Back to SearchLead Data Engineer
Remote in Australia
Data Software Engineering& 7 others
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We are seeking a Lead Data Engineer to own end-to-end data modeling and pipeline delivery as a major enterprise data lake is re-architected. You will work hands-on with Databricks and dbt, partner closely with US-based stakeholders and collaborate with an India-based engineering team. You thrive with high autonomy, clear documentation and strong ownership.
Responsibilities
- Own dimensional data models from requirements through deployment using Kimball-aligned patterns
- Design, build and maintain pipelines in Databricks and dbt to support a modernised data lake
- Translate business requirements into scalable datasets, anticipating future reporting and analytics needs
- Lead end-to-end delivery including development, unit testing, UAT support and release coordination
- Produce clear technical documentation in Confluence and maintain decision records and data definitions
- Partner with US-based stakeholders to align outcomes, scope and delivery expectations
- Collaborate with an India-based engineering team to coordinate build, reviews and handovers
- Support basic dashboarding and validation to confirm data meets business expectations
Requirements
- Dimensional modeling capability including star schema, fact and dimension design and aggregate awareness
- Hands on experience with python programming
- Databricks experience for data engineering development and operational support dbt (data build tool) experience including modular modelling, testing and deployment practices
- SQL proficiency for analytics-grade transformations and performance-aware querying
- Traditional ETL and data warehousing foundation adapted to modern cloud data stacks
- End-to-end delivery ownership across requirements, build, testing, UAT and deployment
- Clear communication and strong documentation habits for non-technical stakeholder engagement
- Self-directed working style with comfort operating under light-touch leadership
Nice to have
- Experience re-architecting enterprise data lakes or data warehouses in multi-phase programs
- Familiarity with release planning across distributed teams and time zones
- Exposure to basic BI development or semantic layer design to support reporting consumption