Data Engineer / SQL Developer
Summary
Build and scale data pipelines, models, and migrations for a golf-tech SaaS platform, migrating legacy data to Snowflake and enabling AI-powered features.
Organisational Background
DotGolf is an international golf technology company that provides software, systems, and solutions for golfers, golf clubs, and golf organisations. We exist to create golf technology solutions that help grow the game.
Well established in New Zealand for over 20 years, we also service international markets in the UK, Europe, Australia, Pacific Islands, and Africa. We currently serve 21 national golfing associations, over 5,000 golf clubs, and around 2 million golfers.
DotGolf has lofty future ambitions that are focused on strengthening our current customer base, growing new customers in new markets, and innovating with new products and services.
We have a passionate team and have built a great culture which has led to some great company success stories. DotGolf HQ is in Albany on the North Shore, and we are also supported by international offices abroad.
About the role
We are looking for a Data Engineer to help build and scale the data capabilities that underpin our platform and continued growth.
A key focus of the role will be the hands-on delivery of customer data migrations and helping us make onboarding increasingly efficient and scalable. You will work with data from legacy and third-party technology platforms, developing repeatable processes, tooling and automation that enable customers to transition onto our platform reliably and at scale.
Alongside this, you will build and maintain data pipelines and models, help improve performance as our platform and data volumes grow, and collaborate with our data, product and engineering teams to develop data and AI-enabled products and insights for our customers.
What you'll do
Own the hands-on delivery of customer data migrations, from understanding and mapping source data through to transformation, validation and migration.
Work with complex data from legacy and third-party technology platforms and map it effectively into our SaaS platform.
Develop repeatable migration processes, tooling and automation to make customer onboarding faster, more reliable and scalable.
Design, build and maintain ETL/ELT pipelines and data models.
Contribute to the modernisation of our reporting and data platform, migrating existing reporting workloads and data models from our legacy SQL environment to Snowflake.
Write and optimise advanced SQL queries across large and complex datasets.
Establish strong data quality, testing and validation practices.
Investigate and resolve data, pipeline and integration issues.
Identify and improve data-related performance across queries, models and pipelines as our platform grows.
Collaborate with data, product and engineering teams to build and evolve data and AI-enabled products and insights for our customers.
Help continuously improve how we build and manage our data solutions.
What we're looking for
You'll be an experienced Data Engineer with strong capability in:
Advanced SQL, including complex queries, data transformation, troubleshooting and performance optimisation.
Data modelling, with experience designing scalable and maintainable data structures.
ETL / ELT, building and maintaining reliable data pipelines and integrations.
Data migration, including mapping, transforming, cleansing and validating data between systems.
Performance and reliability, with the ability to investigate data-related issues and optimise solutions as data volumes grow.
Experience with modern cloud data platforms is important, with our current environment including Snowflake and AWS. Experience with Snowflake would be particularly valuable as we continue to migrate and modernise our reporting and data capabilities.
Experience with Python, data quality and testing practices, Git and CI/CD would also be valuable.
You'll be comfortable working with unfamiliar systems and complex datasets, taking ownership of your work and collaborating with others to solve problems. You'll look for opportunities to create reusable approaches and automation rather than solving the same problem twice.
We're also interested in how data can enable new AI-powered products and experiences, so an interest in AI and emerging data technologies would be an advantage.
An interest in golf is welcome, but not essential.