Top Remote Data & Analytics Jobs in Philadelphia, PA

The Sr. Data Engineer - Databricks designs and maintains scalable data solutions using Apache Spark and Databricks, ensuring data quality and performance for analytics and reporting.

Lead design and delivery of large-scale quantitative and qualitative market research studies, manage client accounts, develop RFPs, mentor research managers, ensure project quality, timelines, and provide strategic recommendations and reports.

Own and maintain Center of Excellence network reporting and health metrics. Build recurring and ad hoc dashboards using Databricks, Python, and SQL. Conduct network adequacy and coverage analysis, validate and distribute reports, surface risks and trends, support client meetings, and produce executive-ready summaries while documenting processes and standards.

Lead reporting and analysis across product, call center, and marketing; manage enrollment and revenue reconciliation; produce partner and carrier reports; analyze member engagement and plan performance to surface actionable insights.

Design, develop, maintain, and optimize ADABAS database structures and data solutions. Support mainframe data processing (Natural, COBOL, JCL), perform migrations to modern platforms, tune performance, ensure data integrity/security, troubleshoot issues, and collaborate with developers, architects, and analysts on modernization, API/cloud integration, and data warehousing initiatives.

Lead end-to-end FOIA data migration projects into RelativityOne, define and prioritize migration tooling, author requirements and runbooks, engage agency customers, ensure FedRAMP-compliant handling of DT1 data, and drive continuous improvement and product feedback.

Lead Imagine's global MEAL strategy, build high-performing country MEAL teams, ensure data governance and quality, develop dashboards and analyses, guide experimental design and reporting, translate insights for stakeholders, and strengthen organizational data literacy to improve program learning outcomes and operational effectiveness.

Build and maintain Power BI reporting products, integrate and validate institutional data, conduct applied quantitative and qualitative research, deliver analyses and visualizations, manage projects and reporting standards, and support cross-organization analytics and stakeholder decision-making.

Investigate financial transactions to identify potential money laundering activities, utilize AI for analysis, document findings, and collaborate with product teams on improvements.

Lead strategic analytics and partner with senior leadership to drive growth, margin, and retention initiatives. Build interactive reporting (Python/Streamlit, BigQuery-connected Google Sheets), perform deep EDA in Jupyter, model and clean data with SQL and dbt, integrate secure AI-assisted tools and automation, ensure analytical quality, and translate insights into measurable business outcomes.