Reflections Technologies [Data Cube]
Website:
datacube.com.au
Company:
https://www.linkedin.com/company/reflections-technologies
Seniority: Mid-Senior level
Industries: IT Services and IT Consulting
Job details:
Looking for 3 to 6 year experienced candidate having strong experience in Azure data platform from scratch, establishing the technical foundation for AI-ready data, reporting, analytics, and data-driven decision-making across the organisation
Primary Skills:
Microsoft Fabric (Lakehouse, Warehouse, Dataflows)
Azure Data Factory (ADF)
Azure Data Lake Storage (ADLS Gen2)
Python
SQL (Advanced queries, performance tuning, data transformation)
ETL/ELT Pipeline Development
Data Modeling & Schema Design
Data Quality and Validation Frameworks
Git Version Control
CI/CD Fundamentals
Responsibilities:
• Actively participate in the design, implementation, and continuous improvement of end-to-
end data platform architecture using modern Azure cloud technologies including Azure Data
Factory, Azure Data Lake Storage, and Microsoft Fabric (Lakehouses and Warehouses).
• Build scalable, reliable ELT/ETL pipelines to ingest, process, and transform data from multiple
source systems including GCAS, GSS, Insurance, Savvy, and BAS systems.
• Implement and maintain automated data quality checks and pipeline testing to ensure
reliability and trust.
• Develop and maintain data lakehouse solutions implementing medallion architecture patterns
with bronze, silver, and gold layers for progressive data refinement.
• Collaborate with offshore data engineering partners to deliver data engineering initiatives,
providing technical guidance and ensuring quality standards.
• Assist the Business Intelligence team with reporting and analytics requirements, ensuring their
needs are supported through effective data solutions.
• Contribute to and adhere to established data governance and security practices, including
metadata management, data quality frameworks, and data cataloging, to promote trust and
reliability.
• Enable business functions with clean, structured data that supports compliance reporting,
customer insights, fraud detection, and product development.
• Provide detailed documentation, knowledge transfer, and training to internal teams to build
data literacy
Click on Apply to know more.
