Top Remote Data & Analytics Jobs in Philadelphia, PA

Design and maintain ELT/ETL pipelines and cloud data warehouse models, build Power BI reports, apply AI tools to accelerate data workflows, and partner with business stakeholders to deliver reliable analytics and data governance.

Support data collection, cleaning, and preliminary analysis. Write and run SQL queries, use statistical tools and Python, produce visualizations, document methods, troubleshoot analytics tools, and collaborate with cross-functional teams to deliver actionable insights.

Lead credit underwriting, pricing, verification, and portfolio performance for personal loans. Use data and ML/AI to design automated decisioning, manage credit/fraud risk, forecast losses, and present strategies to leadership and investors. Collaborate cross-functionally and build vendor/alternative-data strategies to drive profitable growth while keeping losses within risk appetite.

Design, develop, and implement data warehouse logical and physical models, build ETL processes (preferably BODS), tune SQL and star-schema queries, manage metadata, and support DW implementation on Oracle/relational databases.

Design, implement, and optimize Snowflake data storage and ETL solutions. Write and tune SQL, integrate data sources and BI tools, ensure data security and compliance, and collaborate with teams to meet business objectives.

The Senior Data Engineer will design and implement lakehouse architectures, optimize ClickHouse deployments, develop ETL/ELT pipelines, and create data models to support analytical and operational functions.

The SAP IBP Analyst will optimize supply chain planning processes in e-commerce, focusing on SAP IBP modules, system integrations, and stakeholder management.

Lead a small analytics team to produce data-driven insights for marketing and media optimization. Mine proprietary datasets, apply statistical methods, forecast KPI impacts, monitor business metrics, and act as liaison between business and technical teams to drive profitable media and client growth.

Analyze high-scale payment funnel and transactional data to identify conversion bottlenecks, design and evaluate A/B tests, define metrics and measurement frameworks, monitor product performance via dashboards, and translate insights into prioritized product recommendations in partnership with Product and Engineering.

Define and govern enterprise data architecture, models, canonical and semantic layers, field-level mappings, and data governance. Partner with IT, Data Engineering, Security, and product teams to ensure data quality, lineage, integrations (Boomi), and platform alignment (Salesforce, Snowflake, NetSuite). Lead M&A data activities, perform hands-on data profiling and validation, and drive adoption of enterprise data standards to support analytics, AI, and automation initiatives.