Data Engineer

4 weeks ago

Auckland, New Zealand Zuru Full time

Join us as a Mid-Senior Data Engineer and lead the charge in building scalable, resilient, and cost-efficient data infrastructure with a global teamAbout ZURUZURU is on a mission to disrupt industries, challenge the status quo, and catalyse change through radical innovation and advances in automation. Founded in 2003 by EY Entrepreneur of the Year and World Entrepreneur Hall of Fame brothers Nick and Mat Mowbray, ZURU has quickly grown to a team of over 5,000 direct and indirect members across more than 30 international locations.One of the largest toy companies in the world, our globally recognised and award-winning brands include Bunch O Balloons, Mini Brands, XSHOT, Rainbocorns, and Smashers. Our global FMCG brands include MONDAY Haircare, Rascals, NOOD, BONKERS, and Gumi Yum Surprise.Your RoleWe are seeking a skilled and experienced Mid-Senior Data Engineer to lead and shape our data infrastructure, ensuring efficiency, cost optimisation, resilience, and accuracy across all our systems. This role is perfect for someone who is passionate about building scalable and timely data solutions while adhering to best practices, such as AWS Well-Architected Framework. You will lead an international team of engineers, working closely to build APIs, design resilient data pipelines, and optimize our cloud data infrastructure.Key ResponsibilitiesLeadership: Lead and mentor an international team of data engineers, fostering collaboration, innovation, and continuous improvement.Data Pipeline Management: Design, build, and maintain scalable and resilient data pipelines using AWS and Databricks, ensuring the seamless integration of data from multiple sources.API Development: Develop and manage APIs that facilitate seamless data access and interaction with our data platforms.Cloud Infrastructure: Optimize the AWS infrastructure for efficiency, cost-effectiveness, and resilience while ensuring compliance with AWS Well-Architected patterns.Cost Optimisation: Continuously monitor, optimize, and manage cloud costs, ensuring high efficiency and minimal waste in data storage, processing, and retrieval.Data Quality: Ensure the accuracy and timeliness of data across all pipelines, implementing monitoring solutions to detect and correct anomalies in real time.Resilience & Recovery: Implement robust disaster recovery and high-availability strategies to ensure data reliability and reduce downtime.Collaboration: Work cross-functionally with data scientists, analysts, and business stakeholders to understand data needs, architect and distil complex problems into achievable tasks, and ensure efficient delivery. Manage projects from conception to execution, providing technical leadership and oversight to ensure that deliverables are met on time and aligned with business objectives.Automation: Identify opportunities for automation within the data engineering processes, minimising manual intervention and boosting efficiency.Documentation & Best Practices: Maintain thorough documentation of systems and processes and ensure the team follows well-architected and industry-leading data practices.Qualifications3+ years of experience in data engineering, with a focus on cloud technologies and large-scale data systems.Proven expertise in AWS services (e.g., S3, Redshift, Lambda, Glue) and (Optionally) Databricks.Strong proficiency in building, optimising, and maintaining ETL/ELT pipelines.Experience working with APIs for data ingestion and integration.Familiarity with the AWS Well-Architected Framework and best practices for building secure, reliable, and efficient systems.Strong knowledge of SQL and experience with Python distributed data processing.Experience with cost management and performance tuning in AWS.Strong communication and leadership skills, with experience leading and mentoring international teams.Proficiency with programming languages like Python/PySpark.A problem-solving mindset and the ability to work in a fast-paced, ever-evolving environment.Bonus SkillsExperience with CI/CD pipelines, containerisation, and infrastructure-as-code (e.g., Terraform/Cloud Formation).
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