Role & seniority: Test Engineer – Data & Analytics; experienced data-focused QA professional (mid-senior level implied)

Stack/tools: Data quality testing, ETL concepts, SQL, Python scripting; PySpark; CI/CD for data pipelines; (Nice-to-have) Databricks, Delta Lake, Lakeflow; data observability tooling

Top 3 responsibilities

Design and execute data quality tests to ensure processed data meets requirements
Validate accuracy/completeness of transformed datasets across ETL pipelines; identify anomalies
Develop automated validation scripts, contribute to CI/CD testing, and document plans/findings

Must-have skills

Hands-on data quality testing and QA in data-centric roles
Strong SQL and relational database querying
Python scripting for automation/validation; understanding of ETL and pipeline logic
Functional testing mindset with edge-case focus; collaboration across technical teams

Nice-to-haves

Experience with Databricks, Delta Lake, or Lakeflow
Exposure to data-centric CI/CD workflows and observability tooling

Location & work type

Auckland-based, hybrid (at least 3 days in-office)
6-month initial contract with potential extension; competitive rates

Full Description

Test Engineer - Data & AnalyticsThe Company

A leading New Zealand organisation is seeking a skilled Test Engineer to join a high-performing technology team. This role offers the opportunity to work at the forefront of data quality, contributing to modern analytics pipelines and ensuring the integrity of data that powers strategic decision-making.

The Role

Are you an experienced Test Engineer with a passion for data integrity and automation? This role involves taking ownership of data validation tasks, collaborating with data engineers, and ensuring robust testing processes within an agile environment. Your ability to validate complex transformations and develop automated frameworks will be essential in delivering high-quality, actionable insights.

Key Responsibilities

Design and execute data quality tests to ensure processed data meets functional and business requirements. Validate the accuracy and completeness of transformed datasets across ETL pipelines. Identify and escalate data anomalies, inconsistencies, and pipeline quality issues. Develop and run test cases for data pipelines, including business logic validation. Implement automated validation scripts using Python/PySpark within reusable frameworks. Contribute to Cl/CD testing processes to enable continuous delivery of reliable data products. Document test plans and findings, collaborating with technical teams to resolve issues.

Key Requirements

Technical Skills

Hands-on experience in data quality testing, QA, or related data-centric roles. Solid understanding of ETL concepts, data transformations, and pipeline logic. Proficiency in SQL and relational database principles for querying and validating datasets. Exposure to Python scripting for building automation and validation frameworks. Strong grasp of functional testing principles and a methodical, edge-case-driven approach.

Soft Skills

Proactive problem-solver with a mindset geared toward improving test reliability. Excellent collaboration skills, with the ability to work effectively across technical teams. Commitment to continuous learning and adapting to evolving data technologies.

Nice To Have

Experience with Databricks, Delta Lake, or Lakeflow platforms. Exposure to data-centric Cl/CD workflows and observability tooling.

On Offer

6-month initial contract with a high potential for extension. Auckland-based | Hybrid working (at least 3 days in-office) | Contract. Competitive market rates and the chance to work on modern data stacks.

If you are passionate about data quality and automation, apply now to be part of a forward-thinking team! Follow the link to apply or contact Amaan at 0220607986. Alternatively, you can email amaan.kazmi@randstaddigital.co.nz.