Analytics Engineer

Role Overview

We are seeking a world-class, self-directed Analytics Engineer to transform complex engineering and manufacturing data into trusted, decision-ready analytics. You will design scalable data models, develop reliable transformation pipelines, and create intuitive dashboards and analytical solutions that support product development, manufacturing, testing, quality, and operational improvement.

What You Will Do

Design, build, and maintain reliable analytics datasets, semantic models, and data products for engineering, manufacturing, testing, quality, and business use cases. Develop and optimize SQL- and Python-based data transformations that convert raw data into consistent, documented, and reusable analytical models.

Why It Might Be a Fit

Partner with business stakeholders, engineers, analysts, and data engineers to translate requirements into scalable analytics solutions and clear success criteria; document business logic, data lineage, model assumptions, and solution design; and share knowledge with global teams.

Requirements

• Bachelor’s or master’s degree in computer science, Data Science, Engineering, Information Systems, Statistics, or related technical field.
• 2-4 years of total experience, including at least 2 years of analytics engineering, business intelligence, data engineering, or a closely related role.
• Working knowledge of ETL/ELT patterns and data pipeline fundamentals.
• Strong SQL skills, including complex queries, joins, aggregations, window functions, query optimization, and the development of reusable data models.
• Practical experience using Python for data preparation, analysis, automation, and validation, with libraries such as Pandas and NumPy.
• Experience with source control tools such as Git and work-management or bug-tracking tools such as JIRA.
• Ability to define and validate business metrics, analyze trends, test assumptions, and communicate findings clearly.
• Strong analytical, problem-solving, documentation, and stakeholder collaboration skills, including the ability to explain complex technical concepts to global teams.