Data Engineer at The Warehouse Group

Kaipātiki, Auckland, New Zealand -

Full Time

Start Date

Immediate

Expiry Date

18 Oct, 26

Salary

0.0

Posted On

20 Jul, 26

Experience

2 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

SQL, Python, Snowflake, dbt, Azure, ETL/ELT, Data Modelling, CI/CD, Git, Airflow, Data Governance, Data Warehousing, Dimensional Modelling, DevOps, Data Pipeline Engineering, Business Intelligence

Industry

Retail

Description

Company Description The Warehouse Group (TWG) has become a Kiwi household name, and we proudly recognise the role that we play in communities throughout New Zealand. We are the largest general merchandise retailer in NZ across The Warehouse, Warehouse Stationery & Noel Leeming. We are at an exciting point in our journey where our focus is on becoming brand centric, aiming to deliver an unparalleled experience for our customers. Agility and collaboration are cornerstones of our work culture, empowering us to adapt swiftly and work seamlessly together. By being brand-led and retail-focused, we are intentional about placing the right people in the right roles, allowing us to perform work that truly makes a difference. Job Description The Role Sitting within our Tech function, and reporting into the Tech Team Lead: Data Engineering, you will play a crucial role in designing, implementing, and maintaining our data infrastructure to support business intelligence and analytics initiatives. You'll be designing, building, and maintaining scalable data platforms, pipelines, and data infrastructure that enable analytics, AI, and business reporting. The role works closely with data analysts, AI engineers, business stakeholders, and platform teams to ensure data is accurate, trusted, secure, and readily available for decision-making. Based on TWG's current data architecture, this role typically focuses on Snowflake, dbt, Python, SQL, Azure, and modern cloud data engineering practices. Four Key areas of your role: Data Pipeline Engineering Design, develop, and maintain scalable ETL/ELT pipelines. Ingest, transform, and integrate data from multiple enterprise systems. Automate data processing and orchestration workflows. Monitor pipeline performance and resolve data-related issues Data Platform & Modelling Develop and maintain data models, data warehouses, and semantic data structures. Design conceptual, logical, and physical data models. Support data architecture patterns such as Kimball, Medallion, and enterprise warehousing approaches. Ensure platforms are performant, scalable, and cost-effective. Data Quality, Governance & Security Implement data quality controls and monitoring. Support privacy, security, and governance requirements. Ensure trusted and compliant data assets. Contribute to metadata, documentation, and engineering standards Stakeholder Engagement Work with business stakeholders to understand requirements. Partner with BI, AI, Data Science, Data Stewardship, and Automation teams. Translate business requirements into technical solutions. Support self-service analytics and AI initiatives. Qualifications About You First and foremost, you have a passion for setting up data solutions. Equally important, is your ability to uncover and understand business requirements and translate them into technical solutions. We will rely on your thirst to learn, coupled with your strong collaboration skills – for us attitude and a growth mindset is everything. We envisage you will bring the following to the role: Minimum of 3 years' experience in data engineering or a similar role or Senior Data Engineer: 5+ years data engineering experience with dbt expertise. Bachelor's degree in Computer Science, Information Systems, Data Engineering, Software Engineering, or a related discipline Technical competencies: Advanced SQL development. Python programming. Snowflake platform expertise. dbt development and data transformation. Experience with Azure cloud services. ETL/ELT design and implementation. Data warehousing and dimensional modelling. CI/CD and DevOps practices. Source control using Git/Azure DevOps. Airflow or similar orchestration tools. Expertise in designing and implementing data warehousing solutions Hands-on experience with cloud platforms Strong understanding of data modelling, database design, and data governance principles Experience with version control systems Knowledge of data security best practices and regulatory requirements Familiarity with data visualisation tools and machine learning concepts Excellent problem-solving skills, attention to detail, and ability to work effectively in a team environment Experience with technologies such as dbt, Teradata, Wherescape, Kafka, and microservices is advantageous Passion for modern data technologies and continuous improvement. Additional Information We are intentional about finding the right people, allowing us to perform work as a team that truly makes a difference for the business and our customers. In return, you’ll get exposure to exciting technology, meaningful projects, and the opportunity to learn from passionate and experienced people in the Data & AI space. Apply now and make an impact with one of Aotearoa’s most trusted retailers. Be part of our journey to make sustainable living easy and affordable for everyone. Contract Type: Permanent

Responsibilities

Design, implement, and maintain scalable data infrastructure, pipelines, and platforms to support AI and business reporting. Collaborate with stakeholders and technical teams to ensure data is accurate, secure, and available for decision-making.