At a Glance
- Tasks: Design and optimise data pipelines, mentor engineers, and deliver innovative solutions.
- Company: Fast-growing tech consultancy specialising in data, analytics, AI, and cloud solutions.
- Benefits: Work with modern tech, interesting clients, and a supportive culture.
- Other info: Join a collaborative environment that values curiosity and ownership.
- Why this job: Shape the future of data delivery while staying hands-on and making an impact.
- Qualifications: 6+ years in Data Engineering, strong skills in Python, PySpark, and Databricks.
The predicted salary is between 81000 - 99000 $ per year.
About the Company
Our client is a fast-growing technology consultancy specialising in data, analytics, AI and cloud solutions. They help organisations modernise their technology environments and get more value from their data, working with leading platforms including Databricks, Microsoft Azure and Microsoft Fabric. What sets them apart is the combination of deep technical capability and genuine consulting expertise. As their Australian Data Practice expands, they’re looking for an experienced Senior-Principal Data Engineer/Architect to join the team.
About the Role
This is a senior, hands-on consulting role for someone who pairs strong Data Engineering/Architecture fundamentals with the confidence to work directly with clients. You’ll stay close to the technology, designing solutions, building pipelines and writing code, while also mentoring other engineers as the practice grows.
What You’ll Be Doing:
- Designing, building and optimising data pipelines across data lakes, lakehouses and warehouses
- Delivering production-grade solutions on Databricks and cloud data technologies
- Developing transformations using Python, PySpark and SQL
- Working with Databricks notebooks, workflows and Lakeflow Declarative Pipelines (formerly Delta Live Tables)
- Applying Lakehouse and Medallion architecture patterns
- Designing robust data models for analytics, reporting and downstream consumption
- Applying DevOps practices including Git, CI/CD and automated deployment
- Implementing testing, data validation, monitoring and performance optimisation
- Working directly with clients to translate business needs into pragmatic technical solutions
- Collaborating with architects on solution design, estimation and delivery planning
- Leading technical discussions with both technical and non-technical stakeholders
- Conducting peer reviews and mentoring junior and intermediate engineers
- Contributing to reusable frameworks, templates and engineering standards
What You’ll Bring:
- 6+ years’ experience in Data Engineering or Data Platforms
- Strong hands-on experience delivering production solutions on Databricks
- Strong in Python, PySpark, SQL, ETL/ELT pipelines and complex transformations
- Solid understanding of Medallion and Lakehouse architecture works
- Strong data modelling knowledge (dimensional, Star and Snowflake)
- Cloud data platform experience, ideally Microsoft Azure
- DevOps and software engineering practices (version control, CI/CD, automated deployment)
- Experience with testing and data quality in production environments
- Excellent communication skills and confidence working with senior stakeholders
- Ability to work autonomously while collaborating across multidisciplinary teams
Advantageous: Databricks Certifications.
The Person They’re Looking For:
Someone who enjoys working with customers, asks the right questions and looks beyond the technical requirement to the problem behind it. You’ll take ownership, make pragmatic decisions, explain them clearly, and enjoy helping other engineers grow. Most importantly, you want to stay hands-on while developing as a consultant.
Why Join?
- Help shape how the Data Practice delivers, rather than inheriting set processes
- Work with modern technology, interesting clients and experienced people across Data, Integration, Cloud and AI
- A culture where curiosity is encouraged, ideas are heard and people are trusted to take ownership
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