Databricks Data Engineer – SQL/ETL Migration Lead

Talent

City of Melbourne

On-site

AUD 140,000 - 200,000

Full time

41 hours ago
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Benefits offered by this job

Contract until end of April 2027
Government Agency

Job summary

Talent in Melbourne is seeking an experienced Data Engineer to lead a major migration project from SQL Server to Databricks on Azure. You will design and implement scalable data pipelines, notebooks, and ETL workflows using SQL and Python, and ensure data quality across the migration.

The role requires 10+ years in data engineering, strong Databricks experience, advanced SQL skills, and a track record migrating data warehouses to modern platforms.

Qualifications

  • 10+ years of hands-on experience as a Data Engineer.
  • Advanced SQL skills with proven experience working with data warehouses.
  • Strong Python development skills for building data pipelines.
  • Proven experience migrating SQL Server data warehouses, ETL processes or data platforms to modern data platforms.

Responsibilities

  • Lead the migration of an existing SQL Server data warehouse and ETL environment into Databricks and Azure.
  • Translate existing SQL warehouse structures, queries, stored procedures and ETL logic into scalable Databricks solutions.
  • Build and develop Databricks notebooks, data pipelines and workflows using SQL and Python.
  • Analyse existing SQL data and processes, identify migration requirements.
  • Support data validation, testing, optimisation and troubleshooting throughout the migration.

Tools

Databricks
Azure
Python
SQL

Job description

Talent in Melbourne is seeking an experienced Data Engineer to lead a major migration project from SQL Server to Databricks on Azure. You will design and implement scalable data pipelines, notebooks, and ETL workflows using SQL and Python, and ensure data quality across the migration.

The role requires 10+ years in data engineering, strong Databricks experience, advanced SQL skills, and a track record migrating data warehouses to modern platforms.

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