Data Engineer - MDM Data Quality

• AWS
• Python
• Snowflake

Data Engineer - MDM, Data Matching & Data Quality
Contract
Hybrid

We have a contract opportunity for an experienced Data Engineer (AWS, Python, Snowflake) to play a key role in building data matching, cleansing and quality capabilities within a Master Data Management (MDM) environment.
This is a hands-on engineering role for someone who enjoys solving complex data problems and working with large, often imperfect datasets. You'll help develop the rules and processes that identify, match, standardise and cleanse records to create trusted, consistent master data.
A key focus will be supporting the design and implementation of deterministic and fuzzy matching rules, helping identify when different records represent the same customer, organisation, product or other business entity.
Role

• Build scalable data pipelines and data engineering solutions using Python, AWS and Snowflake.
• Design and implement deterministic and fuzzy matching rules.
• Develop data cleansing, standardisation, validation and enrichment processes.
• Work on entity resolution, record linkage and duplicate detection.
• Analyse matching results and refine rules, thresholds and matching logic.
• Translate business requirements into robust, testable data matching solutions.
• Investigate complex data quality issues and help improve the accuracy and consistency of master data.
• Work closely with data architects, MDM specialists, engineers and business stakeholders.
• Help establish trusted and explainable golden/master records.

Skills & Experience

• Strong commercial experience as a Data Engineer or similar role.
• Excellent Python and SQL skills.
• Strong experience with AWS and Snowflake.
• Experience working with MDM, data quality or data cleansing.
• Understanding of data matching, entity resolution, record linkage or duplicate detection.
• Experience developing rule-based data solutions and working with complex datasets.
• A strong analytical mindset and an ability to turn messy data problems into practical, scalable solutions.

Experience with fuzzy matching, similarity algorithms, probabilistic matching, matching thresholds or golden records would be highly desirable.