Top Data & Analytics Jobs in Omaha, NE

The Director of Data Analytics & Business Intelligence leads analytics functions, building models and dashboards while guiding a team. Responsibilities include analytics infrastructure management, cross-functional collaboration, and driving AI/ML initiatives.

The Principal Data Engineer designs and maintains scalable data systems, evaluates new technologies, mentors junior engineers, and leads data engineering initiatives in agile environments.

The Senior Data Engineer will design and implement complex data models, collaborate on data governance, lead data initiatives, and mentor team members.

Lead legacy-to-SaaS data migrations: design and execute ETL, extract/transform/load data, validate integrity, map business workflows to target models, engage clients, document processes, support governance, and train stakeholders to ensure accurate, secure conversions.

Designs, builds, and maintains scalable ETL/ELT data pipelines and integrations. Profiles and cleanses data, creates mappings and SQL, documents metadata, monitors data quality, participates in code reviews, and collaborates with analytics, DBAs, and business partners to enable accurate analytics and data warehousing.

Analyze, trace, reconcile, and migrate insurance policy data from legacy systems into a modern policy platform. Build source-to-target mappings and ETL transformations, perform data cleansing and validation, write complex SQL, use cloud databases (AWS RDS/S3), and collaborate with stakeholders using GitHub and Agile tools. Heavy daily use of AI tooling; mentorship provided throughout migration lifecycle.

Lead Salesforce administration and data quality efforts, manage data model transformations and integrations (FormAssembly, WordPress), handle support tickets and training, create documentation and user enablement, oversee external data collection processes, and collaborate with internal teams and external consultants to build a data-driven culture.

Design, build, and maintain Scala-based ETL and streaming data pipelines, APIs, and data microservices in Azure. Optimize LLM fine-tuning and RAG workflows, support DevOps/CI-CD practices, document standards, mentor engineers, and manage data ingestion frameworks for analytics and partner integrations.

Partner with Product and Engineering to turn product data into insights: define AI/agent metrics, design and analyze experiments, build dashboards and reports, perform cohort and behavioral analysis, surface opportunities, and guide product decisions with measurement and instrumentation improvements.

Lead development and ownership of end-to-end data pipelines and platform tools. Build and optimize ingestion, transform data with dbt and Jinja, implement monitoring/alerting, manage deployments and CI/CD, and create self-service analytics applications and internal tooling.