Data Analytics Specialist

The Specialist – Data Analytics and Engineering is responsible for translating business needs into trusted data, actionable insights, scalable reporting solutions, and self-service analytics while supporting data quality, governance, and continuous improvement initiatives.

Key Responsibilities

• Independently lead stakeholder meetings, requirements-gathering sessions, dashboard reviews, and analytical working sessions.
• Partner with business leaders and process owners to understand operational challenges, reporting requirements, and decision-making needs.
• Translate business questions into clearly defined metrics, KPIs, business rules, analytical frameworks, and actionable recommendations.
• Analyze enterprise data to identify trends, performance gaps, operational risks, utilization opportunities, cost drivers, and business insights.
• Design, develop, and maintain dashboards, scorecards, and self-service analytics solutions using Amazon QuickSight and other business intelligence platforms.
• Create governed analytical datasets, reusable query logic, and business-friendly definitions for enterprise measures and dimensions.
• Write and maintain advanced SQL queries for reporting, data validation, reconciliation, and analytics initiatives.
• Profile, validate, and assess source data for completeness, accuracy, consistency, timeliness, and suitability for reporting purposes.
• Troubleshoot reporting discrepancies and determine root causes across source systems, transformations, metric definitions, security models, and visualizations.
• Collaborate with data engineering teams to define source-to-target requirements, data refresh schedules, quality controls, and production support processes.
• Contribute to data governance, metadata management, business glossary, cataloging, and data lineage initiatives.
• Identify opportunities to automate manual reporting processes and convert recurring requests into scalable, governed, and self-service analytics solutions.
• Leverage AI-assisted analytics and generative BI capabilities to improve data discovery, accelerate analysis, and enhance the reporting experience.
• Validate AI-generated insights and ensure analytical outputs are grounded in trusted enterprise data.
• Participate in the evaluation, testing, and adoption of new analytical tools, semantic models, and visualization technologies.

Required Qualifications

• Bachelor’s degree in Computer Science, Information Systems, Business Analytics, Statistics, Mathematics, Finance, or a related field (or equivalent professional experience).
• 4+ years of experience in business intelligence, data analytics, reporting, or a related discipline.
• Strong SQL expertise, including joins, common table expressions (CTEs), window functions, aggregations, date logic, and data validation techniques.
• Hands-on experience developing production dashboards and self-service reporting solutions using Amazon QuickSight, Tableau, Power BI, Looker, or similar BI platforms.
• Proven ability to translate business requirements into metrics, analytical datasets, dashboards, and actionable business insights.
• Strong understanding of dimensional modeling, data relationships, reporting grain, aggregation behavior, and visualization best practices.
• Experience reconciling analytical outputs with source systems, business controls, and reporting standards.
• Professional fluency in written and spoken English with the ability to independently facilitate stakeholder discussions and present complex information clearly.
• Strong analytical, problem-solving, communication, prioritization, and stakeholder management skills.
• Demonstrated ability to work independently and deliver high-quality work with minimal supervision.

Preferred Qualifications

• Experience working with Snowflake or other modern cloud-based data platforms.
• Advanced experience with Amazon QuickSight, including row-level security, calculated fields, parameters, embedded analytics, and performance optimization.
• Familiarity with AWS services such as Amazon S3, Athena, and Lambda.
• Experience supporting enterprise platforms such as Oracle Fusion, Salesforce, ServiceNow, or similar ERP, CRM, HCM, and ITSM solutions.
• Experience working within managed services, consulting, technology services, or customer-facing operational environments.
• Background supporting financial, workforce, utilization, service management, customer, or operational analytics.
• Knowledge of data governance, metadata management, business glossary development, and data lineage practices.

Work Set up: Remote, Night Shift (US Shift)