Senior Azure Databricks Data Engineer (Lakehouse)

XPT Software Australia Pty Ltd; Sydney; Sur place; AUD 180 000 - 230 000; Plein temps

Résumé du poste

XPT Software Australia Pty Ltd is seeking a Senior Data Engineer in Sydney to design, build, and optimize data pipelines and lakehouse solutions that support analytics, reporting, and enterprise decision-making. You will work with Azure Databricks, Delta Lake, and a broad Azure data ecosystem, delivering production-grade pipelines and governance across environments.

The role emphasizes scalable batch/streaming processing, data quality, and cost-aware Spark tuning while collaborating with

Qualifications

• 8+ years of experience in data engineering, data integration, ETL/ELT, or large-scale data platform delivery.
• Strong hands-on experience with Azure Databricks, notebooks, jobs or workflows, cluster configuration, debugging, and performance tuning.
• Advanced proficiency in Python, PySpark, and SQL for production-grade data engineering.
• Strong experience with Delta Lake and lakehouse architecture, including reliable incremental processing and data-quality controls.
• Practical experience with Azure Data Lake Storage Gen2 and Azure Data Factory.
• Experience implementing CI/CD using Azure DevOps, Git, branching strategies, automated testing, and environment-based deployment controls.
• Strong understanding of dimensional modelling, data warehousing, data lake design, metadata, lineage, partitioning, and file formats such as Parquet.

Responsabilités

• Design, build, and optimize scalable batch and streaming data pipelines using Azure Databricks, PySpark, Python, SQL, and Delta Lake.
• Develop reusable ingestion, transformation, validation, and publishing frameworks for large-scale enterprise datasets.
• Implement medallion or layered lakehouse patterns across raw, curated, and consumption-ready data zones.
• Integrate Azure Databricks with Azure Data Lake Storage Gen2, Azure Data Factory, Azure Key Vault, Azure DevOps, and related Azure services.
• Develop production-grade Databricks notebooks, jobs, workflows, libraries, and cluster configurations.
• Create complex SQL and PySpark transformations, data-quality checks, reconciliation logic, and error-handling routines.
• Optimize Spark workloads, storage layouts, partitioning, file sizes, caching, and query performance while controlling platform cost.
• Implement Delta Lake capabilities such as ACID transactions, schema enforcement, schema evolution, time travel, and merge operations.
• Build automated CI/CD pipelines for code promotion, configuration management, testing, and deployment across environments.
• Apply data security and governance controls using role-based access, secrets management, data masking, auditability, and controlled access patterns.
• Monitor data pipelines, troubleshoot failures, perform root-cause analysis, and deliver sustainable production fixes.
• Partner with Architects, Business Analysts, Data Analysts, Product Owners, and business stakeholders to convert requirements into reliable data products.
• Provide technical leadership, code reviews, engineering standards, and mentoring to other data engineers.

Connaissances

Azure Databricks

Python

PySpark

SQL

Delta Lake

Azure Data Lake Storage Gen2

Azure Data Factory

Azure DevOps

CI/CD

Data governance

Data security

ETL/ELT

Outils

Terraform

Bicep

dbt

Airflow

Kafka

Power BI

Description du poste

XPT Software Australia Pty Ltd is seeking a Senior Data Engineer in Sydney to design, build, and optimize data pipelines and lakehouse solutions that support analytics, reporting, and enterprise decision-making. You will work with Azure Databricks, Delta Lake, and a broad Azure data ecosystem, delivering production-grade pipelines and governance across environments.

The role emphasizes scalable batch/streaming processing, data quality, and cost-aware Spark tuning while collaborating with