Deloitte NZ

Databricks Data Engineer (Data & AI)

Deloitte NZ Wellington, Wellington, New Zealand

Business Consulting and Services · 10,001+ employees

17 h ago
data-engineer Senior (5-10 yrs) Full-time New Zealand
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About the role

Design, develop, and maintain scalable data and AI solutions using Databricks and modern Lakehouse architectures. Collaborate with cross-functional teams to build robust data pipelines and implement AI-assisted engineering practices to accelerate delivery.

What they look for

Databricks Data Engineering Lakehouse Architecture Python ETL/ELT Data Modelling CI/CD DevOps Azure AWS Terraform Generative AI Machine Learning SQL Data Governance Cloud Computing

Requirements

Requires strong hands-on experience with Databricks, data modelling, and distributed processing concepts. Candidates should have proficiency in cloud data services, CI/CD practices, and a strong analytical mindset for troubleshooting complex data environments.

Benefits

Flexible work arrangements Subsidised professional qualifications Paid professional memberships Subsidised health insurance Income protection insurance 22 days annual leave Social events Social sports teams Monthly firm drinks Wellness and well-being focus Community focused volunteer days

Full description

Company Description

Join us. But be you. At Deloitte, you’ll do more than just join something, you’ll add something.  You’ve found a place that values your curiosity, passion, and desire to work alongside brilliant people on the things that really matter. There really is only one question: What impact do YOU want to make?

We are looking for an experienced and motivated Databricks Data Engineer to join our growing AI & Data Engineering team.

This role is ideal for someone who is passionate about modern data engineering, enjoys solving complex business and technical challenges, and is keen to embrace AI-assisted engineering practices to deliver solutions faster and smarter.

Job Description

As a Databricks Data Engineer in Deloitte, you will design, build, and maintain scalable data and AI solutions using Databricks. You will have the opportunity to work across the full engineering lifecycle, from data ingestion and transformation through to modelling, orchestration, deployment, optimisation, and production support as well as leverage the wider capabilities that Databricks offers with Lakebase, Unity Catalog, Databricks Apps etc.

Your AI-enabled engineering mindset will help you leverage Genie Code, GitHub Copilot, and other AI development tools to accelerate delivery while maintaining strong engineering, security, and quality standards.

Key Responsibilities

  • Design, develop, and maintain scalable data and AI solutions on Databricks.
  • Build robust data ingestion, ELT/ETL, and data processing pipelines using Databricks.
  • Develop high-quality and reusable transformations through Lakeflow Declarative Pipelines.
  • Design and implement Lakehouse architectures.
  • Build dimensional, curated, and feature-ready data models to support reporting, analytics, machine learning, and Generative AI use cases.
  • Develop and maintain integrations between Databricks and cloud platforms, APIs, databases, files, streaming platforms, and enterprise applications.
  • Implement automated CI/CD pipelines and modern DevOps practices for Databricks deployments.
  • Develop and orchestrate workloads using Lakeflow Jobs, Azure Data Factory, Airflow, or similar technologies.
  • Implement appropriate security, governance, data quality, lineage, and monitoring controls.
  • Optimise Databricks workloads for performance, scalability, reliability, and cost efficiency.
  • Troubleshoot complex platform, pipeline issues across development and production environments.
  • Collaborate with architects, analysts, data scientists, ML engineers, and business stakeholders to translate requirements into practical technical solutions.
  • Contribute to engineering standards, reusable frameworks, technical documentation, and continuous improvement initiatives.
  • Proactively leverage Genie Code, GitHub Copilot, and other AI-powered development tools across solution design, coding, testing, troubleshooting, code review, and documentation.
  • Identify opportunities to use AI and automation to reduce repetitive engineering effort and accelerate the development lifecycle.

Qualifications

Required Experience

  • Strong hands-on experience with Databricks.
  • Experience designing and building modern Lakehouse architectures.
  • Strong understanding of data engineering, data modelling, data warehousing, and distributed processing concepts.
  • Experience building batch and/or streaming data pipelines.
  • Experience with orchestration technologies such as Lakeflow Jobs, Azure Data Factory, Airflow, or similar tools.
  • Understanding of cloud data services across Azure and/or AWS.
  • Experience with Git, CI/CD, and modern software engineering practices.
  • Experience using Python in data engineering solutions are advantageous.
  • Familiarity with infrastructure-as-code technologies such as Terraform or similar.
  • Strong analytical, troubleshooting, and problem-solving skills.
  • Excellent communication and stakeholder engagement skills.

Preferred Experience

  • Experience with Generative AI, Machine Learning, or MLOps on Databricks.
  • Experience with Databricks Declarative Automation Bundles
  • Databricks certifications such as:• Databricks Certified Data Engineer Associate
  • Databricks Certified Data Engineer Professional

AI-Assisted Engineering

  • An AI-enabled engineering mindset, proactively using tools such as Genie Code, Claude, GitHub Copilot, and other AI capabilities to accelerate development, automate repetitive tasks, improve code quality, and deliver solutions more efficiently.
  • Good judgement when using AI-generated outputs, with a strong focus on security, maintainability, accuracy, and engineering quality.

What Success Looks Like

You are someone who can take ownership of a data engineering problem from design through to production.

You care about building solutions that are not only functional, but also scalable, maintainable, secure, automated, and well engineered.

You are comfortable working across the broader cloud, data, analytics, and AI ecosystem and are always looking for better ways of working through reusable patterns, automation, and effective use of AI-assisted development tools.

Most importantly, you combine strong technical capability with a delivery-focused and continuous-improvement mindset.

Why Join Us?

You will have the opportunity to:

  • Work on exciting project for some of New Zealand’s best companies.
  • Work on modern, enterprise-scale Databricks Lakehouse platforms.
  • Deliver solutions across Data Engineering, Analytics, AI, Machine Learning, and Generative AI.
  • Solve complex, real-world data engineering challenges.
  • Develop experience with modern engineering and AI-assisted development practices.
  • Work alongside experienced data engineers, architects, platform specialists, and technology leaders.
  • Contribute to reusable frameworks, accelerators, and engineering practices that improve how we deliver modern data platforms.

If you are passionate about Databricks, modern data engineering, AI, and building Lakehouse solutions at scale, we would love to hear from you.

Additional Information

So, who is Deloitte in Aotearoa?  

We are driven to create an impact that matters at every opportunity. Supported by a strong leadership team and member firms from over 150 countries across the globe, Deloitte in Aotearoa is in the business of solving complex problems. Over our 175-year history, we have built a reputation for impactful delivery across all areas of our business. 

Deloitte in Aotearoa recognises the uniqueness of our country identified in our founding document, Te Tiriti o Waitangi.  We uphold our responsibility(s) to the founding document and acknowledge Māori as the Tangata Whenua/Indigenous people.  

Our shared values are at the heart of everything we do. Living these values, including ‘Manaaki/taking care of each other’ and ‘Hāpai tangata/fostering inclusion’, is essential to ensuring everyone feels included at work and able to reach their full potential. Our values drive our desire to create positive outcomes for our clients, communities, and people. 

Deloitte Talent Experience  

We hold a simple belief – that our people’s hard work should be recognised and rewarded beyond their remuneration. We have reimagined what ‘work’ looks like and how we can empower all our people to create a work experience that is distinct to their needs. Founded on concepts of trust, balance, wellbeing, and the importance of personal connection, this is the Deloitte experience.  

We offer:  

  •  Flexible work arrangements – work in a way that suits you, us and our clients best  
  •  Subsidised professional qualifications and paid professional memberships  
  •  Subsidised health insurance  
  •  Income protection insurance  
  •  22 days annual leave  
  •  Social events, social sports teams, and monthly firm drinks  
  •  A focus on wellness and well-being   
  •  Community focused volunteer days  
  •  A focus on the environment and sustainability  

We believe the strongest teams are made up of diverse individuals and we are proud to be an equal opportunities employer. We recognise that women and individuals from under-represented backgrounds may hesitate to apply if they don't meet all criteria. If you're passionate about this role and believe you have the skills, we encourage you to apply, even if your experience, ideal working hours or qualifications aren't a perfect match.

Please be aware of phishing attempts posing as Deloitte recruiters. Official communications from Deloitte New Zealand will come from “@deloitte.co.nz,” “@smartrecruiters.com,” or our video interview platform Deloitte<[email protected]>. If you receive a suspicious email, verify its authenticity by contacting us at [email protected].

  • Office address: Deloitte Auckland, Level 20, 1 Queen Street, Auckland
  • Department: Consulting | Technology | AI & Data (incl. GenAI)

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