Top Senior Data & Analytics Jobs in Philadelphia, PA

Designs and optimizes batch and streaming data pipelines, cloud data warehouses, dimensional data models, and ETL/ELT processes at terabyte scale. Troubleshoots pipeline issues, improves infrastructure reliability and performance, implements data quality and governance practices, and supports privacy compliance. Collaborates with analysts, data scientists, and stakeholders to translate business needs into technical solutions. Leads and mentors data engineers, documents systems, and evaluates emerging technologies.

Owns end-to-end architecture and delivery of data products, including schemas, entity resolution, provenance, schema evolution, and normalization pipelines. Leads conversion of unstructured and semi-structured sources into enterprise-quality datasets using deterministic parsing, LLM-assisted extraction, inference, and human review. Partners with domain experts, data scientists, and AI engineers while applying strong SQL, Python, distributed processing, testing, observability, and CI/CD practices.

Leads enterprise data architecture and infrastructure strategy, designing data warehouses, data lakes, and hybrid cloud solutions. Establishes governance, security, automation, DevOps, and CI/CD practices while evaluating emerging technologies such as AI and machine learning. Partners with executives and cross-functional teams on data strategy, cloud roadmaps, resource planning, cost optimization, integrations, and troubleshooting. Serves as an organization-wide subject matter expert and mentor.

Design, build, and operate scalable batch, streaming, and CDC data pipelines across Snowflake and AWS. Lead ETL/ELT architecture, orchestration, data modeling, quality monitoring, observability, incident resolution, and performance optimization. Develop production solutions in SQL and Python, establish engineering standards for testing and CI/CD, and partner with Analytics Engineering, Data Science, Product, and Engineering teams to deliver reliable data products.

Leads fraud strategy through trend analysis, root-cause investigation, mitigation recommendations, and fraud-control optimization. Manages and mentors 2–5 fraud analysts, evaluates detection tools and data sources, monitors performance metrics, and communicates risk insights to leadership. Partners with Operations, Compliance, Credit, and Product teams to implement compliant fraud strategies and reduce losses while supporting growth.

Leads the Underwriting Data Engineering team and oversees the design, development, and productionization of scalable data and machine learning pipelines. Responsibilities include feature engineering, data preparation, model deployment, data validation, governance, monitoring, API integration, analytic data products, roadmap development, stakeholder collaboration, and team coaching.

Designs, develops, and owns business intelligence dashboards, visualizations, analyses, and reporting solutions, primarily in TIBCO Spotfire and also Power BI. Responsibilities include data modeling, calculations, performance tuning, deployment workflows through GitHub, data quality collaboration, BI standards, risk identification, mentoring, and independent decision-making across a multi-tenant Life Sciences data platform.

Leads the design and maintenance of automated data systems for insurance commission processing, accounts payable, payroll reconciliation, and agency payments. Builds ingestion, validation, normalization, reconciliation, mapping, encryption, and self-service tools. Manages agent and agency master data and cloud-hosted infrastructure with backup and recovery capabilities. Improves financial operations by replacing manual spreadsheet workflows with secure, scalable, auditable pipelines.

Leads Data Operations, including reporting, dashboards, data warehouse and dbt model oversight, data quality, governance, service levels, incident response, and stakeholder prioritization. Manages and develops data professionals while partnering with Data Engineering, Security, Privacy, Compliance, and Enterprise Architecture. Ensures reliable, secure, well-documented data services and protects PHI through appropriate access, privacy, lineage, retention, and monitoring controls.

Analyze executive questions using financial, operational, sales, and customer data; reconcile inconsistent sources; build models and variance analyses; deliver recommendations and board-quality reporting. Lead cross-functional CEO initiatives, support acquisition integration and diligence, coordinate executive office continuity, and manage confidential information. Create visualizations, project plans, executive presentations, and reporting architecture while partnering with senior leaders across finance, operations, IT, and corporate functions.