Data Analytics Engineer

About the role

The North American Quality Assurance Department seeks a tech-savvy and creative Digital Innovation Associate to support digital transformation initiatives and drive innovation within the North American Quality Business Unit.

Responsibilities

• Design, develop, test, and deploy quality management applications that support the North American Quality Business Unit.
• Provide application support by troubleshooting minor to moderate issues and escalating complex problems when necessary.
• Build and maintain basic business intelligence dashboards using tools such as Power BI or Tableau to visualize quality metrics including first pass yield (FPY), defect counts, and statistical process control (SPC) charts.
• Ensure data accuracy, consistency, and clarity in dashboards and reports under the guidance of senior team members.
• Support ETL processes by assisting with data extraction, transformation, and loading between quality systems.
• Perform data validation and document workflows, integration steps, and standards to ensure reliable data movement and usage.
• Prepare analytical reports for warranty claims, voice of customer (VOC) trends, and key quality performance indicators (KPIs).
• Maintain clear, up-to-date documentation for dashboards, analytical processes, and reporting procedures.
• Follow established security protocols, audit requirements, and compliance guidelines for all applications and data solutions.
• Aid in monitoring systems for potential security or compliance issues and support incident reporting activities.
• Participate actively in training sessions and learning opportunities to build technical and business knowledge.
• Shadow senior engineers to gain hands-on experience with digital innovation and quality analytics initiatives.
• Contribute to Agile ceremonies such as stand-ups, sprint planning, and retrospectives to support team delivery.
• Collaborate with cross-functional stakeholders to understand quality requirements and translate them into technical solutions.
• Apply strong problem-solving and design thinking approaches to propose improvements in tools, processes, and analytics.
• Manage and prioritize assigned tasks and projects to meet deadlines and deliver high-quality work.

Qualifications

• Bachelor’s degree in Data Analytics Engineering, Computer Science, Data Science, Mathematics, Economics, Engineering, or a related field, or equivalent experience.
• 0–6 years of educational or professional background in analytical or information analysis roles, or at least 3 months of co-op experience in a similar area.
• Strong problem-solving and analytical skills, including the use of design thinking methodologies.
• Strong communication skills, including written, verbal, and visual communication.
• Ability to prioritize tasks effectively, manage workload, and make sound decisions.
• Proficiency in query languages such as SQL for data retrieval and manipulation.
• Proficiency in data analysis using tools such as Python and common data science libraries (for example, NumPy).
• Experience using Microsoft products, including Excel functions such as pivot tables and VLOOKUP, and PowerPoint for presentations.
• Experience with data analysis and interpretation of quality or business metrics.
• Excellent attention to detail when working with data, dashboards, and documentation.

Additional Skills & Qualifications

• Experience with business intelligence tools such as Power BI, Qlik Sense, or QlikView.
• Experience with additional data visualization platforms such as Tableau.
• Experience using common data science toolkits such as R.
• Knowledge of data gathering, cleaning, and transforming techniques.
• Applied statistics skills, including understanding distributions, statistical testing, regression, and related methods.
• Exposure to modern software or analytics frameworks and agile development practices.
• Familiarity with quality metrics such as first pass yield (FPY), defect counts, and SPC charts.
• Interest in digital innovation and continuous improvement within a quality-focused environment.
• Eagerness to learn from mentors and contribute to a collaborative engineering team.