Top Senior Data & Analytics Jobs in Omaha, NE

Leads consumer and market insights for Yahoo Ads, partnering with sales and go-to-market teams to develop data-driven narratives, audience profiles, vertical trends, case studies, and client materials. Uses Yahoo first-party data, syndicated research, quantitative and qualitative methods, and generative AI tools to accelerate research. Builds validated analytical templates and self-service resources, collaborates on reporting pipelines and dashboards, and translates complex findings into executive-ready presentations.

Leads end-to-end data architecture, engineering pipelines, semantic-layer development, data quality, monitoring, and platform operations. Manages agile sprint planning, release delivery, DevOps metrics, and cross-functional project plans. Establishes MLOps and machine-learning platform capabilities, mentors data engineers, manages team members, and ensures reliable, well-governed data solutions for business intelligence and reporting.

Leads the design, optimization, and governance of scalable data architectures and pipelines. Ensures data quality, integrity, security, and compliance; mentors junior engineers; conducts audits and validation; and collaborates on data governance. The role requires expertise in SQL, Python, dimensional modeling, Snowflake on Azure, Azure Data Factory, Databricks, ETL, and data warehousing, with preferred experience in Airflow, Kafka, healthcare, data lineage, and slowly changing dimensions.

Designs and supports enterprise data integrations, ETL/ELT pipelines, APIs, data models, and transformations across Microsoft platforms. Maintains data quality, governance, security, and reliability while developing CI/CD pipelines, deployment automation, and release processes. Troubleshoots integration and deployment issues, manages environments, supports reporting and analytics, and collaborates with technical and business stakeholders to deliver scalable data solutions.

Designs and delivers analytics solutions on Snowflake using dbt, SQL, and modern ELT practices. Responsibilities include data modeling, pipeline development, migrations, performance optimization, data quality, security, orchestration, CI/CD, and release management. Leads discovery and requirements gathering, translates business needs into analytics architectures, provides technical guidance, and communicates recommendations to client stakeholders in agile consulting environments.

Build risk data models, analyze fraud and risk trends, create Tableau dashboards and automated reports, and deliver actionable insights to Risk Operations leaders. The role manages analytics requirements and roadmaps while using SQL, dbt, Dataform, and AI tools to support fraud strategy, compliance monitoring, loss forecasting, and executive reporting.

Leads Gartner research and thought leadership on data management, governance, and AI. Develops actionable insights, analyzes market trends, advises executive clients, delivers presentations, supports sales and conferences, reviews content, improves research processes, and mentors analysts. Requires deep expertise in data and analytics, AI implementation, data security, data value creation, executive communication, research, and strategic analysis. Remote U.S. role with travel up to 25%.

Build and maintain IICS ETL/ELT pipelines, develop Amazon Redshift data models, and use SQL and Python for data transformation and automation. Create Power BI reporting models, implement data quality checks, document pipelines, and collaborate with client stakeholders and engineering teams. The role requires autonomous work, strong communication, and the ability to translate technical solutions into business context, with bonus value for Veeva or life sciences experience.

Leads legacy data migration into SaaS platforms by assessing sources, designing conversion strategies, executing ETL workflows, mapping and transforming data, validating integrity, and managing PII. Engages clients to gather requirements, document business processes, support governance and data quality, coordinate implementation teams, and develop reusable methodologies and training materials.

Develop and optimize enterprise Oracle SQL and PL/SQL solutions, including data models, database designs, APIs, ETL processes, batch jobs, and performance tuning. Collaborate with cross-functional teams to translate requirements into scalable implementations, support testing and CI/CD, troubleshoot production issues, and document solutions. Provide technical leadership, mentor engineers, participate in architecture and code reviews, and drive engineering best practices across data modernization initiatives.