📍 Job Overview

Job Title: Senior Data Platform Engineer
Company: HSO
Location: Hamilton, Waikato, New Zealand
Job Type: Hybrid
Category: Data Engineering
Date Posted: 2025-07-14
Experience Level: Mid-Senior Level (2-5 years)
Remote Status: Hybrid (On-site and Remote)

🚀 Role Summary

Design and implement modern data platforms using Azure Databricks, Microsoft Fabric, Azure Synapse, Data Factory, Power BI, and Purview.
Build scalable ETL pipelines using Spark, Python, and other modern tools.
Collaborate directly with clients to understand their needs and deliver high-value, billable outcomes.
Translate business ideas into technical architecture and data platform solutions.
Mentor others and contribute to internal capability uplift.
Stay curious and explore emerging tech like Machine Learning, IoT, and Infrastructure-as-Code.

📝 Enhancement Note: This role requires a strong background in data engineering with a focus on Azure technologies. The hybrid work arrangement allows for a balance between on-site collaboration and remote work flexibility.

💻 Primary Responsibilities

Data Platform Design & Implementation: Design and implement modern data platforms using Azure Databricks, Microsoft Fabric, Azure Synapse, Data Factory, Power BI, and Purview. Ensure these platforms are scalable, secure, and efficient.
ETL Pipeline Development: Build and maintain scalable ETL pipelines using Spark, Python, and other modern tools. Optimize these pipelines for performance and reliability.
Client Collaboration: Work directly with clients to understand their data needs and deliver high-value, billable outcomes. This involves active listening, problem-solving, and effective communication.
Solution Architecture: Translate business ideas and requirements into technical architecture and data platform solutions. Ensure these solutions are aligned with industry best practices and meet business objectives.
Mentoring & Knowledge Sharing: Mentor junior team members and contribute to internal capability uplift. Share your knowledge and experiences to help others grow professionally.
Emerging Tech Exploration: Stay curious and explore emerging tech like Machine Learning, IoT, and Infrastructure-as-Code. Keep up-to-date with the latest trends and tools in data engineering.

📝 Enhancement Note: This role requires a strong balance of technical expertise and soft skills, with a focus on client collaboration and solution architecture. The ability to mentor others and explore emerging tech is also crucial for success in this position.

🎓 Skills & Qualifications

Education: A bachelor's degree in Computer Science, Data Science, or a related field. Relevant certifications (e.g., Azure Data Engineer Associate, Azure Solutions Architect Expert) are a plus.

Experience: 2-5 years of experience in data engineering, with a strong focus on Azure technologies. Proven experience in consulting or professional services is essential.

Required Skills:

Proven experience in data engineering using Databricks or Microsoft Fabric.
Strong experience in modern cloud engineering with a clear preference for Azure.
Proven experience with Azure Purview, Azure Data Factory, Azure Synapse Analytics, Power BI, or their equivalents.
Experience building cloud systems that wrangle raw data and surface it for reporting or AI workloads.
Solid ETL/data integration skills using Spark, Python, or similar tools.
A background in consulting or professional services, with the ability to manage multiple client deadlines.
Strong interpersonal skills and confidence working directly with clients.
High learning agility and the ability to problem-solve across a range of data domains.
Ability to explain technical solutions to non-technical audiences.

Preferred Skills:

Experience with Machine Learning, IoT, or Infrastructure-as-Code.
Familiarity with other cloud platforms (e.g., AWS, GCP) and ability to work in Azure.
Strong business acumen and the ability to align technical solutions with strategic goals.
High emotional intelligence and a collaborative mindset.
Clear and confident communication across technical and business audiences.
Proven technical leadership in data platform engineering.
Exceptional complex problem-solving skills in dynamic environments.

📝 Enhancement Note: While the required skills are essential for success in this role, the preferred skills will set you apart as an exceptional candidate. These skills demonstrate a strong understanding of the Azure ecosystem, emerging tech, and the ability to thrive in a dynamic consulting environment.

📊 Web Portfolio & Project Requirements

Portfolio Essentials:

Data Platform Projects: Showcase your experience in designing and implementing modern data platforms. Highlight the tools and technologies used, as well as the outcomes and impact of these projects.
ETL Pipeline Projects: Demonstrate your ability to build and maintain scalable ETL pipelines. Include examples of performance optimization and problem-solving in these projects.
Client Collaboration Projects: Provide examples of successful client collaborations. Explain how you understood their needs, delivered high-value outcomes, and managed multiple client deadlines.
Solution Architecture Projects: Showcase your ability to translate business ideas into technical architecture and data platform solutions. Include case studies that demonstrate your problem-solving skills and alignment with business objectives.

Technical Documentation:

Code Quality & Documentation: Include examples of well-documented code, with clear comments and adherence to coding standards. Demonstrate your ability to write clean, efficient, and maintainable code.
Version Control & Deployment Processes: Showcase your experience with version control systems (e.g., Git) and deployment processes. Include examples of automated deployment pipelines and server configuration.
Testing Methodologies & Performance Metrics: Demonstrate your understanding of testing methodologies and performance metrics. Include examples of how you've optimized data platforms and ETL pipelines for performance and reliability.

📝 Enhancement Note: Your portfolio should highlight your technical expertise, client collaboration skills, and problem-solving abilities. Include case studies that demonstrate your experience with Azure technologies and data engineering best practices.

💵 Compensation & Benefits

Salary Range: The salary range for this role is estimated to be NZD 120,000 - 160,000 per annum, depending on experience and qualifications. This estimate is based on market research and industry standards for senior data engineering roles in New Zealand.

Benefits:

Flexible Working: Enjoy a flexible work arrangement that balances on-site collaboration and remote work.
Work-Life Balance: HSO is committed to supporting a healthy work-life balance, with a focus on avoiding overtime and tracking time-in-lieu.
Ongoing Learning Opportunities: Stay up-to-date with the latest trends and tools in data engineering through continuous learning and professional development opportunities.
Team Lunches & Snacks: Enjoy regular team lunches and access to snacks and espresso machines to fuel your productivity.
Modern Office Space: Work in a modern office space equipped with ergonomic desks, great tech setups, cool demos, and greenery to create a zen working environment.

Working Hours: The standard working week is 40 hours, with flexibility for deployment windows, maintenance, and project deadlines.

📝 Enhancement Note: The salary range is estimated based on market research and industry standards for senior data engineering roles in New Zealand. The benefits package is designed to support a healthy work-life balance and provide ongoing learning opportunities to help you grow professionally.

🎯 Team & Company Context

🏢 Company Culture

Industry: HSO is a specialist in emerging tech, focusing on cloud-native data solutions and consulting services. This role will involve working with clients across various industries, exposing you to a diverse range of data domains and challenges.

Company Size: HSO is a growing company with a strong presence across the ANZ region. This means you'll have the opportunity to work on exciting projects and collaborate with a diverse team of professionals.

Founded: HSO was founded with a mission to help businesses unlock the power of data through innovative, cloud-native solutions. The company values curiosity, collaboration, and a good dose of banter, creating a dynamic and engaging work environment.

Team Structure:

Data Engineering Team: You'll be part of the Professional Services team, which is responsible for delivering impactful data projects for clients. This team consists of data engineers, data analysts, and data scientists, all working together to solve real-world problems.
Reporting Structure: As a senior data platform engineer, you'll report directly to the Data Engineering Manager. You'll be expected to mentor junior team members and contribute to internal capability uplift.
Cross-Functional Collaboration: You'll work closely with other teams, including sales, marketing, and project management, to ensure that client needs are met and projects are delivered on time and within budget.

Development Methodology:

Agile/Scrum Methodologies: HSO uses Agile/Scrum methodologies to manage projects and deliver high-value outcomes for clients. You'll be expected to participate in sprint planning, daily stand-ups, and retrospectives to ensure that projects are delivered efficiently and effectively.
Code Review & Testing: HSO places a strong emphasis on code review and testing to ensure the quality and reliability of data platforms and ETL pipelines. You'll be expected to participate in code reviews and help maintain high coding standards.
Deployment Strategies: HSO uses automated deployment pipelines and infrastructure-as-code (IaC) tools to ensure that data platforms and ETL pipelines are deployed consistently and reliably. You'll be expected to contribute to the development and maintenance of these deployment strategies.

Company Website: HSO Website

📝 Enhancement Note: HSO's company culture is built on curiosity, collaboration, and a strong focus on emerging tech. The team structure and development methodologies are designed to support a dynamic and innovative work environment, where you can grow both personally and professionally.

📈 Career & Growth Analysis

Web Technology Career Level: This role is at the senior level, requiring a strong background in data engineering with a focus on Azure technologies. You'll be expected to provide technical leadership and mentorship to junior team members, as well as contribute to internal capability uplift.

Reporting Structure: As a senior data platform engineer, you'll report directly to the Data Engineering Manager. You'll be expected to mentor junior team members and contribute to internal capability uplift.

Technical Impact: In this role, you'll have a significant impact on the design and implementation of modern data platforms and ETL pipelines. Your work will directly influence the ability of clients to extract value from their data and make data-driven decisions.

Growth Opportunities:

Technical Leadership: As a senior team member, you'll have the opportunity to develop your technical leadership skills by mentoring junior team members and contributing to internal capability uplift. You'll also have the chance to work on complex projects that challenge your problem-solving abilities and help you grow professionally.
Emerging Tech Exploration: HSO encourages its team members to stay curious and explore emerging tech like Machine Learning, IoT, and Infrastructure-as-Code. You'll have the opportunity to work on cutting-edge projects and stay up-to-date with the latest trends and tools in data engineering.
Career Progression: As a senior team member, you'll be well-positioned to progress to a leadership role within the data engineering team or take on a more strategic role within the organization.

📝 Enhancement Note: This role offers significant opportunities for career growth and technical development. By joining HSO, you'll have the chance to work on complex projects, mentor junior team members, and explore emerging tech in a dynamic and innovative work environment.

🌐 Work Environment

Office Type: HSO's office is a modern, collaborative workspace designed to support a dynamic and innovative work environment. The office is equipped with ergonomic desks, great tech setups, cool demos, and greenery to create a zen working environment.

Office Location(s): HSO's office is located in Hamilton, Waikato, New Zealand. The office is easily accessible by public transportation and offers ample parking for those who prefer to drive.

Workspace Context:

Collaborative Work Environment: HSO's office is designed to encourage collaboration and teamwork. You'll have the opportunity to work closely with other data engineers, data analysts, and data scientists to solve real-world problems and deliver high-value outcomes for clients.
Modern Tech Setup: HSO provides its team members with modern tech setups, including ergonomic desks, high-quality monitors, and powerful workstations. You'll have everything you need to work efficiently and effectively.
Greenery & Zen Working Environment: HSO's office is designed to be a peaceful and relaxing workspace. The office is filled with greenery and natural light, creating a zen working environment that supports productivity and well-being.

Work Schedule: HSO offers a flexible work arrangement that balances on-site collaboration and remote work. The standard working week is 40 hours, with flexibility for deployment windows, maintenance, and project deadlines.

📝 Enhancement Note: HSO's work environment is designed to support a dynamic and innovative work environment, where you can collaborate with other professionals and grow both personally and professionally. The modern tech setup, greenery, and flexible work arrangement ensure that you have everything you need to work efficiently and effectively.

📄 Application & Technical Interview Process

Interview Process:

Technical Assessment: You'll be asked to complete a technical assessment that focuses on your data engineering skills and problem-solving abilities. This assessment may include coding challenges, system design exercises, and architecture decision-making scenarios.
Client Collaboration Simulation: You'll be asked to participate in a simulated client collaboration scenario, where you'll work with a mock client to understand their needs and deliver a high-value outcome. This simulation will assess your interpersonal skills, communication abilities, and client management skills.
Technical Deep Dive: You'll be asked to participate in a technical deep dive, where you'll discuss your experience with Azure technologies, data engineering best practices, and emerging tech like Machine Learning, IoT, and Infrastructure-as-Code.
Final Evaluation: You'll be evaluated based on your technical expertise, problem-solving abilities, client collaboration skills, and cultural fit within the HSO team.

Portfolio Review Tips:

Curate Your Portfolio: Tailor your portfolio to showcase your experience with Azure technologies, data engineering best practices, and emerging tech like Machine Learning, IoT, and Infrastructure-as-Code.
Include Case Studies: Include case studies that demonstrate your ability to design and implement modern data platforms, build scalable ETL pipelines, and deliver high-value outcomes for clients.
Highlight Your Problem-Solving Skills: Highlight your problem-solving skills by including examples of complex data engineering challenges you've faced and how you overcame them.
Demonstrate Your Technical Leadership: Include examples of your technical leadership skills, such as mentoring junior team members or contributing to internal capability uplift.

Technical Challenge Preparation:

Brush Up on Azure Technologies: Familiarize yourself with the latest Azure technologies, including Azure Databricks, Microsoft Fabric, Azure Synapse, Azure Data Factory, Power BI, and Azure Purview.
Practice Coding Challenges: Practice coding challenges that focus on data engineering tasks, such as ETL pipeline development, data transformation, and data warehousing.
Prepare for System Design Exercises: Familiarize yourself with system design principles and best practices. Practice system design exercises that focus on data engineering scenarios.
Develop Your Communication Skills: Hone your communication skills by practicing how to explain technical solutions to non-technical audiences. This will be essential for success in the client collaboration simulation and technical deep dive.

📝 Enhancement Note: The interview process for this role is designed to assess your technical expertise, problem-solving abilities, client collaboration skills, and cultural fit within the HSO team. By following the tips and strategies outlined above, you'll be well-prepared to succeed in the interview process and secure the role of senior data platform engineer at HSO.

🛠 Technology Stack & Web Infrastructure

Frontend Technologies: This role does not have a significant frontend technology component. However, you should be familiar with data visualization tools like Power BI and have experience creating user-friendly dashboards and reports.

Backend & Server Technologies:

Azure Databricks: A fully-managed Apache Spark-based analytics service provided by Microsoft Azure. You'll use Databricks to design and implement modern data platforms and build scalable ETL pipelines.
Microsoft Fabric: A unified analytics service provided by Microsoft Azure. Fabric combines data integration, data warehousing, and data governance capabilities to help you build and manage modern data platforms.
Azure Synapse: A limitless analytics service provided by Microsoft Azure. Synapse brings together enterprise data warehousing and Big Data analytics. You'll use Synapse to design and implement modern data platforms and build scalable ETL pipelines.
Azure Data Factory: A cloud-based data integration service provided by Microsoft Azure. Data Factory allows you to create, schedule, and monitor data integration projects on a centralized platform. You'll use Data Factory to build and manage ETL pipelines.
Power BI: A suite of business analytics tools provided by Microsoft. Power BI allows you to visualize and analyze data, create reports, and build dashboards. You'll use Power BI to create user-friendly data visualizations and support self-service BI.
Azure Purview: A unified data governance service provided by Microsoft Azure. Purview helps you manage data governance at scale, ensuring that your data is accurate, complete, and compliant with relevant regulations.

Development & DevOps Tools:

Git: A distributed version control system that enables multiple developers to work together on a single codebase. You'll use Git to manage version control and collaborate with other data engineers.
Azure DevOps: A cloud-based platform provided by Microsoft Azure that supports the entire software development lifecycle. You'll use Azure DevOps to manage version control, continuous integration, and continuous deployment pipelines.
Terraform: An open-source infrastructure-as-code (IaC) software tool that allows you to define and provision cloud resources in a declarative way. You'll use Terraform to manage infrastructure-as-code and ensure that your data platforms and ETL pipelines are deployed consistently and reliably.

📝 Enhancement Note: The technology stack for this role is focused on Azure technologies, data engineering best practices, and emerging tech like Machine Learning, IoT, and Infrastructure-as-Code. Familiarize yourself with these technologies and tools to ensure success in the role of senior data platform engineer at HSO.

👥 Team Culture & Values

Web Development Values:

Curiosity: HSO values curiosity and encourages its team members to stay up-to-date with the latest trends and tools in data engineering. You'll be expected to stay curious and explore emerging tech like Machine Learning, IoT, and Infrastructure-as-Code.
Collaboration: HSO values collaboration and encourages its team members to work closely with other professionals to solve real-world problems. You'll be expected to collaborate with data engineers, data analysts, and data scientists to deliver high-value outcomes for clients.
Performance Optimization: HSO values performance optimization and encourages its team members to optimize data platforms and ETL pipelines for speed, scalability, and reliability. You'll be expected to optimize data platforms and ETL pipelines to ensure that they meet business objectives and support data-driven decision-making.
Accessibility: HSO values accessibility and encourages its team members to create user-friendly data visualizations and support self-service BI. You'll be expected to create user-friendly dashboards and reports that meet the needs of a diverse range of users.

Collaboration Style:

Cross-Functional Integration: HSO encourages cross-functional integration between data engineers, data analysts, and data scientists. You'll work closely with these professionals to ensure that data platforms and ETL pipelines meet business objectives and support data-driven decision-making.
Code Review Culture: HSO places a strong emphasis on code review and testing to ensure the quality and reliability of data platforms and ETL pipelines. You'll participate in code reviews and help maintain high coding standards.
Knowledge Sharing: HSO encourages knowledge sharing and supports a culture of continuous learning and professional development. You'll be expected to share your knowledge and experiences with junior team members and contribute to internal capability uplift.

📝 Enhancement Note: HSO's team culture is built on curiosity, collaboration, performance optimization, and accessibility. By joining HSO, you'll have the opportunity to work with a diverse team of professionals and grow both personally and professionally in a dynamic and innovative work environment.

⚡ Challenges & Growth Opportunities

Technical Challenges:

Azure Databricks: Design and implement modern data platforms using Azure Databricks. Optimize these platforms for speed, scalability, and reliability, and ensure that they meet business objectives.
Azure Synapse: Build scalable ETL pipelines using Azure Synapse. Optimize these pipelines for performance and reliability, and ensure that they meet business objectives.
Azure Data Factory: Manage ETL pipelines using Azure Data Factory. Ensure that these pipelines are deployed consistently and reliably, and that they meet business objectives.
Emerging Tech: Stay curious and explore emerging tech like Machine Learning, IoT, and Infrastructure-as-Code. Keep up-to-date with the latest trends and tools in data engineering, and apply them to real-world projects.

Learning & Development Opportunities:

Technical Skill Development: HSO encourages its team members to develop their technical skills and stay up-to-date with the latest trends and tools in data engineering. You'll have the opportunity to work on cutting-edge projects and explore emerging tech in a dynamic and innovative work environment.
Conference Attendance: HSO supports its team members' attendance at relevant conferences and events. You'll have the opportunity to network with other professionals, learn about the latest trends and tools in data engineering, and share your experiences and insights with the wider community.
Mentorship & Leadership Development: HSO encourages its team members to mentor junior team members and contribute to internal capability uplift. You'll have the opportunity to develop your leadership skills and help others grow professionally in a dynamic and innovative work environment.

📝 Enhancement Note: This role offers significant technical challenges and learning opportunities. By joining HSO, you'll have the chance to work on cutting-edge projects, explore emerging tech, and develop your technical skills in a dynamic and innovative work environment.

💡 Interview Preparation

Technical Questions:

Azure Technologies: Be prepared to discuss your experience with Azure technologies, including Azure Databricks, Microsoft Fabric, Azure Synapse, Azure Data Factory, Power BI, and Azure Purview. Demonstrate your understanding of these technologies and how you've used them to design and implement modern data platforms and build scalable ETL pipelines.
Data Engineering Best Practices: Be prepared to discuss data engineering best practices, including ETL pipeline development, data transformation, and data warehousing. Demonstrate your understanding of these best practices and how you've applied them to real-world projects.
Emerging Tech: Be prepared to discuss emerging tech like Machine Learning, IoT, and Infrastructure-as-Code. Demonstrate your understanding of these technologies and how you've explored them in a professional context.

Company & Culture Questions:

HSO's Mission & Values: Be prepared to discuss HSO's mission and values, and how they align with your personal and professional goals. Demonstrate your understanding of HSO's commitment to curiosity, collaboration, performance optimization, and accessibility.
Client Collaboration: Be prepared to discuss your experience with client collaboration and how you've delivered high-value outcomes for clients in a professional services context. Demonstrate your ability to understand client needs, manage multiple client deadlines, and communicate effectively with non-technical stakeholders.
Team Dynamics: Be prepared to discuss your experience working in a team environment and how you've contributed to internal capability uplift. Demonstrate your ability to mentor junior team members, collaborate with other professionals, and support a culture of continuous learning and professional development.

Portfolio Presentation Strategy:

Curate Your Portfolio: Tailor your portfolio to showcase your experience with Azure technologies, data engineering best practices, and emerging tech like Machine Learning, IoT, and Infrastructure-as-Code.
Highlight Your Problem-Solving Skills: Include examples of complex data engineering challenges you've faced and how you overcame them. Highlight your ability to design and implement modern data platforms, build scalable ETL pipelines, and deliver high-value outcomes for clients.
Demonstrate Your Technical Leadership: Include examples of your technical leadership skills, such as mentoring junior team members or contributing to internal capability uplift. Highlight your ability to work with other professionals to solve real-world problems and deliver high-value outcomes for clients.

📝 Enhancement Note: The interview process for this role is designed to assess your technical expertise, problem-solving abilities, client collaboration skills, and cultural fit within the HSO team. By following the tips and strategies outlined above, you'll be well-prepared to succeed in the interview process and secure the role of senior data platform engineer at HSO.

📌 Application Steps

To apply for this senior data platform engineer position at HSO:

Customize Your Portfolio: Tailor your portfolio to showcase your experience with Azure technologies, data engineering best practices, and emerging tech like Machine Learning, IoT, and Infrastructure-as-Code. Highlight your problem-solving skills, technical leadership, and client collaboration abilities.
Optimize Your Resume: Optimize your resume for web development and server administration roles by including relevant keywords and highlighting your experience with Azure technologies, data engineering best practices, and emerging tech. Emphasize your problem-solving skills, technical leadership, and client collaboration abilities.
Prepare for Technical Challenges: Brush up on your Azure technologies, data engineering best practices, and emerging tech skills. Practice coding challenges, system design exercises, and architecture decision-making scenarios to ensure that you're well-prepared for the technical assessment.
Research HSO: Research HSO's mission, values, and company culture. Understand how HSO's commitment to curiosity, collaboration, performance optimization, and accessibility aligns with your personal and professional goals. Prepare questions to ask during the interview process to demonstrate your interest in the role and the company.

⚠️ Important Notice: This enhanced job description includes AI-generated insights and web development/server administration industry-standard assumptions. All details should be verified directly with the hiring organization before making application decisions.

Senior Data Platform Engineer