Senior Data and Analytics Engineer

SG Fleet; Sydney; On-site; AUD 150,000 - 210,000; Full time

Benefits offered by this job

Wellness days

Parental leave

Learning budget

Job summary

SG Fleet is seeking a Senior Data and Analytics Engineer in Sydney to lead design and delivery of scalable data and analytics solutions. The role shapes data architecture, engineering standards, and governance while collaborating with stakeholders to maximize business value.

You will drive end-to-end data pipelines, establish best practices, and mentor teams in a fast-paced Agile environment. The position anchors data as a strategic enterprise asset benefiting operations and customers.

Qualifications

• Bachelor’s degree in computer science, engineering, mathematics, statistics, or related field.
• Certifications in data and analytics tools focusing on Microsoft and Databricks.

Responsibilities

• Lead translation of business requirements into scalable data solutions.
• Design data models, pipelines, and visualisations across modern technologies.
• Establish best practices in data engineering, including architecture, security, governance.

Skills

SQL (T-SQL)

Databricks

PySpark

Azure data stack

Data modelling

Stakeholder engagement

Agile delivery

Education

Bachelor’s degree in CS/Engineering/Math/Stats

Tools

Azure Data Factory

Azure Databricks

Delta Lake

Power BI

Apache Kafka

Confluent

Azure Synapse

Azure Event Hubs

Job description

The Senior Data and Analytics Engineer leads the design and delivery of scalable, end-to-end data and analytics solutions that drive strategic business outcomes, enhance customer value, and enable operational excellence. Acting as a senior technical authority within Solution Delivery, the role shapes data architecture, engineering standards, and best practices while ensuring solutions are secure, governed, and future ready. Through strong stakeholder collaboration and technical leadership, the role also uplifts organisational capability and champions the effective use of data as a critical enterprise asset.

Job Requirements

• Bachelor’s degree in computer science, engineering, mathematics, statistics, or a related field
• Relevant and up to date industry certifications in data and analytics tools and technologies with a focus on Microsoft and Databricks
• Extensive experience in data engineering and analytics, delivering end-to-end solutions in complex environments
• Strong proficiency in SQL (T-SQL), Databricks, PySpark, and the Microsoft data stack including SQL Server, SSRS, and Power BI
• Proven experience designing and implementing modern data architectures, including Lambda and Kappa patterns
• Hands-on expertise in building and optimising batch and real-time data pipelines, including streaming solutions using technologies such as Apache Kafka, Azure Event Hubs, Confluent, and Apache Flink
• Extensive experience with Azure data and analytics services, including Azure Data Factory, Azure Databricks, Delta Lake, and Azure Synapse Analytics
• Experience working in Agile delivery environments, contributing to cross-functional teams and iterative solution development
• Strong capability in data modelling (dimensional and semantic) and delivering scalable, high-performing data models and visualisation solutions
• Experience working with large, complex datasets, applying strong analytical thinking and problem-solving skills to deliver business insights
• Excellent stakeholder engagement, communication, and presentation skills, with the ability to translate technical concepts for non-technical audiences

Job Responsibilities

• Lead the translation of business requirements into scalable data and analytics solutions that deliver measurable outcomes
• Design and oversee the development of data models, pipelines, and visualisations across a range of modern technologies
• Establish and uphold best practice in data engineering, including architecture, performance, security, and governance
• Collaborate with business and technical stakeholders to drive alignment, adoption, and value from data initiatives
• Provide technical leadership and guidance on data architecture, design patterns, and engineering standards across delivery teams
• Support the deployment, adoption, and ongoing optimisation of data and analytics solutions to ensure they remain fit for purpose
• Mentor and coach team members, fostering capability uplift, continuous improvement, and a strong data engineering culture
• Recharge and relax with up to 4 days of wellness days every year
• We offer industry leading 20 weeks paid parental leave
• Monetary service milestone awards
• Career progression opportunities
• Education support towards learning and development, includes a learning budget per year, free access to LinkedIn Learning and more
• Two paid volunteer days each year
• Health and wellbeing support including a subsidy and an Employee assistance Program