Data Engineer

Company Goal
The overall goal of the company is to retain as many clients as possible while growing profitably by delivering online solutions to allow our users to capture, track, manage and report on workplace safety incidents, injuries and workers compensation claims as simply and easily as possible.

The Data Engineer plays a critical role in this goal by designing, implementing, and validating bespoke ETL/ELT solutions to onboard new clients, support existing clients, and identify areas of opportunity to enhance customer facing features and internal operations.

Key Responsibilities
The Data Engineer works in the Customer Implementation function reporting into the Senior Resource Manager. Some key responsibilities include:

Core Functions:

• Acts as the Data Lead for new and existing clients with major ETL/ELT requirements
• Build and run pipelines to import data
• Ensure clients maintain compliance with relevant Australian self-insurance regulatory requirements during and after migrations/transformations, through accurate interpretation and application of jurisdictional data submission specifications
• Work with Sales, Implementation Consultants and other relevant stakeholders on communications with clients regarding the scope of data work, and timeframes for deliverables
• Document and communicate client data issues and proposed solutions to relevant stakeholders
• Revise and improve ETL/ELT processes in line with business, project or relevant stakeholder feedback
• Provide support for data fixes in project and after Go-Live

Data Governance & Quality:

• Profile all newly received client data in a timely manner
• Leverage existing processes, tools and frameworks to ingest, transform and load data as required, to test and production systems
• Create, execute and improve data validation processes that verify and effectively communicate the accuracy of migrated or transformed data
• Provide clear communications through relevant project tools which clearly communicate the progress of data migrations, transformations or imports

Continuous Improvement:

• Identify areas for improvement as it relates to HSI Donesafes data operations, including but not limited to:
• ETL / ELT Optimisation
• Migration functions
• Data Quality Frameworks
• Cost efficiency
• Security and Compliance
• Automate and streamline data ingestion and transformation processes
• Improve documentation and Internal Knowledge Base Material on data processes (e.g., implementation documentation, onboarding data packs, client communications etc.)

Key Professional Competencies

• Adaptability – The ability to balance competing priorities and multiple projects in a fast-paced environment
• Customer Focused – Provide timely and clear communication, and put the customer first
• Collaboration – Work effectively with key internal stakeholders (Product Managers, Implementation Team Members, Development) to develop and deliver great outcomes
• Better – Identifying new tools, products and mechanisms to support and improve Data needs
• Problem Solving – Ability to investigate and resolve complex challenges

Key Technical Competencies

• Strong SQL Skills
• Programming experience in another language(s) such as Python, Java, Ruby, etc.
• Experience with bespoke data handling tools
• Familiarity with ETL frameworks
• Hands-on experience with cloud platforms (AWS, GCP, Azure) and their data services
• Knowledge of data modeling and warehousing concepts
• Strong understanding of data governance, data security, and compliance standards