Data Engineer | remote, dayshift

Work setup: remote

Shift schedule: Morning (6:00am - 3:00pm)

DATA AND ANALYTICS ENGINEER

Work for our global clients and immerse in our rich and diverse company culture where you can thrive, grow and just be aweSOme! Apply now and discover the Satellite Office Candidate Experience – recognized as one of BEST among BPO companies worldwide.

WHAT IS A DATA AND ANALYTICS ENGINEER?

Our awesome client, a leading property and construction company based in Australia is looking for a Data and Analytics Engineer to be part of their team.

WHAT WILL BE YOUR MAIN RESPONSIBILITIES?

• Design and build data pipelines and ETL processes to move and transform data reliably across Hickory's systems
• Develop and maintain data models that support reliable, well-structured reporting and analytics
• Write and optimise SQL across data pipelines, reporting layers, and ad hoc analysis
• Build and maintain Power BI dashboards and reports that give stakeholders clear, accurate visibility into business performance
• Apply data structures and algorithms thinking to design efficient, scalable data processes
• Apply version control and CI/CD practices to data pipeline and analytics code, ensuring changes are tested and deployed safely
• Apply AI tools and literacy to accelerate data engineering, analysis, and reporting work
• Contribute to data warehouse design, database administration, or solution architecture where relevant
• Work closely with stakeholders across the business to understand reporting needs and translate them into reliable data solutions

WHAT ARE WE LOOKING FOR?

• 3 to 5 years relevant experience
• Strong SQL skills, comfortable writing and optimising complex queries across large datasets
• Solid experience with data modelling, structuring data for reliable and maintainable reporting
• Hands-on experience building data pipelines and ETL processes
• Experience building data visualisations and dashboards, ideally in Power BI
• Good grounding in data structures and algorithms
• Practical experience with version control (e.g. Git) and CI/CD pipelines
• Working AI literacy - comfortable using AI-assisted tools to support data engineering and analysis
• Exposure to Azure, data warehousing, database administration, or solution architecture is an advantage, not a requirement
• Analytical and curious, detail-oriented, a strong problem solver who communicates well and can work independently