Top Data & Analytics Jobs

Support and improve enterprise Customer 360 and MDM capabilities through identity resolution, match/merge, survivorship, stewardship, data quality, and governance. Investigate ingestion and transformation issues using SQL and Snowflake, partner with business and technical stakeholders, automate stewardship and remediation workflows, and contribute to AI-enabled, scalable customer data solutions and operational utilities.

Lead the Power & Energy segment’s data architecture vision, strategy, target-state roadmap, conceptual and enterprise data modeling, governance standards, security, metadata, lineage, and solution design. Partner with data engineering, analytics, IT, business stakeholders, and executives to ensure scalable, reusable, high-quality data ecosystems aligned with business needs. Guide data modernization, cloud migration, and digital transformation initiatives.

Design and govern data assets, develop pipeline specifications with field-level mapping and quality rules, document domain data models and canonical formats, design scalable databases and ETL solutions, and solve complex data problems to support Cat Digital. Hybrid work: telecommute one day per week.

Build and support Snowflake-based data pipelines, transformations, and analytical data products for Procurement and Supply Chain. Modernize SAS processes, investigate data discrepancies and production issues, improve data quality and governance, and document data lineage and definitions. Collaborate with product owners, data stewards, analytics teams, and business stakeholders to translate needs into scalable solutions and communicate technical findings clearly.

Lead analytics and digital solutions for global Sales & Operations Planning in Power & Energy. Analyze demand, supply, and capacity data; build data models, dashboards, and reporting; translate business requirements into analytical tools; support S&OP, supply and capacity planning, and 24-month supplier signals; present insights to leadership and drive continuous improvement across global stakeholders.

Design, build, and maintain Python data pipelines and business data objects. Implement source-to-target mappings, CI/CD pipelines, unit and integration tests, and deploy solutions. Apply software design and architecture best practices, mentor team members, and resolve complex technical problems across functional teams.

Design, build, and maintain scalable cloud-native data pipelines, microservices, and platforms to support real-time and batch processing. Collaborate with architects and stakeholders to translate requirements, implement AWS-based ingestion/streaming solutions, enforce data quality/testing, and operate observability and CI/CD practices to ensure reliable production data systems for autonomy initiatives.

Design, build, and maintain scalable data pipelines, microservices, and cloud-native data platforms. Implement real-time and batch processing using Python/Java and AWS services, ensure data quality and automated testing, monitor production systems, collaborate with architects and stakeholders, and drive operational excellence and CI/CD deployment for large-scale distributed data environments.

Lead design, build, and operate scalable data pipelines, microservices, and cloud-native data platforms. Collaborate with architects and stakeholders to translate requirements, ensure data quality and testing, implement streaming and batch solutions on AWS, and maintain operational excellence, monitoring, and CI/CD for high-availability data systems supporting autonomy initiatives.