Top Data & Analytics Jobs in Boise, ID

Design and manage financial systems for accurate cashback calculations, build and maintain reconciliation processes, ensure data integrity for yield-bearing instruments, collaborate with compliance, and partner with cross-functional teams to improve financial system efficiency.

Build and maintain business dashboards and standardized reporting processes; ensure data accuracy, governance, and consistency across systems; clean and structure data; maintain data pipelines; and improve workflow automations across sales, marketing, and operations. The role translates complex data into actionable insights, documents processes, identifies inefficiencies, and partners with stakeholders on scalable reporting and automation solutions.

Lead enterprise data architecture strategy and implementation across cloud data platforms, integration ecosystems, analytics, AI, and operational systems. Design scalable lakehouse or warehouse architectures, canonical data models, governance frameworks, data products, and secure healthcare data integrations. Partner with engineering, product, analytics, AI, security, and executive stakeholders while mentoring technical teams. The role requires deep expertise in modern data platforms and integration, with healthcare or insurance experience preferred.

Designs and productionizes hybrid knowledge graph solutions for healthcare and clinical data using LPG and RDF technologies. Builds FHIR transformation and ingestion pipelines, implements ontology mappings, entity linking, identifiers, provenance, validation, and graph queries with Cypher or SPARQL. Collaborates with ontology, terminology, FHIR, clinical, and data engineering teams, while contributing to architecture reviews, code reviews, testing, and engineering best practices.

Analyzes the end-to-end digital purchasing journey across Web and App platforms. Leads A/B testing and experimentation, builds self-service reporting, measures campaign impact, identifies customer experience opportunities, and communicates insights to product, digital experience, analytics, and senior leadership stakeholders.

Administer and optimize Microsoft SQL Server and Oracle databases in a federal enterprise environment. Responsibilities include installation, patching, monitoring, backup and recovery, performance tuning, access management, security auditing, cloud migration support, SQL development, documentation, ServiceNow incident response, root cause analysis, and on-call support. The role requires at least four years of database administration experience and the ability to obtain Public Trust clearance.

Own the end-to-end architecture and roadmap for MyFitnessPal’s product data stack. Coordinate data engineering, business intelligence, product analytics, and backend teams; establish data movement and standardization practices; lead tool evaluations and platform migrations; implement governance, PII handling, deletion workflows, access controls, and cost optimization; and document architecture standards across the organization.

Leads PBM data integration delivery across claims, eligibility, accumulator, and encounter systems. Profiles and validates data, writes advanced SQL, resolves reconciliation discrepancies, investigates production issues, and partners with engineering on scalable healthcare integration architecture. Owns timelines, risks, vendor dependencies, testing, UAT, migration, rollback planning, executive reporting, and post-deployment support. Requires deep PBM claims-processing expertise, data architecture experience, and hands-on knowledge of ETL, secure file transfer, job scheduling, and healthcare data standards.

Design, develop, and maintain Customer Data Platform solutions and data pipelines to create unified customer profiles, manage identity resolution, enable audience segmentation and activation, ensure data quality and governance, and support integrations with marketing, CRM, and cloud data systems.

Define and lead the company’s data architecture strategy, roadmap, and standards. Drive the transition from batch to real-time data platforms, guide decisions on governance, security, quality, scalability, and reliability, and identify practical AI applications. Partner with executive, product, and engineering leaders, establish design reviews, influence cross-functional decisions, and lead a global team of senior data architects.