Sr Data Engineer – Databricks & Power BI
Senior data engineer building and maintaining scalable data pipelines in Databricks, transforming data with SQL, Python, and PySpark, and developing/optimising Power BI reports and data models. Open to candidates in Wellington or Christchurch, NZ, with valid NZ working rights.
- Compensation
- Not disclosed
- Location
- Wellington, New Zealand
- Work setup
- Not specified
- Seniority
- Senior
- Employment
- Not specified
- Experience
- Not specified
- Category
- Data engineering
- Posted
Skills
Must have
- Hands-on experience with Databricks and data engineering solutions
- Strong SQL skills, including query optimisation and complex transformations
- Experience with Python and PySpark for data processing
- Understanding of ETL/ELT pipelines, data warehousing, and data modelling
- Practical Power BI experience, including report development and data visualisation
- Knowledge of Power Query, DAX, and Power BI data modelling
- Experience with data quality checks, troubleshooting, and pipeline optimisation
- Strong analytical, problem-solving, and communication skills
- Valid New Zealand working rights
Nice to have
- Based in Wellington or Christchurch
- Experience with Azure Data Factory, Azure Data Lake Storage, or Microsoft Fabric
- Knowledge of Delta Lake, Spark, and lakehouse architecture
- Experience with CI/CD, Git, and automated data pipeline deployment
- Familiarity with dimensional modelling and star schemas
- Understanding of data governance, access controls, and cloud security
- Experience with Power BI Service, workspace management, and deployment pipelines
Full description
We are seeking a skilled Data Engineer with hands-on experience in Databricks, data pipeline development, SQL, and Power BI. The successful candidate will be responsible for building and maintaining reliable data pipelines, transforming data for analytics and reporting, and supporting business intelligence solutions.
The ideal candidate will combine strong data engineering fundamentals with practical Power BI knowledge to deliver high-quality, accessible, and analytics-ready data.
Key Responsibilities
- Design, develop, and maintain scalable data pipelines using Databricks.
- Build data ingestion, transformation, and integration workflows.
- Develop and optimise SQL queries for data processing and reporting.
- Work with Python and PySpark to transform and process large datasets.
- Implement ETL/ELT processes and ensure data quality, accuracy, and consistency.
- Develop and maintain data models and curated datasets for analytics and reporting.
- Work with Power BI to create, enhance, and support reports and dashboards.
- Optimise Power BI data models, DAX calculations, and report performance.
- Collaborate with Data Scientists, Business Analysts, and stakeholders to understand data requirements.
- Implement data validation, monitoring, documentation, and performance optimisation.
- Follow data governance, security, and best practices for data management.
Required Skills and Experience
- Hands-on experience with Databricks and data engineering solutions.
- Strong SQL skills, including query optimisation and complex transformations.
- Experience with Python and PySpark for data processing.
- Understanding of ETL/ELT pipelines, data warehousing, and data modelling.
- Practical Power BI experience, including report development and data visualisation.
- Knowledge of Power Query, DAX, and Power BI data modelling.
- Experience with data quality checks, troubleshooting, and pipeline optimisation.
- Strong analytical, problem-solving, and communication skills.
Desirable Skills
- Experience with Azure Data Factory, Azure Data Lake Storage, or Microsoft Fabric.
- Knowledge of Delta Lake, Spark, and lakehouse architecture.
- Experience with CI/CD, Git, and automated data pipeline deployment.
- Familiarity with dimensional modelling and star schemas.