• Permanent role
• Auckland office location with hybrid working
• Work collaboratively with other data professionals to deliver best in class solutions
  We strive to create better experiences together for a better tomorrow for our customers and team, bringing the best of Woolworths Group and Quantium together to make data driven decisions. By partnering with Quantium, a world-class data science and advanced analytics business we’re excited about the future as we unlock the power of data to reimagine retail.
  Through this partnership, we’ve created a new business called wiq who will harness the best of Woolworths Group and Quantium to reimagine retail by solving the most complex problems using data and analytics. As a team, we leverage Agile ways of working to help our team develop their skills while also making sure our team is focusing on solving the most complex problems for both our customers and team.

REQUIRED SKILLS & EXPERIENCE:

• 8+ years of experience as a data engineer delivering data warehouse solutions.
• Strong hands-on ETL experience using tools such as DBT, BigQuery, Airflow.
• Proven experience designing and implementing complex, high-throughput distributed batch and real-time solutions leveraging GCP services (BigQuery, DataProc, Dataflow, Dataprep, Composer, Pub/Sub, Apache Beam, Kubernetes), as well as Python and Java.
• Deep understanding of data structures, data modeling, and system design principles focused on reliable, high-throughput batch and streaming solutions.
• Influence business strategies through the provision of technical alternatives.
• Keeps well abreast of industry trends and directions to ensure solutions will provide business with forward compatible, scalable and flexible solutions.
• Strong software engineering background and passion for high quality design and code (use of git, CI/CD, technical spikes, collaboration with solution architects)
• Google Cloud Professional Data Engineer and Cloud Architect certifications would be valuable
  This is a fast paced innovative role and one where you will be empowered to make a significant contribution to making Kiwis’ lives a little better everyday! If you’d like to make a key contribution to the growth of our business, apply today!

As a Senior Group Data Engineer, you will provide technical leadership and delivery accountability for WDP enhancements specific to the WWNZbusiness. You will act as the primary liaison and data SME for all NZ data assets and requirements, bridging between wiqNZ and Group IM to ensure the delivery of cost-effective, high-quality, and innovative data solutions aligned with best practices. Your role involves close collaboration with Group IM data architects and engineers, as well as working day-to-day with the NZ data engineering chapter and contributing to their agile sprints
You will manipulate and provision data as well as build scalable, reliable data pipelines that can service both batch and realtime use cases. You will also contribute to the development of data engineering patterns and processes, applying your problem-solving skills to root cause analysis, process improvements, and build and cost optimisation.

Responsibilities will include, but are not limited to:

• Collaborate with Woolworths Group Data Architects and Platform teams to define a suitable logical target state architecture. One that supports upstream data platform initiatives like ML Ops, Advanced Analytics, and Data Governance. It should also facilitate fast data manipulation and provisioning, as well as the development of scalable and dependable data models and pipelines for both batch and real-time applications.
• Collaborate with Product Managers to input to WDP enhancements and pinpoint implementation challenges and develop risk mitigation strategies.
• Demonstrated adherence and understanding of data platform Group standards (data structures, data provisioning, privacy & cyber risk protection)
• Code quality and peer review processes - understand and lead the review analytics data provisioning against use cases (pulling in WWNZ QA support as needed) ensuring follow specifications and quality standards
• Development of data preparation for advanced data modeling, data mining and production quality data science models
• Collection, cleansing, merging, management and integration of datafrom various source systems across the business ensuring conformity and avoiding duplication
• Contribute to analytics problem solving and insight generation. Applies problem-solving skills to root cause analysis, process improvements, and build and cost optimisation.
• Drive the shift towards better data engineering practices by identifying, designing, and implementing internal process improvements: automating manual processes, optimizing data