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About the Role

The Senior Data Platform 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.

Responsibilities

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

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.
Strong development experience using SQL, Python and Apache Spark (PySpark) for large-scale data processing.
Proven experience developing and operating data pipelines using Databricks Workflows & Jobs, Delta Live Tables (DLT) and/or Lakeflow Declarative Pipelines.
Deep understanding of incremental data loading, including Change Data Capture (CDC), MERGE operations and Slowly Changing Dimensions (SCD) in a Lakehouse environment.
Experience in designing and implementing Medallion Architecture (bronze, silver and gold) using Delta Lake.
Experience implementing data quality checks with tools and frameworks such as DLT expectations, Great Expectations or similar, including pipeline testing and monitoring.
Hands-on experience with data cataloguing, lineage and metadata management within Unity Catalog to support governance, auditing and troubleshooting.
Experience tuning Spark and Databricks workloads, including partitioning strategies, file sizing, query optimization and efficient use of Delta Lake features.
Experience working with code versioning (Git), peer review and promoting pipelines through development, test and production environments.
Understanding of data access control, sensitive data handling and working with Unity Catalog in the context of governed environments.
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.
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.

Skills

Databricks
AWS
SQL
Python
Apache Spark
PySpark
Databricks Auto Loader
Lakeflow Connectors
Fivetran
API integrations
File-based integrations
Databricks Workflows & Jobs
Delta Live Tables (DLT)
Lakeflow Declarative Pipelines
Change Data Capture (CDC)
MERGE operations
Slowly Changing Dimensions (SCD)
Medallion Architecture
Delta Lake
DLT expectations
Great Expectations
Data cataloguing
Data lineage
Metadata management
Unity Catalog
Spark performance tuning
Databricks performance tuning
Partitioning strategies
File sizing
Query optimization
Delta Lake features
Git
Peer review
Infrastructure-as-code (Terraform)
Databricks Asset Bundles
CI/CD pipelines (Jenkins)
Data warehousing
Dimensional modelling
Kimball methodology
Facts & dimensions
Star schemas
Data marts
AI
ML

Location

Sydney

Work Type

Hybrid

Experience Level

Senior

About the Company

Nuix is on an incredible journey of transformation, aligning our strengths with our ambitions to pursue greater opportunities.
As we expand our global team and extend our skills and expertise, we are unified as one Nuix team guided by our shared values.
Nuix Vision: Finding Truth in a Digital World.
Nuix Mission Statement: Nuix creates innovative software that empowers organizations to simply and quickly find the truth from any data in a digital world. We are a passionate and talented team, delighting our customers with software that transforms data into actionable intelligence.
Nuix Values: TAKE OWNERSHIP, RESILIENT, UNRAID, TEAM NUIX, HERO OUR CUSTOMERS.
We believe in these principles and seek to weave them into the fabric of our daily work at Nuix. In doing so, we co-create a dynamic and purposeful company culture that we can be proud of and want to belong to.

Equal Opportunity

Nuix is an equal opportunities employer.
Don’t let imposter syndrome hold you back! We welcome all applications and are a flexible employer.
We strive to make any required adjustments where possible to make the process fair and equitable for everyone.
If you need any accommodations throughout the interview process, please note this in your job application.
Nuix is an Equal Opportunity Employer