Top Remote Data & Analytics Jobs

Conduct pretesting, item analysis, IRT, score maintenance, data extraction, statistical reporting, and quality control for SAT assessments. Develop and maintain Python and R-based data management and statistical workflows, improve operational processes, document procedures, and evaluate AI-enabled tools. Collaborate with psychometricians and cross-functional teams to deliver accurate assessment data and reports under strict deadlines.

Build and maintain Power BI dashboards, reports, data models, pipelines, ETL/ELT processes, and data warehouses. Develop advanced DAX and SQL solutions, optimize performance, implement security and governance, manage Fabric and Power BI deployments, and integrate diverse data sources. Translate business requirements into technical solutions while collaborating with end users on testing and implementation. The role also requires strong visualization, data quality, documentation, communication, and automation skills.

Generates business, market, customer, and competitive insights for enterprise strategy and growth initiatives. Analyzes healthcare trends, customer needs, market opportunities, and competitive dynamics; builds forecasts, market models, and scenario analyses; synthesizes research, voice-of-customer data, and internal analytics; and presents executive-ready recommendations. Provides analytical and project support to marketing and PMO teams while translating customer insights into strategic actions.

Collects, processes, and analyzes data from multiple sources using R, Python, and SQL. Develops reports, visualizations, analytical methods, and data-driven insights while applying statistical and introductory machine learning techniques. Collaborates with internal and external stakeholders, documents project progress in JIRA, debugs code, clarifies requirements, and communicates findings through reports and presentations.

Serve as the technical authority for enterprise SQL Server administration and database engineering. Manage configuration, upgrades, patching, performance, security, backups, disaster recovery, and high availability. Design schemas, optimize T-SQL, enforce data integrity, and establish retention policies. Lead incident root-cause analysis, database initiatives, documentation, and continuous improvement while collaborating with DevOps, infrastructure, engineering, QA, and product teams. Mentor developers and maintain highly available, secure, and recoverable production databases.

Lead migration to a Databricks lakehouse using dbt, design ELT pipelines, improve ingestion reliability, establish data quality and governance, and build analytics- and AI-ready datasets. The role owns platform architecture, access controls, monitoring, documentation, data contracts, and legacy-system retirement. It partners with engineering, data science, AI, analysts, and business stakeholders while mentoring engineers and influencing technical standards.

Leads and develops a data engineering team implementing Navigate360 integrations for partner campuses. Oversees integration design, data mapping, validation, reconciliation, quality controls, delivery planning, and scalable implementation processes. Partners with Product, Launch, and Partner Success teams to resolve technical and partner challenges, improve adoption, manage project health, and ensure reliable outcomes. Provides technical mentorship, code and design review, stakeholder communication, and continuous process improvement.

Supports public health data extraction, management, cleaning, validation, harmonization, statistical and qualitative analysis, and evaluation. Develops analytic datasets and documentation, analyzes implementation and outcome measures, integrates mixed-methods data, and prepares technical memoranda, reports, tables, figures, and presentations. The role also uses Microsoft Office and CDC administrative systems while supporting government program monitoring and evaluation activities.

Leads enterprise data engineering by architecting Snowflake and dbt platforms, scalable pipelines, data models, governance, observability, and integrations. Partners with business, architecture, compliance, and technology teams to deliver reliable data products. Resolves complex production issues, improves data quality and performance, supports AI/ML data infrastructure, and mentors engineers while establishing engineering standards and technical direction.

Build, test, and support Databricks data pipelines using Python, PySpark, and SQL. Ingest, clean, validate, and transform source data into reusable layered tables for analytics, reporting, and automation. Document pipelines and business rules, resolve data quality issues, support production delivery, and collaborate with stakeholders and senior engineers. The role also involves adapting to new tools and business areas while supporting a federal government client.