Data Engineer

About the Company

Working via 10xlabs, a leading technology consultancy, you will collaborate directly with an industry-defining provider of AI-driven digital twin and analytics platforms for the energy sector. By generating real-time grid intelligence, the platform empowers energy distribution networks and utilities to gain unprecedented visibility into asset utilization, capacity constraints, grid connections, and distributed energy resources (DER).

About the Opportunity

As a Data Engineer, you will step into a vital, dynamic engineering environment working directly on core data pipelines and analytics infrastructure for energy grid intelligence solutions.

This is a hands-on technical role where you will build, maintain, and optimize data transformation workflows and orchestration frameworks. The work environment is fluid and fast-paced, so we look for flexible, proactive data engineers who can confidently manage changing priorities, collaborate effectively across teams, and execute using modern cloud-data tooling. Crucially, this position requires working US-overlap hours (05:00 – 13:00 AEST) to align seamlessly with international deployment schedules and global stakeholders.

Your Impact and Responsibilities

• Data Pipeline Engineering: Build and maintain scalable, robust ETL/ELT pipelines using dbt, Databricks, Spark/PySpark, and Python to process complex grid telemetry and asset data.
• Declarative Configuration Management: Utilize YAML configurations to manage pipeline behaviors, schema definitions, and automated workflow parameters.
• Orchestration & Workflow Automation: Implement and manage pipeline workflows using Dagster to ensure dependable, monitored, and resilient data processing loops.
• Data Transformation & Profiling: Process time-series, asset, and spatial dataset structures using SQL, Pandas, and PySpark to convert raw utility feeds into clean, analytics-ready formats.
• CI/CD & Engineering Practices: Maintain rigorous quality standards across codebases using GitHub, automated testing, continuous integration/continuous delivery (CI/CD) pipelines, and task management in Linear.
• Cross-Team Collaboration: Work adaptively with internal engineering, analytics, and consultancy teams in a fluid environment to support evolving client requirements and product deployments.

Required Experience & Qualifications

• Core Experience: Proven track record as a Mid-Level Data Engineer (or strong experience in an adjacent, highly technical data/software engineering role).
• Technical Stack: Strong commercial proficiency with dbt, Databricks, Python, SQL, and YAML-based configurations.
• Data Processing Tools: Hands-on experience with Spark / PySpark and Pandas for large-scale data manipulation and transformations.
• Orchestration & DevOps: Familiarity with modern orchestration tools (ideally Dagster) alongside GitHub, Linear, and general CI/CD integration processes.
• Work Schedule Flexibility: Ability and willingness to work across different time zones, mainly early mornings AEST
• Soft Skills & Adaptability: Proactive, self-motivated mindset with strong communication skills and high comfort navigating fluid scheduling, shifting priorities, and dynamic workloads.

Preferred Skills

• Domain Knowledge: Exposure to electricity utility data frameworks, including AMI/smart meter data, GIS network models, SCADA telemetry, or DER/interconnection records.
• Advanced Data Architectures: Experience working with high-volume time-series data or real-time event-streaming architectures.

What You’ll Gain

• A high-impact role directly shaping the data pipelines that power real-time AI solutions for global energy networks.
• Exposure to an advanced, modern data stack leveraging Databricks, Spark, Dagster, and dbt.
• Flexible work arrangements combining remote options with a Sydney-based office culture.

WHAT’S NEXT? This role is being recruited by NTP Talent. All applicants will receive a response. The easiest way to register your interest is to apply using the link.

If you’d like to have a chat before applying, please contact Craig Bird on 0409 321 995 or [email protected].