Senior Data Engineer: Hands-on Databricks & Client Impact

ICM Asia Pacific; City of Melbourne; On-site; AUD 140,000 - 180,000; Full time

Job summary

Adaptiv in Melbourne or Brisbane seeks a senior Data Engineer to design, build and deliver modern data platforms and engineering solutions with a focus on Databricks and cloud‑based architectures.

You’ll work across client engagements, collaborating with architects, consultants and engineering teams to translate business requirements into scalable, production‑ready data solutions. The role blends hands‑on coding with mentoring, in a growing Australian Data Practice.

Qualifications

• 6+ years' professional experience across Data Engineering, Data Platforms or a closely related discipline.
• Strong hands‑on experience delivering production Data Engineering solutions using Databricks.
• Practical experience with Databricks notebooks, workflows, Lakehouse architectures and modern data pipeline development.
• Strong Python, PySpark and SQL capability.
• Experience designing and developing ETL/ELT pipelines and complex data transformations.
• A good understanding of modern data architecture patterns, including Medallion architecture and scalable Lakehouse design.
• Strong data modelling knowledge, including dimensional, Star and Snowflake modelling approaches.
• Experience with cloud data platforms, ideally within Microsoft Azure or another major cloud ecosystem.
• Experience applying DevOps and software engineering practices including version control, CI/CD and automated deployment.
• Experience implementing testing, data quality and validation practices within production data environments.
• Familiarity with analytics and data consumption technologies such as Power BI or similar platforms.

Responsibilities

• Designing, building and optimising modern data pipelines across data lakes, lakehouses and data warehouses.
• Delivering production‑grade solutions using Databricks and associated cloud data technologies.
• Developing data transformations and engineering solutions using Python, PySpark and SQL.
• Working with Databricks notebooks, workflows and Lakeflow Declarative Pipelines (formerly Delta Live Tables).
• Applying modern data architecture patterns including Lakehouse and Medallion architectures.
• Designing and implementing robust data models for analytics, reporting and downstream data consumption.
• Applying software engineering and DevOps practices including Git, CI/CD, automated deployment and environment management.
• Implementing testing, data validation, monitoring and performance optimisation to ensure reliable production data solutions.
• Working directly with clients to understand requirements and translate business needs into pragmatic technical solutions.
• Leading technical discussions and communicating engineering concepts to both technical and non-technical stakeholders.
• Collaborating with architects and other consultants on solution design, estimation, scoping and delivery planning.
• Identifying delivery risks, communicating progress and helping resolve technical blockers.
• Conducting peer reviews and supporting high standards across code, documentation and engineering practices.
• Mentoring junior and intermediate engineers and contributing to knowledge sharing across the Data Practice.
• Helping improve Adaptiv's reusable frameworks, delivery patterns, templates and engineering standards.
• Staying current with developments across Databricks, cloud data platforms, AI/ML and the broader modern data ecosystem.

Skills

Databricks

Python

PySpark

SQL

ETL/ELT

Lakehouse

Medallion architecture

Cloud data platforms

DevOps practices

Power BI

client‑facing delivery

Tools

Azure

Databricks notebooks

Lakeflow

Job description

Adaptiv in Melbourne or Brisbane seeks a senior Data Engineer to design, build and deliver modern data platforms and engineering solutions with a focus on Databricks and cloud‑based architectures.

You’ll work across client engagements, collaborating with architects, consultants and engineering teams to translate business requirements into scalable, production‑ready data solutions. The role blends hands‑on coding with mentoring, in a growing Australian Data Practice.