Top Remote Data & Analytics Jobs in Boise, ID

Lead complex customer analytics engagements, translating industrial business needs into scalable analytics architectures and solutions. Advise customers, drive product adoption, identify high-value use cases, mentor Analytics Engineers, resolve technical escalations, and influence product roadmaps. Apply expertise in industrial process data and sectors such as power, pharmaceuticals, and semiconductors. Collaborate with customers, partners, product teams, and account teams to deliver measurable business outcomes.

Lead enterprise Master Data Management strategy, architecture, governance, data quality, and integration initiatives across customer, product, supplier, employee, and financial domains. Design data models, hierarchies, matching and survivorship rules, integration patterns, and implementation roadmaps. Advise clients on Oracle and Salesforce ecosystems, lead workshops and executive presentations, guide solution delivery, mentor consultants, and contribute to proposals and statements of work.

Designs, develops, and maintains Databricks-based ETL pipelines, data lake architectures, datasets, and data warehouses supporting reporting, analytics, and AI/ML workloads. Troubleshoots and optimizes Databricks and SSIS processes, maintains SSRS reports, implements data quality controls, migrates legacy systems, and collaborates with business and technical teams. The role also promotes AI-assisted development practices and documents technical procedures.

Designs, analyzes, documents, integrates, and migrates complex environmental datasets for AirHub business lines. Responsibilities include analyzing legacy databases, creating logical and physical data models, documenting mappings and business rules, developing migration specifications and API integrations, supporting data governance and testing, and producing technical documentation. The role also requires close collaboration with business stakeholders in an Agile delivery environment.

Lead financial data engineering initiatives involving commissions, incentive programs, and backend financial systems. Build scalable, accurate, and reliable data pipelines, platform tooling, partner integrations, analytics infrastructure, and data science infrastructure. Shape technical strategy and roadmaps, collaborate with Finance, Product, Data Science, and Engineering, mentor engineers, contribute code, lead incident response, and establish engineering standards.

Supports commercial loan system administration, department reporting, and analysis of deposit and lending activities. Works with large datasets across multiple systems to synthesize actionable insights, collaborates with credit union departments, and performs related administrative and analytical tasks under supervision. The internship is fully remote with optional office work and is limited to 29 hours per week.

Leads end-to-end healthcare payer data conversions between platforms, including profiling, transformation mapping, ETL design, mock and parallel runs, bulk loading, validation, testing, defect resolution, documentation, and client reporting. Develops Python and SQL conversion routines, manages risks and timelines, collaborates with onshore and offshore teams, and mentors junior staff. Requires expertise in claims, enrollment, or provider data and extensive technology integration leadership.

Build and maintain scalable ETL/ELT pipelines, integrate travel and customer data from internal and external systems, develop cloud data warehouse models, implement data quality monitoring, support real-time streaming, and ensure data privacy and regulatory compliance. Collaborate with analysts, data scientists, and product teams to deliver reliable datasets for personalization, forecasting, pricing, route optimization, and customer experience initiatives.

Develop and deploy business intelligence applications for a U.S. Air Force financial platform across development, testing, integration, and production environments. Design and optimize Informatica ETL pipelines, Oracle databases, SQL and PL/SQL processes, data warehouses, BI semantic layers, and SAP integrations. Support Agile delivery, budgeting integrations, monitoring, interface changes, and security hardening. The role also requires Oracle APEX, WebLogic, HTTP Server, performance tuning, and collaboration on data-related issues.

Build and maintain Google Cloud data pipelines and ETL/ELT processes supporting GenAI and RAG solutions. Classify and govern sensitive data using Dataplex and Cloud DLP, enforce access controls, assess AI readiness, and design reusable schemas and data models. Collaborate with engineering, delivery, and client teams to integrate legacy systems, monitor pipeline reliability, conduct data quality testing, document data flows, and proactively identify compliance and delivery risks.