Motion Recruitment
Customer Analytics Engineer
- Compensation
- Not disclosed
- Location
- Victoria, Australia
- Work setup
- Not specified
- Seniority
- Not specified
- Employment
- Contract
- Experience
- Not specified
- Category
- Data analytics
- Posted
Skills
Must have
- Cloud Data Warehousing: Extensive experience with Snowflake architecture and performance optimization.
- Analytics Engineering: Proven track record of deploying version‑controlled models using dbt.
- Relational Database Expertise: Advanced command of SQL for complex data manipulation and extraction.
- Data Governance Tools: Practical experience using Elation (or an equivalent enterprise data catalog) to manage data governance workflows.
- Domain Knowledge: Previous experience within customer analytics, retail, or large‑scale consumer services is highly desirable.
- Strong analytical and problem‑solving capabilities.
- A meticulous approach to data documentation and quality assurance.
- Exceptional communication skills, with the ability to navigate a large, complex corporate structure.
Full description
We are currently representing a well known Australian organization in their search for a Customer Analytics Engineer for a 12-month fixed-term engagement. This role is a critical component of the enterprise data team, responsible for developing high-quality, governed data models that underpin the organization's customer-centric strategies.
The successful candidate will be responsible for the end-to-end transformation of complex customer datasets. You will ensure that data architectures are scalable, performant, and aligned with enterprise data governance frameworks.
Responsibilities
- Data Transformation & Modeling: Design, develop, and maintain robust data transformation pipelines using dbt within a Snowflake environment.
- SQL Development: Execute sophisticated SQL development to support advanced analytics, segmentation, and customer lifecycle modeling.
- Data Governance & Metadata Management: Utilize Elation to maintain data lineage, enhance data discoverability, and ensure adherence to internal compliance and quality standards.
- Stakeholder Integration: Act as a technical liaison between data engineering and business units to ensure data outputs are fit-for-purpose and technically sound.
Requirements
- Cloud Data Warehousing: Extensive experience with Snowflake architecture and performance optimization.
- Analytics Engineering: Proven track record of deploying version‑controlled models using dbt.
- Relational Database Expertise: Advanced command of SQL for complex data manipulation and extraction.
- Data Governance Tools: Practical experience using Elation (or an equivalent enterprise data catalog) to manage data governance workflows.
- Domain Knowledge: Previous experience within customer analytics, retail, or large‑scale consumer services is highly desirable.
- Strong analytical and problem‑solving capabilities.
- A meticulous approach to data documentation and quality assurance.
- Exceptional communication skills, with the ability to navigate a large, complex corporate structure.