At MMS, our purpose is clear: To make a difference to people's lives. Guided by this commitment, we offer tailored solutions to clients and customers across our businesses in Australia and New Zealand. Our vision is to be your trusted partner, simplifying complexities and turning challenges into opportunities. Our diverse services – from salary packaging and fleet management to disability support – aim to enhance your financial wellbeing and empower your aspirations. Through our subsidiaries, we offer a breadth of services and expertise designed to responsibly deliver superior long-term value to our clients and customers, which include Federal and State governments and some of the largest public and private sector, health and charitable organisations. Reporting to the Data Engineering Practice Lead, as a Data Engineer you will be working with a team to deliver high-quality mission-critical data platforms for our stakeholders. You will use your expertise in Azure Data Factory, dbt, SQL Server and Snowflake to design, build, and maintain scalable and reliable data pipelines, data models, and data warehouses. You will be a key part of the full delivery lifecycle, including planning, testing, deployment, and support. This role will sit within our Architecture and Common Platforms team helping to ensure that the data provided via key platforms is available when and where it is needed, as well as working with other business stakeholders and IT teams as required. Key Responsibilities Design, develop, test, and deploy data pipelines using Azure Data Factory, dbt, and Snowflake. Ensure data quality, reliability, and scalability across our data platforms. Collaborate with data analysts, data scientists, and business stakeholders to understand data requirements and deliver solutions. Provide technical guidance and support to other data engineers and data practitioners. Report to the Data Engineering Practice Lead and contribute to the data engineering best practices and standards. You will bring: Bachelor's degree in computer science, Engineering, or related field or equivalent work experience At least 5 years of experience in data engineering, preferably in a consulting or professional services environment. Strong knowledge and experience in Azure Data Factory, dbt, and Snowflake. Proficient in SQL Experience in data modelling, data warehousing, and data quality. Experience in leading and managing data engineering teams and projects. Excellent communication, presentation, and problem-solving skills. Ability to work independently and collaboratively in a fast-paced and dynamic environment. What we can offer you: Our strong people-first culture Flexible/hybrid working to enhance your work/life balance Novated lease benefits and discounts 12 weeks Paid Parental leave and access to our Parents Portal Exempt Employee Share Plan Paid Income Protection Insurance under MMSG default Super plan Access to a broad range of learning and development programs Career break and volunteering leave Access to Employee Assistance Program and annual Flu vaccination Lifestyle Rewards program As an employer who embraces Diversity, Equity & Inclusion, we hold a collective commitment to foster an environment where all differences are valued and respected. We encourage Aboriginal and Torres Strait Islander people, individuals from all backgrounds, including those caring for and living with disability to apply. Please note all successful candidates will be required to undergo background checks.
