Top Data & Analytics Jobs

Governs and maintains product, customer, and vendor master data across SAP, Devex, and One World Sync. Develops data standards, governance controls, and standard operating procedures; supports product change projects, integrations, testing, troubleshooting, root cause analysis, and process improvements. Partners with cross-functional teams to ensure data accuracy and integrity, tracks item setup progress, conducts training, and supports compliance with GS1 standards.

Develop marketing analytics, KPIs, reporting methodologies, dashboards, visualizations, and actionable insights for client campaigns. Query and analyze data, identify optimization opportunities, communicate findings to technical and nontechnical audiences, collaborate with media planning and brand strategy teams, and manage client expectations. The role also improves analytical workflows, supports measurement strategies, and presents key findings throughout client engagements.

Designs and maintains scalable data pipelines, warehouses, lakes, integration solutions, and analytics platforms. Develops AWS and Snowflake data solutions using Python, SQL, dbt, ETL/ELT, and Data Vault modeling. Supports replication, APIs, governance, metadata, lineage, and data quality across enterprise environments. Troubleshoots complex data issues and provides technical leadership while collaborating with engineering, architecture, analytics, and business teams.

Research and engage utility providers to improve bill delivery methods. Monitor automated workflows, troubleshoot robot exceptions, investigate recurring email and bill processing failures, and optimize automation accuracy. Collaborate with external utility vendors and internal development and testing teams while communicating clearly and working independently in a fast-paced environment.

Lead the design and development of enterprise data products and AI platforms. Build ELT pipelines, semantic models, governance, quality, observability, and lineage frameworks using dbt, SQL, Python, and Databricks. Develop executive analytics applications, conversational AI agents, RAG systems, and guardrails. Partner with senior leaders across business functions, establish engineering standards, and mentor engineers while remaining hands-on.

Build and operate data products, scalable pipelines, and ML-ready features from traffic telemetry. Develop analytics for anomaly detection, incident prediction, capacity forecasting, and traffic attribution. Create dashboards for platform performance, implement data quality and monitoring practices, and apply statistical techniques to identify reliability and traffic patterns. Collaborate with engineering, SRE, platform, application, and product teams to improve scalability, observability, and decision-making.

Leads enterprise data platform engineering and architecture across OCI, GCP, and Azure. Owns the modern data and AI operating system, metadata control plane, data catalog, security model, observability, and AI infrastructure including vector databases, knowledge graphs, feature stores, and RAG pipelines. Guides platform engineering standards, modernizes legacy ETL, establishes GitOps and Data-as-Code practices, and mentors global technical teams while presenting architecture to executive stakeholders.

Provides market and vertical insights through research design, quantitative analysis, reporting, and data visualization. Translates business needs into research, develops pivot tables and graphs, supports marketing and business intelligence requests, identifies trends, and makes data-driven recommendations to leaders. Collaborates with marketing, sales, product, solutions, and cross-functional analyst teams. The role requires a hybrid schedule in Lincolnshire, Illinois, or Holtsville, New York.

Build and operate reliable data pipelines transforming flight test, simulation, and operational data into versioned, traceable ML training datasets. Responsibilities include ingestion, normalization, time alignment, validation, dataset lineage, anomaly mining, labeling workflows, deployment feedback loops, monitoring, and data coverage analysis. Collaborate with flight test and operations teams on instrumentation and data access. The role is on-site in Boston and requires production data engineering experience supporting machine learning pipelines.

Reviews and reconciles data errors before records are cataloged in the Automated Records Management System. Corrects incomplete or erroneous information, coordinates with responsible offices, provides customer service, answers phones, and serves as a trusted system access agent. The role requires effective communication, computer proficiency, flexibility in a fast-paced environment, and the ability to meet physical requirements.