The Analytics Engineer is a domain-aware modeler who turns business complexity into reusable, trusted analytical data products and data models. This role partners with business stakeholders, analysts, data scientists, product teams, and Data Platform teams to design governed analytical models, define metrics, document assumptions, and support reliable downstream consumption across reporting, analytics, and AI-enabled business use cases.

Education

• Bachelor's degree in Computer Science, Engineering, Information Systems, Data Analytics, Business, or related field preferred.
• Equivalent years of relevant work experience may be considered.

Experience

• 4+ years of experience in analytics engineering, business intelligence engineering, data modeling, data products, cloud data platforms, or related fields.
• Experience designing reusable analytical models, governed metrics, semantic layers, or curated data products.
• Experience supporting analytics, reporting, business intelligence, or AI-enabling use cases.
• Retail, ecommerce, merchandising, pricing, supply chain, customer, marketing, finance, or adjacent industry experience preferred.

Skills

• Strong understanding of analytics engineering, semantic modeling, governed metrics, and reusable data product design.
• Hands-on experience with data build tools (dbt) or similar transformation frameworks, advanced SQL, Git-based code management, testing practices, documentation standards, and peer review workflows.
• Ability to translate analytical intent into clear model designs, assumptions, validation rules, and business-ready data structures.
• Experience collaborating with analysts, data scientists, product teams, and business stakeholders to support trusted downstream consumption.
• Demonstrated ability to leverage approved AI-enabled productivity tools to improve documentation, analysis, testing, and delivery of analytics solutions.
• Capability to deliver analytics to stakeholders through business intelligence and visualization tools such as Power BI, Looker, MicroStrategy, Tableau, or similar platforms.
• Strong communication, problem-solving, and prioritization skills across technical and business audiences.
• Ability to navigate ambiguity and create clarity in business logic, data definitions, and analytical requirements.
• Commitment to disciplined documentation, testing, validation, peer review, semantic consistency, and measurable business value.
• Ability to balance business outcomes with technical standards, model quality, and governance expectations.

Responsibilities

• Partner with business stakeholders, analysts, and team members to understand analytical requirements, clarify business logic, and contribute to scalable analytical solutions.
• Support adoption after delivery by gathering feedback, monitoring usage, documenting issues, and identifying opportunities to improve data product usability and business value.
• Design and build reusable productized analytical models and metrics.
• Define and maintain semantic consistency across analytical products.
• Support production readiness and operational reliability of analytical data products by contributing to monitoring, runbooks, issue triage, root cause analysis, stakeholder communication, and continuous improvement of data quality and freshness.
• Collaborate with analysts, data scientists, and product teams to support downstream consumption.
• Create, enable, or support stakeholder-facing analytics experiences using approved BI tools, ensuring insights are accessible, trusted, and aligned to business decision needs.
• Leverage AI tools responsibly to improve productivity, summarize complex information, draft documentation, validate logic, and streamline repetitive analytical workflows while maintaining quality, accuracy, and governance standards.
• Document model designs, assumptions, and tradeoffs clearly.
• Consolidate and retire duplicate or conflicting analytical logic.
• Promote reuse and standardized modeling practices across pods.
• Participate in testing, validation, and quality reviews.
• Support company initiatives and perform additional duties as assigned.

About INSPYR Solutions
Technology is our focus and quality is our commitment. As a national expert in delivering flexible technology and talent solutions, we strategically align industry and technical expertise with our clients' business objectives and cultural needs. Our solutions are tailored to each client and include a wide variety of professional services, project, and talent solutions. By always striving for excellence and focusing on the human aspect of our business, we work seamlessly with our talent and clients to match the right solutions to the right opportunities. Learn more about us at inspyrsolutions.com.

INSPYR Solutions provides Equal Employment Opportunities (EEO) to all employees and applicants for employment without regard to race, color, religion, sex, national origin, age, disability, genetics, or any other protected status. INSPYR Solutions complies with all applicable laws governing nondiscrimination in employment in every location in which the company has facilities. Applicants requiring reasonable accommodation during the application or interview process should contact HR@inspyrsolutions.com for assistance.

Information collected and processed through your application with INSPYR Solutions (including any job applications you choose to submit) is subject to INSPYR Solutions' Privacy Policy and INSPYR Solutions' AI and Automated Employment Decision Tool Policy: https://www.inspyrsolutions.com/policies/. By submitting an application, you are consenting to being contacted by INSPYR Solutions through phone, email, or text.

26-160254