Top Analysis Reporting Jobs in Boise, ID

Design, develop, and support SQL Server databases and related ETL/BI solutions (SSIS/SSRS). Implement database source control, CI/CD with TFS/SSDT, tune performance, maintain security, and collaborate with teams in an Agile/Scrum environment.

Senior technical leader responsible for designing and implementing scalable Databricks/Azure data architectures, building high-scale pipelines, embedding across teams to unblock delivery, mentoring engineers, and defining engineering standards and best practices for enterprise data platforms.

The role involves leading data engineering and analytics teams, optimizing data systems, collaborating on data pipelines, and managing data infrastructure projects.

Design, build, and maintain Workday reports, dashboards, Adaptive Planning sheets, and automations. Deliver workforce analytics, forecasts, and visualizations to support workforce planning and data-driven HR decisions. Collaborate to develop scorecards and influence business outcomes with real-time and forecasted people data.

Lead end-to-end customer journey analytics by integrating structured performance data with Voice of Customer inputs. Drive journey mapping, KPI frameworks, stakeholder alignment, and actionable insights to improve acquisition, engagement, conversion, and retention.

Design, build, and maintain scalable, reliable data systems and pipelines. Partner with Product, Sales Ops, and Finance to deliver analytics and self-service tooling. Maintain SLOs, improve pipeline reliability, implement testing and documentation, and contribute to data platform strategy and operations.

Own end-to-end client data migrations: reverse-engineer legacy ETL, design and build Airflow DAGs and Spark jobs, validate and reconcile data at scale, document architecture and decisions, and coordinate cross-functional teams through go-live and hypercare.

The Senior Data Engineer will develop data engineering solutions, manage ETL workflows, and establish a new data practice while collaborating with stakeholders.

Design and run evaluation frameworks to assess third-party vendor data for fraud detection. Build lift analyses, backtests, and champion/challenger tests; profile vendor datasets for quality and coverage; collaborate with fraud, product, and data engineering to define ingestion and testing requirements; translate findings into actionable recommendations and maintain an internal knowledge base; support ad hoc analyses on fraud trends and model performance.

The Senior People Analytics Consultant delivers insights from complex data to guide people strategies and influence decisions within the organization.