My client a leading payment aggregator and provider of secure payment solutions, is looking for a Senior Data
Engineer to join their growing team. This role focuses on designing, building, and maintaining scalable data
pipelines and architectures that enable advanced analytics and support data-driven decision-making across the organisation. 
The ideal candidate is a proactive, self-directed individual with strong technical expertise, excellent problem-solving ability, and the ability to work both independently and collaboratively in a fast-paced environment.

Responsibilities include:

• Design, build, and maintain scalable ETL/ELT data pipelines using Python, SQL and cloud-native tools.
• Integrate and harmonise data from multiple sources, including transactional systems, accounting platforms, and CRM tools.
• Develop and manage data warehouse structures across environments such as SQL Server and
• PostgreSQL.
• Ensure data quality, reliability, and performance through monitoring, validation, and optimisation processes.
• Collaborate with data architects, analysts, and business stakeholders to deliver fit-for-purpose data products.
• Implement and maintain data governance, documentation, and best practices.
• Research and implement new data technologies and improvements to existing systems.
• Support deployment processes, version control, and system integration.
• Contribute to data modelling, architecture decisions, and technical strategy.
• Build prototypes and proof of concepts where required.
• Assist with disaster recovery planning and system resilience.
• All other tasks related to the role.

Minimum requirements:

• Degree in a relevant field (Information Systems, Computer Science, Engineering, Mathematics or
  similar role). 
• 8+ years’ experience in a data engineering or similar role. 
• Strong proficiency in SQL and Python. 
• Proven experience building and maintaining data pipelines and data architectures.
• Strong communication skills in English with the ability to work effectively with both technical teams and non-technical business stakeholders.
• Own reliable transport.

Advantageous:

• Experience with data orchestration tools (e.g. Airflow).
• Understanding of data warehousing and dimensional modelling.
• Exposure to systems such as SQL Server, PostgreSQL, Sage One, Xero, Business Central,
• HubSpot, or Microsoft Dataverse.
• Experience with Agile / Scrum delivery practices.
• Experience in fintech, payments, or financial services.
• Experience documenting data architectures, data 

models, or data dictionaries.