
Data Engineer, Senior Consultant (SQL Developer)
- Auckland
- Permanent
- Full-time
- Gathering Requirements: The engineer leads collaboration with stakeholders to determine project requirements. They use their understanding of tradeoffs and project costs to define critical metrics or measures to assess the feasibility of delivery across multiple features and capabilities. They proactively seek clarification on non-functional requirements (NFR) and lead junior engineers in understanding requirements across solution delivery.
- Translating Business Requirements: The engineer translates functional and non-functional requirements into system designs and communicates how the components will interact across teams. They identify and interpret possible solutions and understand requirements and interdependencies in their solution space. The engineer also identifies potential impacts of risks in solutions and communicates these to the team lead.
- System Design and Architecture: The engineer designs and develops complex architectural solutions that are robust, scalable, and meet the project requirements. They plan and pilot new technology capabilities and features to enhance the system's functionality and user experience.
- Technical Expertise: The engineer should have advanced technical knowledge relevant to software development. They should be capable of analyzing patterns across bugs and implementing systemic solutions.
- Leadership: The engineer should demonstrate leadership in technical discussions and decisions, and be capable of leading junior engineers in understanding requirements.
- Communication: Effective communication with a wide range of stakeholders is crucial. The engineer should be able to translate business requirements into technical ones and vice versa.
- Problem-Solving: The engineer should have strong problem-solving skills, with the ability to identify potential impacts of risks in solutions and implement systemic solutions to address patterns across bugs.
- Proactiveness: The engineer should proactively seek clarification on non-functional requirements, new knowledge, and adapt to new trends, technical solutions, and patterns.
- Cloud environments – AWS preferred
- Data ETL/ELT transformation (e.g., Python, Spark, SSIS)
- Deep knowledge of Microsoft SQL Server internals
- Data modelling and design experience
- .NET and .NET Core/Standard development in C#
- Streaming data solutions
- Scripting (e.g., PowerShell)
- Data governance
- CI/CD
- Source control (e.g., Git, GitHub etc) and continuous integration (e.g., GitHub Actions, Code Deploy etc)
- Performance, profiling, troubleshooting and issue resolution
- Data Analysis / Data Science
- Serverless technologies (e.g., S3, Lambda, Glue, Athena, DynamoDB)
- BI and Reporting technologies (PowerBI, SSRS, etc)
- Test automation frameworks supporting unit, integration, end to end testing