About The Role

We are seeking an experienced Senior Data Engineer to design, build and maintain scalable data solutions that support business intelligence, analytics, AI and strategic decision-making.

The role will be responsible for developing robust data pipelines and architectures, ensuring data is reliable, secure and accessible across the organisation. You will work closely with Data, Engineering, Product and Business teams to translate complex requirements into high-quality data solutions.

Key Responsibilities

Data Engineering & Architecture

• Design and develop scalable, reliable data architectures and engineering solutions.

• Build and maintain robust data pipelines for batch and real-time processing.

• Develop and optimise data ingestion, transformation and integration processes.

• Design and maintain data warehouses, data lakes and modern data platforms.

• Ensure data solutions are scalable, maintainable and fit for purpose.

Data Pipelines & Integration

• Build ETL/ELT pipelines to integrate data from multiple internal and external sources.

• Develop APIs and data integrations where required.

• Implement automated data processing and orchestration workflows.

• Monitor pipeline performance and troubleshoot data quality or processing issues.

• Optimise existing pipelines for performance, reliability and cost.

Data Quality & Governance

• Establish and maintain data quality, validation and monitoring processes.

• Implement appropriate data governance, security and access controls.

• Ensure data is accurate, consistent, traceable and appropriately managed.

• Work with Security and Compliance teams to ensure data solutions meet regulatory and organisational requirements.

• Support data privacy and retention requirements.

Cloud & Modern Data Platforms

• Design and implement cloud-based data solutions, particularly within Microsoft Azure.

• Work with technologies such as Azure Data Factory, Azure Synapse, Databricks, Microsoft Fabric or equivalent platforms.

• Support cloud migration and data modernisation initiatives.

• Apply best practices around scalability, security and cloud cost optimisation.

Analytics & AI Enablement

• Prepare and structure data to support reporting, analytics, machine learning and AI applications.

• Work with Data Scientists, Analysts and AI teams to provide reliable and accessible datasets.

• Develop data models and structures that support business intelligence and advanced analytics.

• Support the development of data foundations for AI and automation initiatives.

Technical Leadership

• Provide technical guidance and mentoring to other data engineers.

• Review data architecture, pipelines and technical solutions.

• Establish engineering standards and best practices.

• Identify opportunities to improve data platforms, processes and performance.

• Communicate complex technical concepts clearly to technical and non-technical stakeholders.

Required Skills & Experience

• 5+ years' experience in data engineering or a closely related technical role.

• Strong experience designing and developing enterprise-scale data solutions.

• Strong SQL skills and experience with Python or another data engineering language.

• Experience building ETL/ELT pipelines and data integration solutions.

• Strong understanding of data warehousing, data lakes and modern data architectures.

• Experience working with cloud-based data platforms, particularly Microsoft Azure.

• Experience with data modelling, data quality and governance.

• Strong understanding of database technologies and data processing.

• Experience working with large and complex datasets.

• Strong problem-solving and analytical skills.

• Excellent communication and stakeholder management skills.

Preferred Experience

• Microsoft Azure certifications or relevant cloud experience.

• Experience with Azure Data Factory, Azure Synapse, Databricks or Microsoft Fabric.

• Experience with Python, PySpark or Spark.

• Experience with real-time data processing and event-driven architectures.

• Knowledge of CI/CD, DevOps and Infrastructure as Code.

• Experience supporting AI, machine learning or advanced analytics projects.

• Experience within B2B technology, FinTech or other regulated environments.

• Understanding of data security, privacy and regulatory requirements.