What To Expect
The APAC Industrial Energy team is looking for a technical Data Analyst to join our Business Operations team. In this role, you will work across the entire project lifecycle, connecting data streams from the initial bid phase through to contracting and final deployment for our Megapack and Autobidder products.

We are seeking a data all-rounder capable of delivering end-to-end data solutions. You will not just report on the business; you will build the infrastructure that helps run it. From developing data pipelines (ETL) to building interactive dashboards or Python-based applications and automating manual workflows, you will own the full lifecycle of your data products. Key stakeholders include Sales, Sales Engineering, Sales Operations, Logistics, Project Deployment, and senior leadership.

What You'll Do

Process Automation: Proactively identify opportunities to replace manual, repetitive tasks with automated Python scripts and workflows, significantly reducing administrative overhead for Sales and Operations teams.

Internal Tooling & Application Development: Design, build, and deploy scalable internal web applications to support different areas of the business.

Scalable Architecture: Develop modular Python tools and libraries that standardise development practices, creating a foundation that allows other analysts to easily contribute to the team’s application ecosystem.

Lifecycle Data Integration: Connect disparate data sources to create a unified view of the project journey, ensuring seamless data flow across many departments.

Data Engineering: Maintain robust SQL pipelines and ETL processes to ensure high data availability and accuracy for business-critical reporting.

Business Intelligence: Design intuitive dashboards (Power BI/Tableau) that translate complex datasets into actionable insights for diverse stakeholders.

What You'll Bring

Bachelor’s degree in a quantitative or technical field (e.g., Data Science, Engineering, Mathematics, Physics, Statistics)

3–5 years of relevant experience in data analytics, data engineering, or business intelligence

Advanced proficiency in Python for building production-grade automation scripts and Streamlit-based web applications.

Expertise in writing complex SQL queries, optimising database performance, and designing data models to unify datasets across the project lifecycle.

Experience building interactive dashboards in Power BI or Tableau.

Demonstrated ability of delivering a project from concept to deployment, including data ingestion, processing, and visualization.

Strong written and verbal communication skills to articulate technical concepts to non-technical stakeholders and collaborate with cross-functional teams (Sales, Engineering, Logistics).

Energy industry experience highly regarded

, Tesla