PBT Group is seeking an experienced Data Engineer to join a high-performing data team responsible for building and maintaining modern, scalable data platforms that enable enterprise-wide analytics and business intelligence.
This role is ideal for an end-to-end Data Engineer with strong Data Warehousing experience and a passion for designing robust data solutions. You will work across the full data engineering lifecycle—from ingesting and transforming data through to designing scalable data models and delivering trusted datasets that support business-critical reporting, analytics, and operational decision-making.
While the environment leverages modern cloud technologies, we're primarily looking for candidates with excellent core data engineering skills. Experience with Azure or AWS cloud platforms is highly valued, with exposure to Google Cloud Platform considered advantageous.
Key Responsibilities
Data Engineering
Design, develop, and maintain scalable data pipelines supporting enterprise analytics and reporting.
Build robust ETL/ELT processes to ingest, cleanse, transform, and deliver high-quality data.
Develop reliable, reusable, and maintainable data integration solutions.
Optimise data processing performance, scalability, and reliability.
Data Warehousing
Design and develop enterprise Data Warehouse solutions.
Implement dimensional models using industry best practices (Kimball/Inmon methodologies).
Develop fact and dimension models to support reporting and analytical workloads.
Ensure data quality, governance, and consistency across enterprise datasets.
Cloud Data Platforms
Develop cloud-native data solutions using modern cloud technologies.
Work with structured and semi-structured data across multiple data sources.
Support migration and modernisation initiatives into cloud-based data platforms.
Contribute to performance optimisation and cloud cost efficiency.
Collaboration
Work closely with Business Analysts, BI Developers, Data Scientists, Architects, and business stakeholders to understand data requirements.
Translate business requirements into scalable technical solutions.
Participate in Agile ceremonies, sprint planning, estimation, and solution design sessions.
Engineering Excellence
Develop high-quality, production-ready code using software engineering best practices.
Perform code reviews and promote continuous improvement.
Maintain technical documentation and data lineage.
Support CI/CD processes and deployment automation where applicable.
Monitor and troubleshoot data pipelines and production environments.
Minimum Requirements
Qualifications
Degree or Diploma in Computer Science, Information Systems, Engineering, Mathematics, or a related discipline.
Relevant cloud certifications will be advantageous.
Experience
Minimum 5 years' experience in a Data Engineering role.
Strong end-to-end Data Engineering experience.
Proven experience designing and developing enterprise Data Warehouse solutions.
Extensive experience developing ETL/ELT pipelines.
Strong SQL development and database optimisation skills.
Experience working with cloud-based data platforms such as Azure or AWS.
Experience integrating data from multiple enterprise source systems.
Strong understanding of data modelling and dimensional modelling principles.
Experience working within Agile delivery teams.
Strong problem-solving and analytical skills.
Technical Skills
Experience with many of the following technologies is highly desirable:
SQL
Python
Google Cloud Platform (GCP), utilizing tools like BigQuery, Cloud Data Integration
Azure Data Factory, Synapse Analytics, or AWS Glue
Azure Data Lake or Amazon S3
Databricks (advantageous)
Spark or PySpark (advantageous)
Data Warehousing
ETL/ELT development
Data Modelling
Dimensional Modelling (Kimball/Inmon)
Git
CI/CD pipelines
Power BI or other modern BI platforms (advantageous)
Key Competencies
Strong analytical and problem-solving skills
Excellent attention to detail
Passion for building scalable, high-quality data solutions
Strong communication and stakeholder engagement skills
Collaborative team player
Results-oriented with a continuous improvement mindset
Ability to work effectively in a fast-paced Agile environment