Top Remote Data & Analytics Jobs

Translates transport platform data requirements into technical data models, schemas, semantic layers, and warehouse integrations. Develops ERDs, data matrices, lineage documentation, transformations, and technical specifications while supporting data governance and quality. Collaborates with product experts, architects, reporting teams, and stakeholders to enable analytics and self-service reporting. Maintains data models as platforms evolve, with a focus on Blue Yonder TMS and global transport implementations.

Leads enterprise data platform architecture, engineering standards, technical decisions, and development of scalable data products. Designs batch and streaming systems, governance, observability, security, and reliability practices. Partners cross-functionally, mentors engineers, drives modernization and migrations, and establishes reusable patterns for data modeling, orchestration, quality, and platform operations.

Designs and optimizes scalable data infrastructure, including ETL pipelines, data integrations, BI solutions, validation, cleansing, workflow optimization, and troubleshooting. The role supports clinical and operational teams by integrating data from clinical systems, APIs, warehouses, and external sources while ensuring data quality and performance. Collaboration across departments and delivery of data-driven insights are key responsibilities.

Generates enterprise, market, customer, and competitive insights for Customer Solutions. Analyzes healthcare trends, customer needs, market opportunities, and competitive dynamics; builds models, forecasts, and scenario analyses; translates research and voice-of-customer data into strategic recommendations; presents executive-ready insights; and supports marketing and PMO initiatives.

Lead the architecture and implementation of scalable, secure cloud data platforms for Nokia’s photonic integrated circuit operations. Build high-performance batch and streaming pipelines, enterprise data models, quality and observability frameworks, DataOps automation, governance, and AI-ready data foundations. Enable trusted self-service analytics and AI-assisted exploration while leading and mentoring product engineering teams and driving technical excellence.

Leads Relation Insurance’s enterprise data engineering and analytics function, owning data strategy, architecture, pipelines, governance, quality, reporting, and AI-enabled workflows. The role requires hands-on development in SQL, Python, and PySpark, executive communication, technical team leadership, lakehouse architecture, Power BI modeling, production support, and secure data management. The director also directs AI coding agents, builds LLM-powered workflows, establishes engineering standards, and delivers reliable data products aligned with business priorities.

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.

Analyzes card fraud threats by gathering and interpreting transaction data, quantifying losses, evaluating fraud rules, monitoring suspicious activity, and recommending control improvements. The role produces reports and presentations, supports automation, data governance, model monitoring, quality audits, and ad hoc business analysis. It partners with fraud, data governance, and model governance teams to improve detection effectiveness and reduce financial losses.

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.