Quantexa Data Engineer | Contract | Melbourne, Sydney or Canberra (Hybrid)
My client, a global IT services and consulting provider, is looking for an experienced Quantexa Data Engineer to join a data and decision intelligence program.
You'll build and maintain the data pipelines and integration processes behind the Quantexa platform. That means bringing together data from multiple source systems, resolving entities, and creating trusted, connected views of people, organisations, accounts and transactions. The program sits within a broader data and AI governance context, so data must be accurate, traceable and fit for enterprise risk and compliance use.
Contract summary
Duration: 6–12 months
Rate: Negotiable, based on experience
Location: Melbourne, Sydney or Canberra
Key responsibilities
Ingest and prepare data from multiple internal and external sources for Quantexa
Design, develop and maintain transformation and processing pipelines
Map source data into Quantexa data models and entity structures
Cleanse, standardise, validate and reconcile complex, high-volume datasets
Configure and support entity resolution, matching and network generation
Optimise pipelines for performance, scalability and reliability
Troubleshoot data quality issues and pipeline or platform failures
Embed data quality, lineage and access controls into engineering processes
Work closely with architects, BAs,



data specialists and governance stakeholders
Support testing, release, production deployment and ongoing maintenance
Essential skills and experience
Hands‐on experience delivering Quantexa implementations as an engineer or developer
Scala and Apache Spark for large-scale distributed processing
Strong SQL
Data modelling, mapping and integration across disparate systems
Understanding of entity resolution (record matching, deduplication, entity linking)
Transparent communicator who can explain what they built, how and why
Quantexa certification or delivery through a Quantexa partner practice
Financial services, financial crime, fraud, AML, risk or compliance data experience
Network or graph analytics experience
Cloud data platforms (AWS, Azure or GCP), Elasticsearch, Git and CI/CD
Data governance exposure (lineage, provenance, data quality frameworks, access controls)
Government or regulated-sector experience; an Australian Government security clearance may be an advantage, particularly for Canberra
What success looks like
You can point to a project where you received data from multiple source systems, built or modified pipelines to integrate it, resolved data quality issues, implemented entity matching and linking, and delivered a stable, performant solution into production.
expected day rate.
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📌 Data Engineer (Melbourne)
🏢 IT & Telecomms
📍 Melbourne