findings clearly to non-technical users.

Nice to Have

Background in sensitive or regulated data environments.

Understanding of data protection considerations.

Exposure to ETL or data pipeline development.