Top Remote Data & Analytics Jobs in Boise, ID

Own the architecture, roadmap, and operation of Clarium’s AWS-based data platform. Build reliable batch and near-real-time pipelines, model healthcare supply chain data, optimize Postgres and Snowflake performance, and establish standards for testing, deployment, quality, and governance. Partner cross-functionally to create durable data models, lead multi-quarter initiatives, manage sensitive data controls, and mentor engineers.

Leads and mentors the Data Engineering team while remaining hands-on in designing, building, and maintaining scalable data pipelines, warehouses, integrations, and infrastructure. Establishes architecture, reliability, quality, and performance standards; guides technical delivery; and resolves complex issues. Partners with Finance and business stakeholders to translate data needs into practical solutions, sets technical direction, evaluates technologies, and communicates strategy, risks, and recommendations to leadership.

Designs and maintains enterprise data architecture, including data lakes, warehouses, integrations, migrations, orchestration, and data management protocols. Partners with architects, DBAs, BI teams, product leaders, and business stakeholders to support analytics and data science. Requires deep experience with cloud data environments, Azure SQL, Microsoft Fabric, Spark, Hadoop, PySpark, SparkSQL, security protocols, and enterprise data integrations.

Leads the design and implementation of scalable data architectures, ETL pipelines, data warehouses, migrations, and cloud data solutions. Provides technical leadership through system analysis, requirements gathering, design documentation, code and architecture reviews, SDLC management, production deployments, and mentoring junior engineers. Develops integrations using multiple programming languages, ETL platforms, cloud services, APIs, and CI/CD tools.

Leads and delivers complex data engineering projects, designing scalable data infrastructure, pipelines, warehouses, and data quality solutions. Recommends tools and architectures, optimizes data movement and performance, collaborates across technical teams, mentors engineers, and translates technical concepts for clients and nontechnical stakeholders. The role may also involve real-time processing, data modeling, transformation, security, and MLOps.

Analyze large healthcare datasets, build and implement quantitative models, perform statistical analyses, ensure data accuracy, collaborate with cross-functional teams, and provide actionable insights to improve healthcare delivery.

Analyze medical claims (inpatient, outpatient, SNF, rehab, professional, DME) to identify utilization and root causes. Pull/integrate data, perform QA, present findings, maintain attribution methodology, coordinate stakeholders, and develop tools. Primary coding: Hive, SQL, Python.

Administer and optimize enterprise SQL Server and Azure SQL databases across development, testing, and production environments. Responsibilities include database installation, upgrades, migrations, modeling, security, backup and recovery, performance tuning, data warehouse and Power BI support, and ETL validation. The role collaborates with developers, stakeholders, vendors, and service providers while supporting releases, risk tracking, issue resolution, and process improvement.

Serves as the technical authority for Azure SQL architecture, deployment, security, performance, operations, and migrations supporting federal programs. Designs secure Azure Government database environments, leads on-premises SQL Server migrations, develops T-SQL and data models, builds Azure Data Factory pipelines, implements DevOps and infrastructure automation, troubleshoots incidents, optimizes costs, documents standards, and mentors team members. Collaborates with engineering, architecture, data, and DevOps teams on reliable data platforms.

Monitor prediction markets and perpetual futures by tracking news, trader sentiment, venues, volumes, open interest, funding rates, and market share. Research protocols and users, build dashboards and datasets, identify product opportunities for Pyth, size opportunities with market and on-chain data, and collaborate with product, engineering, and business development teams. Write research reports, present recommendations to leadership, and evaluate launched initiatives against their original theses.