Senior QuickSight Analytics Engineer

About the role

Supports the design, development, and deployment of scalable data solutions that enable business insights and operational efficiency. This role works across the data lifecycle to build pipelines, structure data assets, and improve data quality in support of business and client needs. The ideal candidate brings hands-on engineering experience, strong technical execution, and the ability to work across multiple priorities in a fast-paced environment. This is a hands-on role requiring strong Amazon QuickSight experience, Python expertise, analytical problem-solving skills, and the ability to work across the full business intelligence delivery lifecycle.

Responsibilities

• Analyze the client's existing data environment, reporting processes, and Python code to understand current capabilities, constraints, and opportunities for improvement.
• Gather and translate business and technical requirements into scalable dashboards, reports, data models, and reporting solutions.
• Design, build, and implement interactive dashboards and visualizations using Amazon QuickSight.
• Develop reporting logic, calculations, metrics, filters, parameters, and business rules to support accurate and actionable insights.
• Use Python to analyze client data, evaluate existing code, support data preparation, and automate or enhance reporting processes where appropriate.
• Integrate, transform, and model data from multiple sources to create reliable datasets for analytics and reporting.

Skills

• Ability to work independently and collaborate as part of a team
• Effective written and verbal communication skills
• Meticulous attention to detail and quality of work product
• Ability to build and sustain professional relationships
• Ability to lead projects or workstreams
• Ability to manage and prioritize multiple tasks in a fast-paced and dynamic environment
• Strong interpersonal skills and professional demeanor
• Ability to meet deadlines
• Ability to provide clear guidance to others

The team

Our Data Engineering team helps build and modernize data platforms that support analytics, reporting, and business decision-making across complex environments. The team works with stakeholders across technology and business functions to develop scalable, secure, and maintainable data solutions.

Qualifications

Required:

• Bachelor's degree in Computer Science, Information Systems, Engineering, or a related field
• 5+ years of experience in Python, including the ability to analyze the client's existing environment, review and understand Python code, support data preparation, and develop automation or reporting enhancements
• 2+ years of experience designing, developing, and implementing interactive dashboards and visualizations using Amazon QuickSight
• 2+ years of experience gathering, documenting, and translating business and technical requirements into dashboards, reports, data models, and scalable analytics solutions
• Ability to travel 10%, on average, based on the work you do and the clients and industries/sectors you serve
• Must be legally authorized to work in the United States without the need for employer sponsorship, now or at any time in the future

Preferred:

• Master's degree in Computer Science, Information Systems, Engineering, or a related field
• Experience developing reporting logic, calculated fields, metrics, filters, parameters, controls, and business rules in support of accurate and actionable reporting
• Experience integrating, transforming, and modeling data from multiple sources to create reliable, reusable datasets for analytics and reporting
• Ability to assess existing reporting processes and technical solutions, identify gaps and constraints, and recommend practical improvements
• Willingness and ability to support a heavy build and implementation effort followed by ongoing operations, maintenance, and enhancement activities

Pay

For individuals assigned and/or hired to work in Maryland, a reasonable estimate of the current compensation range is $107,700 to $179,500. You may also be eligible to participate in a discretionary annual incentive program, subject to the rules governing the program, whereby an award, if any, depends on various factors, including, without limitation, individual and organizational performance.