Senior Data Engineer
Hands-on senior data engineer at an IT consultancy, designing, building and supporting production Databricks lakehouse pipelines (Delta Live Tables, Unity Catalog, Asset Bundles, PySpark) with CI/CD, while working directly with clients and mentoring juniors. Must hold a valid NZ work visa; Wellington preferred, Auckland or Christchurch possible.
- Compensation
- Not disclosed
- Location
- Wellington
- Work setup
- Onsite
- Seniority
- Senior
- Employment
- Full time
- Experience
- Not specified
- Category
- Data engineering
- Posted
Skills
Must have
- Valid New Zealand work visa
- Strong commercial, hands-on Databricks engineering experience
- Production experience with Delta Live Tables and Unity Catalog
- Experience deploying solutions using Databricks Asset Bundles
- Practical experience with Delta Lake, lakehouse architecture, and Medallion design principles
- Strong PySpark or Python data engineering capability
- Experience using Git and delivering through CI/CD pipelines across multiple environments
- Proven experience designing, deploying, and supporting data pipelines in production
- Able to explain differences between Delta and Parquet, and lakehouse vs traditional data warehouse architectures
- Experience working in a consulting, professional services, or client-facing delivery environment
- Clear communication skills and confidence in workshops, technical discussions, and delivery updates
- Ability to work independently, manage ambiguity, and deliver within architectural guardrails
Full description
Tō kamupene hou | Your new company
Join a leading IT consultancy delivering production-grade solutions across modern data platforms. This is an opportunity for an experienced Senior Data Engineer who enjoys remaining hands-on while working directly with clients, architects, and delivery teams.
You will design, build, deploy, and support scalable Databricks data pipelines within lakehouse environments. The role requires strong engineering discipline, independent delivery capability, and confidence engaging with both technical and business stakeholders
Tō tūranga hou | Your new role
You will be responsible for:
- Designing and delivering production data pipelines using Databricks
- Building solutions with Delta Live Tables, Databricks Asset Bundles, workflows, jobs, and notebooks
- Working with Delta Lake and Medallion architecture across Bronze, Silver, and Gold layers
- Developing scalable data transformations using PySpark or Python
- Implementing structured CI/CD, source control, and multi-environment deployment practices
- Taking ownership of pipelines from design and development through to production support
- Troubleshooting production issues and improving reliability, performance, and data quality
- Working directly with clients to clarify requirements, explain technical decisions, and communicate risks and trade-offs
- Contributing to peer reviews, knowledge sharing, and the development of junior team members
Ngā uara me ngā pūkenga e angitu ai koe | What you'll need to succeed
To be successful, you will need:
- Strong commercial, hands-on Databricks engineering experience
- Production experience with Delta Live Tables and Unity Catalog
- Experience deploying solutions using Databricks Asset Bundles
- Practical experience with Delta Lake, lakehouse architecture, and Medallion design principles
- Strong PySpark or Python data engineering capability
- Experience using Git and delivering through CI/CD pipelines across multiple environments
- Proven experience designing, deploying, and supporting data pipelines in production
- The ability to explain the differences between Delta and Parquet, and between lakehouse and traditional data warehouse architectures
- Experience working in a consulting, professional services, or similarly client-facing delivery environment
- Clear communication skills and confidence contributing to workshops, technical discussions, and delivery updates
- The ability to work independently, manage ambiguity, and deliver within established architectural guardrails
Location: Wellington (ideal preference), Auckland/ Christchurch