PBT Group is seeking an experienced and delivery-focused Data Engineer to join our consulting team on a contract basis. The successful candidate will have strong data engineering and data warehousing experience within a Microsoft-centric environment and will be responsible for designing, developing, and maintaining scalable data solutions that support business intelligence, analytics, and reporting requirements.

The ideal candidate will have a solid foundation in the traditional Microsoft BI stack (SSIS, SSAS, SSRS/Power BI), strong SQL development skills, and proven experience in enterprise data warehousing environments. Exposure to cloud-based data platforms and emerging AI-enabled data solutions will be highly advantageous.

Key Responsibilities

• Design, develop, and maintain robust ETL/ELT processes and data integration solutions.

• Build and support enterprise data warehouse solutions, including dimensional modelling and data marts.

• Analyse business requirements and translate them into technical data solutions.

• Develop, optimise, and troubleshoot SQL queries, stored procedures, and database objects.

• Ensure data quality, integrity, governance, and performance across data platforms.

• Develop and maintain reporting and analytics solutions using SSRS and/or Power BI.

• Collaborate with business stakeholders, analysts, architects, and project teams to deliver data solutions.

• Support data migration, integration, and modernisation initiatives.

• Participate in data architecture discussions and contribute to continuous improvement initiatives.

• Produce and maintain technical documentation and operational procedures.

Required Skills and Experience

Technical Skills

• Strong SQL Server development experience.

• Advanced T-SQL programming and database optimisation skills.

• Solid experience with:

  • SQL Server Integration Services (SSIS)

  • SQL Server Analysis Services (SSAS)

  • SQL Server Reporting Services (SSRS)

  • Power BI

• Strong understanding of Data Warehousing principles and methodologies.

• Experience in:

  • Star and Snowflake schema design

  • Dimensional modelling

  • ETL development

  • Data quality and reconciliation processes

• Experience integrating data from multiple source systems.

• Knowledge of performance tuning and optimisation practices.

Data Warehouse & Analytics Experience

• Proven experience designing and supporting enterprise data warehouse solutions.

• Strong understanding of data modelling concepts and best practices.

• Experience supporting reporting, analytics, and business intelligence environments.

• Ability to work with large and complex datasets.

Advantageous Skills

• Experience with cloud data platforms such as:

  • Microsoft Azure

  • Azure Data Factory

  • Azure SQL

  • Azure Synapse Analytics

  • Microsoft Fabric

• Exposure to Databricks or modern data platform technologies.

• Experience with DevOps practices and CI/CD pipelines.

• Knowledge of data governance and data management frameworks.

• Exposure to AI, Machine Learning, Generative AI, or AI-enabled analytics solutions.

• Experience working in consulting or client-facing environments.

Qualifications

• Relevant tertiary qualification in Computer Science, Information Systems, Engineering, Mathematics, Statistics, or a related field.

• Microsoft certifications will be advantageous.

Personal Attributes

• Strong analytical and problem-solving abilities.

• Excellent communication and stakeholder engagement skills.

• Self-managed and delivery-oriented.

• Ability to work independently and within cross-functional teams.

• Strong attention to detail and commitment to quality.

• Adaptable and able to work across multiple client environments.

Why Join PBT Group?

PBT Group is a leading provider of data, analytics, and technology solutions. We partner with clients across a variety of industries to unlock value from their data and help them make informed business decisions. This role offers the opportunity to work on diverse projects, collaborate with experienced professionals, and contribute to innovative data initiatives.