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Senior Data Engineer

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Hybrid

Senior Data Engineer

Software At Scale

Senior Data Engineer

Skills

SQL QueriesData EngineeringPythonData ScienceSnowflakeDatabricksMachine LearningAIdbtApache Airflow

1 month ago

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Important information


Contract type:

Freelance / Contract

Location:

Sydney NSW, Australia

Work mode:

Hybrid

Published on:

15 September 2026

What they need


Our 'black belt' specialists are leaders in their domains: digital champions, delivery-focused experts, top-tier security professionals, AI thought leaders, and engineering best practice advocates.

As 1 of Australia’s fastest-growing software businesses, Software at Scale delivers cutting-edge technology solutions that power mission-critical platforms. We solve complex engineering challenges at scale, driving quality, performance, and resilience through the strength of our people.

The Role & The Challenge

We are seeking a highly proactive, commercially minded AI-Empowered Senior Data AI Engineer to play a key role in designing and scaling data foundations that directly power advanced artificial intelligence systems.

This is not a traditional pipeline-building role. You will operate within complex enterprise environments, taking the initiative to actively source required data assets, build robust enterprise data models that make sound commercial sense, and bridge the gap between raw data engineering and data science.

You will step into a high-trust, fully empowered environment where you are expected to take complete technical ownership, align data architectures with strategic business priorities, and leverage statistical rigour to solve complex enterprise problems.

AI Access & Claude Code: We actively encourage our engineers to solve problems using AI. You will have full access to enterprise GenAI tooling, including Claude Code, to accelerate data transformations, pipeline refactoring, and code generation.

Key Responsibilities

  • Proactive Asset Discovery: Act as a technical catalyst within the enterprise. Autonomously source, evaluate, and integrate required data asset sources across complex business domains, ensuring high data readiness for AI initiatives.
  • Commercial Enterprise Modelling: Design and build high-impact enterprise data models that align directly with business priorities and drive measurable commercial value.
  • Modern Data Stack Execution: Architect and optimise large-scale data platforms using Snowflake (strongly preferred) or Databricks (highly preferred), ensuring high performance, scalability, and cost efficiency.
  • Statistical & Analytical Rigour: Apply a deep understanding of statistics and data patterns to validate data integrity, shape feature engineering, and support advanced machine learning workloads.
  • AI-Driven Engineering: Extensively utilise Claude Code and modern agentic tools to accelerate pipeline refactoring, test automation, and code generation.
  • Pipeline Architecture & Orchestration: Build and optimise robust data pipelines, ELT frameworks (using tools like dbt), and orchestration layers (such as Airflow) to feed analytical and AI systems seamlessly.
  • Data Governance & Quality: Implement rigorous data quality controls, governance standards, and operational monitoring across all data products.

What You Bring

  • Commercial & Strategic Acumen: A sharp understanding of business priorities. You don't just move data from point A to point B; you design models that make strict commercial sense and solve real business problems.
  • Data Platform Mastery: Deep, hands-on commercial expertise with industry-leading data platforms—Snowflake is strongly preferred, and proficiency with Databricks is highly desirable.
  • Statistical & Analytical Foundation: A solid grasp of applied statistics, enabling you to reason about data distributions, feature relevance, and data quality metrics for AI use cases.
  • Proactive Enterprise Navigation: Proven experience operating within large, complex enterprise environments where you independently hunt down data sources, untangle ambiguity, and drive alignment with stakeholders.
  • Senior-Level Engineering: Advanced SQL and Python skills, alongside strong experience with modern ELT frameworks (dbt) and workflow orchestration (Airflow).
  • AI Fluency: Practical experience using Claude Code and AI tooling to accelerate data engineering workflows.

What We Offer

  • The chance to work for 1 of Australia's fastest-growing and most innovative software businesses.
  • Full access to cutting-edge AI tooling, including Claude Code.
  • Meaningful, hands-on data and AI engineering work on mission-critical enterprise platforms.
  • Clear growth pathways from Senior to Staff and beyond.
  • A low-ceremony, delivery-focused environment that values engineers who own outcomes.
  • Competitive remuneration and benefits.

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