Senior Data Engineer

As a Senior Data Engineer , you will play a leading role in the design, development, implementation and operation of modern cloud-based data platforms for clients. The role is primarily focused on data engineering, DataOps and MLOps delivery across Snowflake, dbt, AWS and Azure, supporting the development of scalable, secure and production-ready data solutions. In addition to hands‑on engineering responsibilities, you will provide technical leadership across client engagements by contributing to solution design, establishing engineering standards, and supporting the successful delivery of complex data platform initiatives. You will work closely with clients, Solution Architects, Data Architects, Business Analysts, Data Scientists and Data Engineers to translate business requirements into robust technical solutions. An aspect of the role involves software engineering activities, including the design and development of reusable code libraries, automation frameworks, deployment pipelines and cloud-native services that improve platform reliability, operational efficiency and delivery consistency. As a senior member of the engineering team, you will mentor Data Engineers, contribute to engineering best practices, support technical decision‑making and help drive continuous improvement across data platform, DataOps and MLOps capabilities. This role is based in Auckland, New Zealand and requires you to work Monday to Friday, from 8:30am to 5:00pm, a total of 40 hours per week. Salary Band is $131,000 – $145,000 per annum. Key Responsibilities: Lead the design, development and implementation of scalable cloud-based data platforms and data products using Snowflake, AWS and Azure. Design and optimise enterprise‑grade ELT/ETL frameworks using dbt, orchestration platforms and modern data engineering practices. Develop and maintain data warehouse, data lake and lakehouse solutions that support analytics, reporting, artificial intelligence and machine learning workloads. Define and implement data modelling, ingestion and transformation standards to improve scalability, maintainability and performance across data platforms. Develop and maintain data ingestion, transformation and orchestration processes for structured, semi‑structured and unstructured data sources. Lead the implementation of DataOps practices including CI/CD, automated testing, deployment automation, observability and operational monitoring. Design and implement data quality frameworks, validation processes and operational controls to support trusted and reliable data assets. Develop reusable software components, frameworks, templates and automation tools that improve engineering productivity and delivery consistency. Write, review, test and optimise code using Python, SQL and related technologies in accordance with software engineering best practices. Leverage AI‑assisted development tools including GitHub Copilot and Snowflake Cortex Code CLI to accelerate development activities, improve code quality and enhance engineering productivity. Implement and maintain Infrastructure as Code (IaC) solutions using technologies such as Terraform and Azure Bicep. Ensure data security, governance, privacy and compliance requirements are integrated into data platform design and implementation. Work directly with clients and stakeholders to gather requirements, provide technical recommendations and translate business needs into scalable data platform solutions. Contribute to technical design workshops, engineering estimation activities and solution planning for client engagements. Collaborate with Solution Architects, Data Architects, Data Scientists, Analysts and Engineering teams to deliver successful client outcomes. Provide technical leadership and mentoring to Data Engineers through code reviews, design reviews, knowledge sharing and coaching activities. Evaluate emerging technologies, cloud platform capabilities and AI‑enabled engineering practices, recommending improvements that enhance performance, reliability and operational efficiency. Key Requirements: Bachelor's degree in Computer Science, Engineering, or Information Technology, Information Systems or a closely related discipline. Minimum 5 years' professional experience in Data Engineering or, DataOps Engineering. Demonstrated experience designing, implementing and operating production‑grade cloud data platforms within enterprise environments. Proven experience leading the delivery of data engineering initiatives and contributing to technical solution design. Experience working within consulting, professional services or enterprise delivery environments. Strong experience with Snowflake and dbt for data warehousing, data transformation, analytics and platform operations. Experience developing, testing, documenting and deploying data transformation frameworks using dbt. Experience with GitHub Copilot and Snowflake Cortex Code CLI. Strong experience working across AWS and/or Azure cloud environments. Advanced SQL skills and experience working with structured and semi‑structured data. Experience implementing DataOps practices including CI/CD, automation, monitoring and operational support. Experience supporting MLOps workflows including feature pipelines and model‑ready datasets. Strong software development experience using Python or similar programming languages. Experience with Infrastructure as Code tools such as Terraform or Azure Bicep. Demonstrated ability to mentor and support engineers through technical leadership, code reviews and knowledge sharing. Strong consulting, stakeholder engagement, analytical and problem‑solving skills. Ability to work independently while contributing effectively within multidisciplinary project teams. AWS, Azure and/or Snowflake certifications are highly desirable. Must be based in Auckland, New Zealand. Availability to travel to customer sites as required. Here’s a Taste of What’s on Offer at dataengine: Opportunity to solve real‑world business problems. Collaborative and supportive work environment. Competitive salary. Be at the forefront of data science innovation in a dynamic startup environment. Work on a variety of challenging and impactful projects across different industries. Opportunity to learn and grow your skillset with the latest technologies. Continuous learning and development opportunities. Weekly fresh fruit, snacks, monthly industry led lunches and active staff activities. Be part of a company that is shaping the future of data‑driven solutions. About dataengine: dataengine, a New Zealand-based leader in data solutions, empowers businesses to unlock the hidden value within their data and achieve true transformation. We connect people, processes, and technology for optimised efficiency and sustainable impact. Founded in 2018, we've grown rapidly thanks to our exceptional team and commitment to delivering practical, impactful results. We believe in building the foundation right, starting with strategic planning and robust architecture. #J-18808-Ljbffr