トレンド企業

Tesla
Tesla

Accelerating the world's transition to sustainable energy.

Data Analyst, Industrial Energy Business Operations

職種データ分析
経験ミドル級
勤務地Melbourne, Victoria, Australia
勤務オンサイト
雇用正社員
掲載今日
応募する

必須スキル

Python

SQL

Tableau

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

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    Teslaについて

    Tesla

    Tesla

    Public

    A financial leasing taxi company that provides vehicles to customers

    140,000+

    従業員数

    Ciudad De Panamá

    本社所在地

    $800B

    企業価値

    レビュー

    10件のレビュー

    3.8

    10件のレビュー

    ワークライフバランス

    2.3

    報酬

    4.0

    企業文化

    3.2

    キャリア

    4.1

    経営陣

    2.8

    65%

    知人への推奨率

    良い点

    Innovative projects and cutting-edge technology

    Great team and supportive colleagues

    Good compensation and benefits

    改善点

    Long hours and poor work-life balance

    High pressure and tight deadlines

    Management issues and high expectations

    給与レンジ

    1,403件のデータ

    Junior/L3

    Mid/L4

    Junior/L3 · Associate Analyst

    2件のレポート

    $94,875

    年収総額

    基本給

    $82,500

    ストック

    -

    ボーナス

    -

    $92,000

    $97,750

    面接レビュー

    レビュー4件

    難易度

    3.5

    / 5

    期間

    14-28週間

    体験

    ポジティブ 0%

    普通 75%

    ネガティブ 25%

    面接プロセス

    1

    Application Review

    2

    Recruiter Screen

    3

    Technical Phone Screen

    4

    Take-home Assignment

    5

    Panel Interview

    6

    Offer

    よくある質問

    Coding/Algorithm

    Technical Knowledge

    Behavioral/STAR

    System Design

    Machine Learning Concepts