Data Engineer

• Design, build, and operate reliable data ingestion pipelines across APIs, events, databases, files, and third-party platforms
• Build services, integrations, and reusable tooling using Python, TypeScript, and the patterns established by Vista’s data engineering team
• Use AI-first engineering practices to orchestrate the design, development, testing, documentation, and operation of production systems
• Create secure and observable interfaces that allow copilots, agents, automation, and decision-support workflows to consume trusted data
• Help build unified views of Vista’s customer and business operations
• Implement monitoring, logging, alerting, auditability, failure handling, and data quality controls across services and pipelines
• Apply strong security, privacy, access control, data ownership, and responsible AI practices throughout the solution lifecycle
• Manage multiple workstreams in parallel while remaining self-directed and accountable for delivery
• Help improve Vista’s data engineering architecture, development practices, and reusable platform patterns

Software Engineer – Data Engineering

• **What you’ll do**
• - Work with stakeholders to understand business outcomes, operational pain points, workflows, and decisions that could be improved through better access to data and AI
• - Translate business needs into clear requirements, data points, metrics, source systems, and prioritised engineering work
• - Design and deliver data ingestion pipelines, services, integrations, and tooling using the patterns established by Vista’s data engineering team
• - Use AI-first engineering practices to orchestrate the design, development, testing, documentation, and operation of production systems
• - Build practical AI-enabled solutions, including copilots, agents, automation, and decision-support workflows.
• - Break ambiguous problems into clear, achievable increments that deliver measurable value
• - Run multiple streams of work in parallel while remaining self-directed and accountable for outcomes
• - Ensure data quality, security, access, auditability, observability, and responsible AI practices are built into each solution
• - Work closely with data engineering, product, support, security, and business teams to ensure solutions are useful, reusable, and scalable
• - Provide day-to-day people leadership for the Data Engineering team, including regular one-to-ones, coaching, feedback, career development, wellbeing support, and performance management
• - Build a healthy, inclusive, and accountable team environment that supports high autonomy and effective collaboration
• - Provide leadership visibility into team health, capacity, capability, and emerging people risks

Senior Software Engineer – Team Lead, Data Engineering

• Support the ongoing support, maintenance, and enhancement of systems that support storage, processing, and retrieval of the Bank’s data products
• Supporting the delivery of two brand new data collections
• Implementing changes, resolving defects, applying upgrades, and adding new data to meet evolving business needs
• Work closely with colleagues across the Operations Group to evolve the data engineering practice using appropriate frameworks and tools and consistently applying these to daily work

• Build and maintain robust dataset and evaluation infrastructure, including ground-truth quality controls
• Diagnose and fix measurement-path issues between offline evals and production accuracy
• Iterate on and scale existing labeling frameworks and knowledge capture systems
• Own prompt optimization across its full lifecycle, from candidate selection through production rollout and post-launch validation
• Automate eval pipelines and build the tooling to run this at scale across multiple AI products
• Create reusable internal tooling for error analysis, audits, and experimentation, and prioritize work using likely impact

Senior Software Engineer, Data Science – AI Accuracy

• Design, build and optimise data pipelines across lakehouse and warehouse environments.
• Develop high-quality data transformations for analytics, reporting and AI/ML workloads.
• Work with Databricks, Delta Live Tables, Lakeflow, Git and CI/CD pipelines.
• Implement testing, monitoring and data quality practices.
• Lead technical discussions and translate business requirements into engineering outcomes.
• Collaborate with architects and delivery teams on solution design and delivery planning.
• Mentor junior and intermediate engineers and support knowledge sharing across the team.
• Contribute to continuous improvement of frameworks, templates and delivery standards.

Senior Data Engineer – Databricks

• Completing the migration of the final legacy MySQL datasets into a modern Databricks environment.
• Building and maintaining pipelines across Databricks, Fivetran (including reverse ETL), DBT, and Airflow.
• Handling full data engineering responsibilities — ingestion, pipeline reliability, performance optimization, and infrastructure maintenance.
• Supporting the clean retirement of legacy systems without impacting downstream consumers.
• Working closely with a senior internal team and owning work independently.
• Identifying risks early and maintaining clear documentation.

• Build and maintain data infrastructure
• Contribute to the development and maintenance of data pipelines
• Help ensure data is reliable, accurate, and available
• Write clean, maintainable code
• Help investigate data issues and troubleshoot pipeline failures
• Support efforts to improve data quality, performance, and reliability
• Partner with Product Managers, Software Engineers, Data Analysts and other team members

Data Engineering Intern

• Perform DBA-like operational tasks that include fulfilling database-related service requests, monitoring and improving our Cloud-based SQL environments, and resolving incidents with the help of software engineers.
• Perform T-SQL development tasks such as creating new or optimising existing T-SQL code (queries, stored procedures, functions), and reviewing and approving T-SQL code written by software engineers.
• Participate in initiatives such as regular database performance improvement, process improvement, automation, and data security review.
• Contribute to other projects that include tasks such as creating data pipelines, building a data model, and creating reports.
• Mentor and coach other engineers at any level.
• Adhere to SQL and data engineering best practices.
• Collaborate with various stakeholders to bring better tooling and automation opportunities related to database infrastructure.
• Participate in an on-call roster (roughly one week for 4 weeks).

Data Engineer jobs in New Zealand

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Software Engineer – Data Engineering

Senior Software Engineer – Team Lead, Data Engineering

Data Engineer

Senior Software Engineer, Data Science – AI Accuracy

Senior Data Engineer – Databricks

Data Engineer

Data Engineering Intern

Senior Data Engineer – Database Operations