Senior Data Engineer
At Provoke, we're looking for an experienced Data Engineer who enjoys solving complex business problems through modern Microsoft data platforms.
You'll partner directly with customers across the globe to design, build and evolve scalable cloud-native data solutions using Microsoft Fabric and the broader Azure ecosystem. From modern Lakehouse architectures through to enterprise analytics platforms, you'll help organisations unlock the full value of their data while laying the foundations for advanced analytics and future AI capabilities.
This is a highly consultative role where you'll combine technical excellence with customer engagement, helping shape solutions design, guiding implementation, mentoring engineers and delivering outcomes that make a real impact.
This is a NZ-based Role.
About the Role
As a Senior Data Engineer, you'll play a leading role in designing and delivering modern data platforms for customers across a diverse range of industries.
You'll work in cross-functional delivery teams with customer stakeholders to build scalable, secure and well-governed data solutions. While Microsoft Fabric will be at the centre of your work, you'll also contribute to broader Azure data platforms and help customers prepare their data for analytics, reporting and emerging AI workloads.
This role will blend hands-on engineering, technical leadership, solution design and customer engagement.
What You'll Do
- Design and implement modern Microsoft Fabric data platforms from architecture through to production.
- Build scalable ingestion, transformation and orchestration pipelines that deliver trusted, high-quality data.
- Design Lakehouse, Warehouse and semantic data models that support enterprise reporting, analytics and decision making.
- Work directly with customers to understand business challenges, facilitate workshops and translate requirements into practical technical solutions.
- Provide technical leadership across delivery teams through architecture guidance, mentoring and engineering best practice.
- Champion modern engineering disciplines including source control, CI/CD, automation, testing and operational excellence.
- Collaborate with AI and Software Engineering teams to ensure data platforms are optimised for advanced analytics, machine learning and future AI workloads.
- Continuously improve delivery approaches, reusable assets and engineering standards across the practice.
What Success Looks Like
Success in this role isn't measured purely by the code you write. It's measured by the outcomes you help create.
You'll be successful when:
- Customers see you as a trusted technical advisor who can simplify complex challenges and deliver practical solutions.
- Data platforms are scalable, secure, governed and ready for production.
- Engineering teams benefit from your mentoring, technical leadership and collaborative approach.
- Data pipelines are automated, observable and built for long-term maintainability.
- Analytics and AI teams have reliable, well-modelled data that enables them to deliver valuable business insights faster.
What You'll Bring
Essential
- 4-6+ years' commercial experience delivering Data solutions.
- Proven experience designing and implementing Microsoft Fabric solutions within enterprise environments.
- Strong consulting skills, with experience working directly with customers to design and deliver technical solutions.
- Strong SQL and Python development skills.
- Experience designing modern cloud-based data platforms and enterprise data architectures.
- Excellent communication skills and the ability to explain technical concepts to both technical and business stakeholders.
- A collaborative mindset and a genuine passion for mentoring and sharing knowledge.
Technical Experience
We're looking for someone with strong experience across modern Microsoft data engineering, including many of the following capabilities:
- Modern Data Platforms - Designing and delivering Lakehouse, Warehouse and enterprise data solutions using Microsoft Fabric and the Azure data ecosystem, with a strong focus on scalability, governance and performance.
- Data Engineering & Integration - Building robust ingestion, transformation and orchestration pipelines using technologies such as Data Factory, Spark, PySpark and SQL to deliver trusted, production-ready data.
- Analytics & Modelling - Developing semantic models, dimensional models and curated data products that enable reporting, self-service analytics and business intelligence through Power BI and related technologies.
- Engineering Practices - Applying modern software engineering principles including Git, CI/CD, testing, automation, Infrastructure as Code and operational monitoring to deliver reliable, maintainable data platforms.
Nice to Have
While not essential, experience in any of the following would be highly regarded:
- Supporting data platforms that underpin AI, machine learning or natural language processing workloads.
- Exposure to Azure AI, Azure Machine Learning or Microsoft's AI ecosystem.
- Experience working alongside AI or Data Science teams to prepare and optimise data for intelligent applications.
- Databricks or other large-scale distributed data processing platforms.
- Microsoft Data, Fabric or AI certifications.