Data Analyst
@ Halter

Auckland, Auckland, New Zealand
NZ$80,000
On Site
Full Time
Posted 4 days ago

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XXXXXXXX XXXXXXXXXXX XXXXXX***** @halter.com
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Job Details

About Data Analyst at Halter

At Halter, we are on a mission to revolutionize agricultural practices by equipping farmers with the most advanced data-driven tools. Data Analysts play a vital role in building insights and modern reporting infrastructures that enable smarter, faster decision-making for our Go-To-Market teams.

Key Responsibilities

  • Develop and publish business intelligence reports using Tableau.
  • Collaborate with GTM leaders to define key metrics and insights.
  • Write quality data models in a dbt environment.
  • Automate data pipelines using tools like Airflow and Github.
  • Maintain strong communication with stakeholders across departments.

What You Bring

You should be product-minded and user-driven, with expertise in business intelligence tools, SQL and data modelling, and automation using Python. You are prepared to adapt, collaborate, and contribute to the strategic direction of analytics at Halter.

Additional Perks & Culture

  • Unlimited paid annual leave and wellness days.
  • Generous self-development budget.
  • Family-friendly benefits including extended caregiver leave.
  • Office-first culture in a state-of-the-art Auckland facility.

Key skills/competency

  • Tableau
  • SQL
  • dbt
  • Python
  • Airflow
  • Github
  • Data Visualization
  • Business Intelligence
  • Automation
  • Stakeholder Communication
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How to Get Hired at Halter

🎯 Tips for Getting Hired

  • Research Halter's culture: Study mission, benefits, and office dynamics.
  • Customize your resume: Highlight Tableau, SQL, and data modeling skills.
  • Emphasize technical expertise: Showcase experience with Python, dbt, and CI/CD tools.
  • Prepare for interviews: Practice data storytelling and stakeholder communication.

📝 Interview Preparation Advice

Technical Preparation

Practice constructing Tableau dashboards.
Review SQL queries and data modeling.
Familiarize with dbt and CI/CD tools.
Experiment with Python scripting for automation.

Behavioral Questions

Describe a time you solved data issues.
Explain approach to meeting tight deadlines.
Discuss collaboration with cross-functional teams.
Share experience adapting in dynamic environments.

Frequently Asked Questions