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Senior Data Engineer

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Nuix

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Location:
Australia , Sydney

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Category:
IT - Software Development

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Contract Type:
Employment contract

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Salary:

Not provided
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Job Description:

The Senior Data Engineer will design and oversee data pipelines in Databricks on AWS, manage integrations with SaaS platforms and implement robust data quality and observability frameworks. This role ensures reliable, high-performance data delivery for enterprise analytics and AI workloads.

Job Responsibility:

  • Design, build and maintain scalable ETL/ELT pipelines that ingest, transform and deliver trusted data for analytics and AI use cases
  • Build data integrations with well-known SaaS platforms such as Salesforce, NetSuite, Jira and others
  • Implement incremental and historical data processing to ensure accurate, up-to-date data sets
  • Ensure data quality, reliability and performance across pipelines through validation, testing and continuous code optimization
  • Contribute to data governance and security by supporting data lineage, metadata management and data access controls
  • Support production operations, including monitoring, alerting and troubleshooting
  • Work with stakeholders to translate business and technical requirements into well-structure, reliable datasets
  • Share knowledge and contribute to team standards, documentation and engineering best practices

Requirements:

  • Data Ingestion & Integration: hands-on experience building robust ingestion pipelines using tools and patterns such as Databricks Auto Loader, Lakeflow Connectors, Fivetran and/or custom API / file-based integrations
  • Core Data Engineering: strong development experience using SQL, Python and Apache Spark (PySpark) for large-scale data processing
  • Data Pipeline Orchestration: proven experience developing and operating data pipelines using Databricks Workflows & Jobs, Delta Live Tables (DLT) and/or Lakeflow Declarative Pipelines
  • Incremental Processing & Data Modelling: deep understanding of incremental data loading, including Change Data Capture (CDC), MERGE operations and Slowly Changing Dimensions (SCD) in a Lakehouse environment
  • Data Transformation & Lakehouse Design: experience in designing and implementing Medallion Architecture (bronze, silver and gold) using Delta Lake
  • Data Quality, Test and Observability: experience implementing data quality checks with tools and frameworks such as DLT expectations, Great Expectations or similar, including pipeline testing and monitoring
  • Data Governance & Lineage: hands-on experience with data cataloguing, lineage and metadata management within Unity Catalog to support governance, auditing and troubleshooting
  • Performance Optimization: experience tuning Spark and Databricks workloads, including partitioning strategies, file sizing, query optimization and efficient use of Delta Lake features
  • Production Engineering Practices: experience working with code versioning (Git), peer review and promoting pipelines through development, test and production environments
  • Security & Access Control Awareness: Understanding of data access control, sensitive data handling and working with Unity Catalog in the context of governed environments
  • Stakeholder & Team Collaboration: strong communication and analytical skills working with business and technical stakeholders to gather requirements, explain data concepts and support downstream users such as analysts and dashboard developers

Nice to have:

  • Experience with Amazon Web Services (AWS)
  • Understanding of DevOps best-practices and solutions such as: Infrastructure-as-code (Terraform)
  • Databricks Asset Bundles
  • CI/CD pipelines (Jenkins)
  • Familiarity with data warehousing and dimensional modelling methodologies (e.g. Kimball, facts & dimensions, star schemas, data marts)
  • Basic understanding of AI & ML, including preparation of structured and unstructured data for ML use cases and AI agents

Additional Information:

Job Posted:
February 19, 2026

Employment Type:
Fulltime
Work Type:
Hybrid work
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