Analytics Engineer, Employee Technology Support

Details

As an integral member of the Employee Technology Support team, you will build the data foundation that improves support operations through engineering, automation, and scalable analytics. You will design pipelines, data models, and reporting platforms that transform raw operational data into trusted, decision-ready information across the organization.

You will partner with Employee Technology Support, Engineering, Product, and business stakeholders to understand operational challenges and translate them into robust, scalable data solutions. Your work will support analysis of complex support datasets, identify trends and root causes, improve operational efficiency and employee experience, and inform strategic decision-making.

Responsibilities

• Partner with Employee Technology Support teams to understand operational challenges and design scalable data solutions.
• Build and maintain data models, ETL pipelines, and automated data flows using SQL, Python, and Qlik Sense.
• Develop dashboards, KPIs, and operational metrics covering service performance, workload, employee experience, and operational efficiency.
• Architect and optimize the data layer powering operational reporting, ensuring it is performant, well-documented, and reusable.
• Perform data profiling, trend analysis, and root cause investigations to identify process improvement opportunities.
• Design and implement automated data validation and monitoring to improve data quality, consistency, and reliability.
• Modernize legacy reporting and analytical workflows through automation and scalable solution design.
• Translate business requirements into visualizations and actionable insights for technical and non-technical stakeholders.
• Collaborate with Engineering and Product teams to improve data architecture, reporting capabilities, and system scalability.
• Establish best practices for data modeling, pipeline design, reporting standards, and analytics development.
• Communicate project progress, findings, and recommendations to stakeholders and senior leadership.
• Own data solutions throughout their lifecycle, ensuring they remain accurate, reliable, and aligned with evolving business needs.

Requirements

• Bachelor's degree or higher in Computer Science, Mathematics, Statistics, Information Systems, Data Analytics, or a related STEM discipline.
• At least 3 years of experience building data engineering, business intelligence, or analytics solutions.
• Advanced SQL skills and experience working with large relational datasets.
• Strong Python development experience for data engineering, automation, and ETL workflows.
• Experience building scalable data models, pipelines, reporting solutions, and dashboard applications.
• Experience with Qlik Sense, Tableau, Power BI, or similar visualization platforms.
• Strong understanding of data quality, validation techniques, and operational reporting.
• Experience performing root cause analysis and translating findings into business recommendations.
• Ability to manage multiple projects, independently prioritize work, and deliver high-quality solutions.
• Excellent communication skills, with the ability to explain complex technical concepts to business stakeholders.

Preferred Qualifications

• Advanced Qlik Sense dashboard development and KPI framework design.
• Experience with IT Service Management platforms, ServiceNow, SDSK, or enterprise support data.
• Experience designing enterprise reporting frameworks and operational scorecards.
• Knowledge of data governance, metadata management, and reporting standards.
• Experience automating manual reporting and data processes using Python.
• Experience supporting operational analytics within Employee Technology or enterprise IT organizations.
• Demonstrated ability to improve operational efficiency through automation, engineering, and scalable data solutions.

Compensation and Benefits

The salary range is $110,000–$130,000 USD annually, plus benefits and bonus. Benefits may include merit increases, incentive compensation for exempt roles, paid holidays, paid time off, medical, dental, vision, short- and long-term disability benefits, a 401(k) match, life insurance, and wellness programs. Actual compensation may vary based on geographic location, work experience, market conditions, education, training, and skill level.