Data Engineering Practice Lead
1 week ago
The McMillan Shakespeare Group (MMS) is a trusted provider of salary packaging, novated leasing, disability plan management, support co-ordination, asset management, and related financial products and services. Since its establishment in 1988, MMS has been at the forefront of Australia's salary packaging industry, known for innovation and exceptional service.
Through its subsidiaries, MMS caters to Federal and State governments, as well as large public and private sector, health, and charitable organizations, offering a wide range of services and expertise aimed at delivering long-term value responsibly.
Data Engineering Practice Lead RoleIn the role of Data Engineering Practice Lead at MMS, you will lead a team of data engineers to develop high-quality, mission-critical data platforms for stakeholders. Your responsibilities will involve designing, building, and maintaining scalable and reliable data pipelines, models, and warehouses using Azure Data Factory, dbt, and Snowflake. You will oversee the entire delivery lifecycle, from planning and testing to deployment and support, collaborating closely with other leads, managers, and stakeholders to ensure alignment with business requirements and best practices.
Key Responsibilities- Lead the data engineering practice and mentor the team.
- Design and develop data solutions using Azure Data Factory, dbt, and Snowflake.
- Implement data quality, governance, and security measures.
- Optimize performance, scalability, and reliability of data solutions.
- Manage the full delivery lifecycle, including planning, testing, deployment, and support.
- Maintain Asset Lifecycle Management practices.
- Collaborate with other leads, managers, and stakeholders for alignment and integration of data solutions.
- Stay updated with the latest trends and technologies in data engineering.
- Reports to Head of Architecture and Common Platforms
- Works with Head of Data to ensure data availability
- Collaborates with IT practice leads for technical best practices
- Engages with other business stakeholders and IT leaders as required
You will bring:
- Bachelor’s degree in computer science, Engineering, or related field or equivalent work experience
- Minimum 5 years of data engineering experience, preferably in consulting or professional services
- Strong knowledge and experience in Azure Data Factory, dbt, and Snowflake
- Proficiency in SQL, data modeling, 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 environment
- People-first culture
- Flexible/hybrid working options
- Novated lease benefits and discounts
- 12 weeks Paid Parental leave and Parents Portal access
- Employee Share Plan and Income Protection Insurance
- Learning and development programs
- Career break and volunteering leave
- Employee Assistance Program, annual Flu vaccination, and Lifestyle Rewards
As an equal opportunity employer, MMS values and respects diversity. We encourage applications from all backgrounds, including individuals with disabilities. Background checks will be conducted for all successful candidates.
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