Top Data & Analytics Jobs in Philadelphia, PA

Build data pipelines, tools, and infrastructure for large-scale data warehousing alongside experienced data engineers. Work with AWS, Redshift, Glue, ECS, DMS, Fivetran, Airflow, DataHub, Terraform, Python, and SQL while partnering with Risk, Commerce, Marketing, Operations, and Finance stakeholders. Interns will ship production improvements, present their work, and gain practical experience in data engineering at a fintech startup.

Leads marketing analytics, predictive modeling, segmentation, and experimentation to improve acquisition, retention, and pipeline performance. Designs and maintains machine learning models, governs A/B and multivariate testing, translates insights into campaign execution, and evaluates analytics platforms. Manages budgets, regulatory compliance, strategic initiatives, and team performance while partnering with Finance, Sales, Operations, IT, and servicing teams. The role is fully on-site with occasional adjusted schedules.

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.

Analyzes customer, operational, and financial data to produce dashboards, predictive insights, value cases, and actionable recommendations. Partners with cross-functional leaders to improve customer experience, field service, scheduling, care, operational performance, and margins. Maintains KPI definitions, supports business reviews, improves data quality, and tracks initiatives from recommendation through realized impact. Uses AI-enabled tools responsibly to accelerate analysis and develop agent-assisted workflows.

Leads enterprise-wide data and AI governance, including policy development, AI Governance Center of Excellence leadership, risk assessment, regulatory compliance, data stewardship, and governance lifecycle implementation. Partners with Engineering, Product, business units, and executives to manage data quality, metadata, master data, retention, privacy, bias, cybersecurity, and third-party risks. Establishes governance KPIs, advises senior leadership, and promotes responsible AI accountability through training and awareness programs.

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.

The Junior Data Analyst cleans, transforms, validates, queries, and maintains data for business intelligence. Responsibilities include database management, data quality assurance, statistical analysis, dashboard and report development, documentation, stakeholder collaboration, SOP support, and contributing to data lake or warehouse solutions. The role requires SQL, Excel, strong analytical skills, and the ability to support data-driven decisions in a fully on-site environment.

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.