Data Architectural Expert

Job Description

We are a leading provider of data-driven solutions, proudly owned by a well-established insurance company. Our organization is comprised of trusted and well-known brands that cater to the needs of millions of Australians.

At our organization, we are passionate about making a difference in people's lives by simplifying their financial decisions. With over two decades of experience, we have established ourselves as a one-stop destination for comparison and purchasing across various products, including insurance, utilities, and personal finance.

Our Noble Purpose is to make a positive impact on the lives of Australians by providing them with easy access to sound financial decisions. This guiding principle is at the heart of everything we do, shaping our direction, prioritization, and decision-making processes.

As a key member of our team, you will have the opportunity to contribute to the development of our modern data platform, built on Databricks/AWS. You will be responsible for establishing foundational engineering principles and providing technical leadership to support our business intelligence, data science, and machine learning practices.

As a Senior Data Engineer, you will be expected to provide guidance on architecture and solution design, while contributing to the data strategy from an engineering perspective. You will work closely with a great team of data scientists, business intelligence developers, data engineers, data architects, data modellers, and business analysts to develop the data platform and overall ecosystem.

Responsibilities:

• Work with data producers, data consumers, and other supporting roles to ensure data is well managed for consumption.">
• Build, maintain, and optimize high-quality data pipelines for serving analytics use-cases, including business intelligence and machine learning.">
• Collaborate with architects to develop architectural patterns for data pipelines, including event-based real-time processing.">
• Support the development and implementation of the data engineering roadmap.">
• Champion best practices for data management and data governance, including data modelling, ETL and processing performance, data quality, observability, discoverability, security, and sensitive data handling.">

Requirements:

• 5+ years of experience as a professional data engineer or analytics engineer, developing ETL pipelines for production environments.">
• Solid experience building analytical data pipelines in cloud systems.">
• Solid data management experience covering data modelling, data quality monitoring, maintaining data dictionaries, row/column level security, sensitive data masking or tokenization, and access controls.">
• Ability to write high-quality code for data pipelines, preferably in Python.">
• Excellent SQL skills.">
• Experience with CI/CD and Infrastructure as Code builds.">
• Experience providing data engineering leadership and mentorship.">
• Solid written and verbal communication skills.">
• Highly regarded:">
• Experience developing on Databricks and/or using Spark or PySpark.">
• Experience building robust feature stores with batch and streaming data for use by machine learning models.">
• Experience building highly automated metadata-driven solutions.">

What We Offer:

• Career opportunities.">
• A competitive salary plus generous uncapped commission scheme.">
• The opportunity to work with a well-known, household brand.">
• Work with a team of highly energized, motivated, and driven professionals.">
• Three 'recharge' days per year.">
• A free coffee each day, a funky café, and a state-of-the-art workspace.">
• An impressive Employee Benefits Program.">

What You Need To Succeed:

If you are someone who fosters team spirit, has resilience, and aspires to continue learning and developing your skills to drive commercial outcomes, you will have tremendous success in helping us achieve our progressive growth agendas. High energy levels and a love of having fun are also important to working in this energetic business.