Data Engineer (Remote)

Whether you’re working from home or on your way to the office, chances are you’re probably reading this because you’re seeking a new adventure, or you’re up for a new challenge. GROW Inc might just be that for you!

So, who is GROW Inc?
Founded in 2016, we’re the Australian FinTech success story you probably haven’t heard about. We’re solving big problems in the Superannuation and Managed Funds industry. The administration platforms (the software that tracks everything to do with your super) are built on things you or your parents would recognise from the glory days of 90’s computing.

How are we doing it?
We’re solving this by disrupting the wealth management industry with DLTA, our platform built on Distributed Ledger Technology which improves the financial wellbeing of Australians. We’re making Super more timely and information more accessible whilst enabling wealth management companies to offer more cost effective solutions.

We’re rebels with a cause. We’re authentic, diverse, and embrace our differences as we continue to put a dent in the universe. We know diversity of thought helps us to build better solutions for our customers which is why we encourage the entire GROW team to bring their whole selves to work each and every day.

Job Description

As a Data Engineer at GROW, you will own the development and continuous improvement of our data platform capabilities including data pipelines, data lake & warehouse, lakehouse ingestion and integration with reporting & operational systems.

• Technical Skills:

  • Strong data warehouse development – SQL, Python, Spark, DBT, Databricks. Any experience in test automation using DBT is nice to have.

  • AWS experience is advantageous but happy to consider strong experience with other clouds – Azure and GCP.

  • DevOps experience is highly advantageous.

• Security & Governance:

  • Build data pipelines and stores that are secure from the start

  • Applies data governance practices upfront

• Design/Architecture:

  • Identify and adopts best practices in data engineering at all levels the process

  • Develop scalable, robust and pragmatic solutions to problems that provide flexibility without sacrificing simplicity

• Quality:

  • Develop high-quality data pipelines backed by automated test cases

• Teamwork

  • Collaborate with the product owner, designers and QA to understand the problems that need solving and work with them on viable solutions.

• Data Engineering

  • Participate in Scrum and understand what a good data engineering process is and seek to improve the status quo. Understand the flow of work into production

  • Participate in improving the delivery process (CI/CD)

Additional Information

Why you’ll love working at GROW

• 1 day of birthday leave each year
• Health insurance for you and 1 dependent
• Government Contributions paid on top of salary
• Flexible, remote working environment
• Diverse, friendly, and transparent culture
• On-the-job learning and training

Looking for a job can be stressful and we don’t want you agonising over the wording of your cover letter, so don’t include one. Just make sure your CV is well-written and detailed enough so we can get a better idea of the type of person you are. Even if you don’t meet every single requirement, but you feel inspired to join our mission, we encourage you to send in your application. You never know, you could be the perfect person to join our team!

We are a 2024 Circle Back Initiative Employer – we commit to respond to every applicant