Senior Data Engineer (Databricks, Data Modeling)

EPAM Systems Inc; New South Wales; On-site; AUD 180,000 - 240,000; Full time

Job summary

EPAM Systems Inc in Australia is seeking a Senior Data Engineer (Databricks, Data Modeling) to model large-scale batch and streaming data into Bronze, Silver and Gold layers for regulatory reporting data products. You will build on Databricks using Spark, Python and SQL, and partner with stakeholders on definitions while using AI-assisted tools to speed up delivery, testing and documentation.

You will design medallion architectures, develop scalable Spark pipelines, and collaborate across teams

Qualifications

• Data modeling across conceptual, logical and physical models.
• Databricks experience including Delta Lake and governance concepts.
• Spark with PySpark and Spark SQL in production.
• Streaming data with Spark Structured Streaming and Kafka.
• Python for pipeline development.
• Advanced SQL for transformations and performance.
• Data governance covering quality, lineage and data contracts.
• AI-assisted development tooling exposure (Claude or similar).

Responsibilities

• Design trusted Bronze, Silver and Gold layers using medallion architecture principles.
• Model large-scale batch and streaming datasets into reusable, governed data models for reporting use cases.
• Build Databricks pipelines using Delta Lake, Delta Live Tables or Lakeflow aligned to quality and lineage needs.
• Develop Spark workloads using PySpark and Spark SQL for performance, reliability and maintainability.
• Implement streaming ingestion and processing using Spark Structured Streaming and Kafka or similar.
• Partner with business and regulatory stakeholders to translate reporting needs into data products and model definitions.
• Strengthen governance with cataloging, lineage and data quality checks using Unity Catalog or equivalent patterns.
• Contribute to CI/CD for data pipelines, Git-based workflows, testing and release practices.

Job description

We are seeking a Senior Data Engineer (Databricks, Data Modeling). You will model large-scale batch and streaming data into governed Bronze, Silver and Gold layers to support regulatory reporting data products. You will build on Databricks using Spark, Python and SQL, partner with stakeholders on definitions and use AI-assisted tools to speed up delivery, testing and documentation.

Responsibilities

• Design trusted Bronze, Silver and Gold layers using medallion architecture principles
• Model large-scale batch and streaming datasets into reusable, governed data models for reporting use cases
• Build Databricks pipelines using Delta Lake, Delta Live Tables or Lakeflow aligned to quality and lineage needs
• Develop Spark workloads using PySpark and Spark SQL for performance, reliability and maintainability
• Implement streaming ingestion and processing using Spark Structured Streaming and Kafka or similar
• Partner with business and regulatory stakeholders to translate reporting needs into data products and model definitions
• Strengthen governance with cataloging, lineage and data quality checks using Unity Catalog or equivalent patterns
• Contribute to CI/CD for data pipelines, Git-based workflows, testing and release practices

Requirements

• Data modeling background across conceptual, logical and physical models using dimensional, Data Vault or similar approaches
• Databricks experience, including Delta Lake plus governance concepts such as Unity Catalog
• Apache Spark skill sets using PySpark and Spark SQL in production environments
• Streaming data experience using Spark Structured Streaming, Kafka or similar technologies
• Python capability for pipeline development and orchestration patterns
• Advanced SQL skill sets for transformation logic, validation and performance tuning
• Data governance experience covering quality, lineage, controls and well-defined data contracts
• AI-assisted development tooling exposure, with Claude preferred, to accelerate build, testing and documentation

Nice to have

• Regulatory reporting data exposure such as EMIR, MiFIR or ASIC derivative reporting
• Data mesh experience delivering domain-owned data products
• Data Vault 2.0 experience in large-scale enterprise models
• Apache Kafka experience and strong understanding of streaming platform operations