Top Data & Analytics Jobs in Philadelphia, PA

Maintains and updates conflicts database records, especially corporate trees, parent-subsidiary relationships, and affiliated entities. Researches mergers, acquisitions, and other corporate transactions to keep data current, performs quality-control reviews, resolves discrepancies, and collaborates with Finance, Firm Intelligence, and Intake & Conflict Services teams. The role requires corporate research, database maintenance, strong attention to detail, and proficiency with research tools and online databases.

Design, build, and govern end-to-end Power BI reports and dashboards. Scope requirements with business stakeholders, develop data models and DAX, manage datasets/dataflows, enforce dashboard governance, audit performance and accuracy, provide user enablement, and maintain workspaces, RLS, and distribution in Power BI Service.

Build and maintain production data models supporting supply chain, merchandising, marketing, and CRM decisions. Own data integrity, transformation logic, availability, testing, monitoring, documentation, and efficient data access. Partner with business and engineering teams to translate questions into durable models and self-service tools. Develop Looker dashboards, automate reporting, identify data gaps, define data product requirements, and support tracking improvements.

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.

Design, build, and operate Azure-based data pipelines and integrations. Consolidate data from multiple sources into centralized SQL systems, perform transformations and field mapping, and maintain data warehouse capabilities. Troubleshoot quality, integrity, latency, security, and reliability issues while applying governance, monitoring, and SLA practices. Collaborate with engineers, analysts, and stakeholders in Agile pods to deliver reusable, analytics-ready data assets.

Leads the organization’s data strategy, analytics, and measurement capabilities. Advises enterprise clients on attribution, incrementality, marketing mix modeling, customer acquisition, and lifetime value. Oversees analytical workstreams, data products, dashboards, measurement tools, and the analytics roadmap while partnering with strategy, sales, client services, and AI teams. Builds data literacy through training and thought leadership, mentors talent, supports commercial growth, and represents the company at industry events.

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.

Design, develop, and maintain scalable ETL/ELT pipelines using Python, PySpark, Snowflake, and Azure technologies. Build data ingestion frameworks, dimensional data models, and enterprise warehouse solutions. Optimize Snowflake workloads, implement data quality and governance controls, monitor production pipelines, troubleshoot incidents, document data processes, and collaborate with architects, analysts, data scientists, and business stakeholders. Support secure, compliant, reliable data platforms for analytics, reporting, and operational use cases.

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 enterprise data, business intelligence, reporting, and customer and product usage analytics. Owns strategy, architecture, governance, data quality, platform transformation, migration, operational stability, budgets, and partner management across cloud data platforms and BI tools. Manages multidisciplinary data and analytics teams while translating business priorities into scalable, trusted reporting solutions.