Top Remote Data & Analytics Jobs

We are seeking a Data Engineer to design, build and optimize scalable data pipelines. Strong experience in Databricks, PySpark, and data warehouse concepts is required.

Design and implement scalable, secure enterprise data solutions on Databricks and Azure using Delta Lake and Medallion Architecture. Lead and mentor data engineering teams; define integration patterns, governance, security (Unity Catalog, RBAC, masking, row/column-level security), and CI/CD/IaC practices. Ensure data quality, lineage, monitoring, and optimize Spark/Delta workloads for performance and cost while aligning solutions with business needs.

Lead design and delivery of enterprise risk data architecture using Microsoft Fabric. Build medallion data pipelines, unify risk data from ServiceNow, SAP, Workday and others, create Power BI semantic models, establish data governance and observability, and enable analytics and AI-ready datasets for IRM stakeholders.

The BI Developer III will enhance BI systems, develop applications for data analysis, and collaborate with other developers. Requires intermediate BI skills and knowledge.

Lead hands-on development, validation, and productionalization of actuarial models for commercial lines using Python and cloud platforms. Translate outputs into executive-ready deliverables, maintain auditability, partner with solution engineering to operationalize models, and scale a team and vendor resources across the analytics platform.

Design and implement scalable data platforms, build ETL/ELT pipelines, integrate multiple data sources, define KPIs, create dashboards and executive reports, ensure data quality/governance, and collaborate with stakeholders to optimize BI capabilities.

Drive data-led growth for US loans: analyze and optimize acquisition channels, design price tests, forecast and allocate volume, validate commercial hypotheses, and implement changes using SQL and analytics tools.

Build and maintain production-grade data processing systems and foundational infrastructure for enterprise AI. Collaborate with researchers and engineers, deliver end-to-end implementations, transform unstructured data into performant datasets, and use distributed processing frameworks and modern analytics tooling to inform products and strategy.

Provide ad-hoc data and reporting support to Sales and internal teams using SQL, Databricks/Count, and spreadsheets. Clarify requirements, investigate discrepancies, resolve basic data issues, support routine data operations, and create reusable queries/reports and documentation to enable self-service.

Lead SAP Data Migration activities for enterprise transformation projects, ensuring data quality, governance, and compliance while collaborating with cross-functional teams.