Top Data & Analytics Jobs

Provide data analysis, reporting, and operational support for customer communications, contact data integrity, and digital experience platforms. Serve as subject-matter expert for assigned functions, support Salesforce Marketing Cloud messaging (templates, audiences, sends, QA), prepare reports, analyze contact data, assist with user stories/testing, track and resolve issues, monitor workflow, recommend process improvements, and support training and change management.

Design, build, and maintain scalable Python-based data pipelines and ETL processes. Ensure data quality, performance, and reliability while developing APIs, databases, and documentation. Collaborate across teams, perform code reviews, troubleshoot and debug production issues, and implement CI/CD and cloud orchestration solutions.

Lead and develop a team of data engineers while contributing hands-on to design, implement, and operate scalable, secure data pipelines. Partner with product, software, and architecture teams to deliver cloud-native data solutions, ensure production reliability, and drive engineering best practices and continuous improvement.

Lead design and scaling of ELT pipelines and analytics schemas on Snowflake. Build Looker views, CI/CD automation, and orchestration workflows (Prefect/Airflow). Ensure production reliability with monitoring (Datadog, Monte Carlo), partner with cross-functional teams, and provide technical leadership including code reviews, testing, and end-to-end ownership of data integrity and platform trustworthiness.

Manages global sourcing analytics across travel, gaming, and onboard media categories. Designs Power BI dashboards, analyzes complex datasets, builds business models, and delivers insights supporting sourcing strategies, negotiations, and operational improvements. Leads data governance, automation, AI adoption, and reporting optimization while serving as the team’s Power BI subject matter expert. Partners with IT, Finance, and Centers of Excellence to improve data structures, analytics tools, and transactional data quality.

The Business Analyst partners with stakeholders to gather needs, define requirements, analyze operational data, improve processes, assess risks, support system design and configuration, create testing documentation, assist with user acceptance testing and training, and contribute to project management. The role emphasizes operational efficiency, data-driven recommendations, compliance, system functionality, and continuous process improvement across Agency Operations.

Collects, organizes, curates, and maintains macroeconomic and market time-series data for systematic investment research. Responsibilities include data sourcing, vendor management, metadata maintenance, historical data cleaning, seasonal and calendar adjustments, diagnostics, quality control, revision-aware dataset management, and exploratory analysis. Works with research analysts to deliver investment-ready datasets across equities, foreign exchange, rates, and commodities.

Owns enterprise-wide customer data governance, master data management, data quality, standards, lineage, security classifications, and compliance. Leads customer data domain strategy, golden-record definition, quality analysis using SQL, issue resolution, governance initiatives, stakeholder communication, change management, and regulatory alignment. Partners across business, sales, marketing, legal, privacy, and technical teams while managing data catalogs, integrations, audit trails, and governance training.

Leads enterprise data integration and engineering capabilities, including APIs, middleware, ELT pipelines, data governance, master data management, and cloud analytics platforms. Designs secure, compliant integrations across ERP, CRM, clinical, research, quality, finance, and commercial systems. Establishes architecture standards, data quality controls, monitoring, validation, and support processes while coordinating internal engineers, vendors, and business stakeholders. The role also provides technical leadership for trusted datasets, regulatory compliance, operational reliability, and commercialization readiness.

Build and validate SQL transformations mapping healthcare financial and clinical data into a unified ontology and semantic layer. Reverse-engineer customer business rules, own testing and data correctness, manage historical backfills and incremental loads, and collaborate with customers and platform, insights, and product engineering teams. The role requires strong healthcare revenue-cycle data expertise, production Python, modern data-platform experience, transformation-as-code workflows, data modeling, and customer-facing requirements discovery.