Senior Data Engineer – Microsoft Fabric (Snowflake or Databricks)

MIP; Council of the City of Sydney; Hybrid; AUD 130,000 - 160,000; Full time

Benefits offered by this job

Flexible hybrid work

Supportive culture

Job summary

A leading data consultancy is seeking a Senior Data Engineer to lead project squads and manage data projects. This role requires significant hands-on expertise with Microsoft Fabric, along with at least one of Snowflake or Databricks. Candidates must have 5–10+ years in data engineering and strong communication skills to connect effectively with both technical teams and stakeholders. The position offers flexible hybrid work arrangements and the opportunity to work with marquee Australian clients.

Qualifications

• 5–10+ years in data engineering in consulting or complex enterprise environments.
• Proven experience leading project workstreams and small teams.
• Strong hands-on experience with Microsoft Fabric.

Responsibilities

• Lead delivery for a small data squad and manage project scope.
• Design and build scalable data models and pipelines on Microsoft Fabric.
• Ensure security and governance for data projects.

Skills

Microsoft Fabric

SQL

Python

Data modeling

CI/CD

Stakeholder communication

Tools

Snowflake

Databricks

Azure DevOps

Job description

Senior Data Engineer – Microsoft Fabric (Snowflake or Databricks)

We’re growing our data engineering practice and need a Senior Data Engineer who can own delivery as well as build. This person will lead project squads – running stand-ups, managing scope, keeping RAID up to date, and reporting to stakeholders – while also being hands‑on in Microsoft Fabric. Snowflake or Databricks is a nice‑to‑have. This role is for someone who can keep a data project on track, on budget, and visible to the business.

Note: the role requires the candidate to be Sydney-based, able to work a minimum of 4 days per week in the office, and to have full working rights in Australia.

Core Responsibilities:

• Lead delivery for a small data squad: plan iterations, run ceremonies, manage scope and risks, maintain RAID, and provide regular status updates to stakeholders.
• Work with architects/consultants on solution design, estimation and SoWs; demo increments to business/exec users.
• Design and build scalable data models and pipelines on Microsoft Fabric (OneLake, Lakehouse, Pipelines, Dataflows Gen2, Semantic Models) and at least one of Snowflake or Databricks.
• Implement notebook/dbt transformations (tests, docs, exposures) and enforce best practices (modularity, lineage, CI checks).
• Set up CI/CD for data projects (Git, Azure DevOps or GitHub Actions).
• Optimise performance and cost (Fabric capacities, pipeline runtimes; Snowflake warehouses or Databricks clusters).
• Ensure security and governance (RLS/column security, PII handling, Purview/lineage).
• Keep documentation, patterns, and reusable components current for the practice.

Required Qualifications:

• 5–10+ years in data engineering in consulting or complex enterprise environments.
• Sydney-based and able to work a minimum of 4 days per week in the office.
• Must have full working rights in Australia.
• Proven experience leading project workstreams/small teams – sprint planning, stakeholder comms, status reporting, risk management.
• Strong hands‑on with Microsoft Fabric and at least one of Snowflake or Databricks.
• Solid CI/CD for data, strong SQL and Python, familiarity with Parquet/Delta/Iceberg.
• Excellent communication skills – able to talk to both engineers and business.

Nice to have

• AWS data stack, Terraform/Bicep, AWS DMS.
• Data governance & lineage (Purview), RLS/CLS, masking.
• Testing/observability tools (Great Expectations, Soda, Monte Carlo/Revefi).
• Power BI/Tableau, DAX/Tabular.
• Formal PM experience or having acted as a project lead on data deliveries.

What you’ll get in return:

Work with marquee Australian clients on modern stacks (Snowflake, Fabric, Databricks). Real ownership with support from senior architects and practice leads. Flexible hybrid work and a supportive culture.