Junior Analytics Engineer

Job Description

Junior Analytics Engineer | Exiger

The Tone:
This is an early career position at Exiger, with a flexible hybrid work model. Exiger builds an AI platform, 1Exiger, to give instant visibility into complex supplier ecosystems. This platform uses proprietary data and AI to identify risk, automate compliance, and create efficiencies for stronger supply chain resilience. This role supports the development of scalable data pipelines and analytics-ready datasets, contributing to impactful data initiatives that make the world safer and more transparent.

The TL;DR
• Role: Early Career
• Location: Hybrid

• Team: Data & Analytics team
• Mission: Support the development of scalable data pipelines and analytics-ready datasets.
• Tech Stack: SQL, Python, dbt Cloud, Snowflake, Apache Spark, Kafka, AWS, S3, Sisense, D3, Ogma, JavaScript, TypeScript, React, VS Code, Cursor, OpenAI tools, Claude, Antigravity

What You’ll Actually Do
• Develop: Support the development and maintenance of semantic data models used for scalable analytics and reporting.
• Build: Help build and improve automated data pipelines for ingesting, transforming, and delivering data.
• Automate: Work with dbt Cloud to support data transformation, testing, documentation, and workflow automation.
• Analyze: Use notebooks and analytical workflows to perform quality control, exploratory analysis, and data validation.
• Translate: Translate business questions into clean, analytics-ready datasets for dashboards and downstream applications.

The Must-Haves
• Background: Bachelor’s degree in Computer Science, Information Systems, Data Analytics, Engineering, Mathematics, or equivalent practical experience. Possess a foundational understanding of data modeling, transformation, and data quality concepts.
• Experience: Approximately 1–3 years of relevant experience, including internships, academic projects, or early-career roles in analytics engineering, data engineering, business intelligence, or software engineering. Hands-on experience working with analytics, pipelines, data modeling, data transformation, or visualization tools.
• Skills: Working knowledge of SQL for querying, transforming, and validating data. Working knowledge of Python for scripting, analysis, and basic pipeline development. Experience using notebooks for analytical workflows, testing, and validation. Ability to review and validate AI-generated code. Strong attention to detail and problem-solving ability.
• Bonus: Exposure to frontend technologies (JavaScript, TypeScript, React), familiarity with AI-assisted development workflows and prompt engineering, experience with cloud and data ecosystem tools (Snowflake, Apache Spark, Kafka, AWS, S3), familiarity with analytics and visualization tools (Sisense, D3, Ogma), experience with developer tools (VS Code, Cursor, OpenAI tools, Claude, Antigravity), or exposure to trade, supply chain, or supply chain risk domains.