Top Senior Data & Analytics Jobs in Lincoln, NE

The Senior Data Engineer will design and implement lakehouse architectures, optimize ClickHouse deployments, develop ETL/ELT pipelines, and create data models to support analytical and operational functions.

The Director of Cloud FinOps will manage financial operations related to public cloud, optimize costs, and partner with various teams to maintain efficiency and profitability.

Own and implement the canonical data model and governance for a multi-tenant MEP SaaS platform. Architect data for AI/ML readiness (RAG, embeddings, vector search), design polyglot persistence and lake/lakehouse pipelines, lead staged modernization and migrations, produce hands-on prototypes and in-repo guardrails, and partner with platform, DB engineering, and ML teams to ensure data quality, lineage, and observability.

Lead and scale companywide analytics for a DTC marketing business: own marketing measurement, financial forecasting, retention/LTV modeling, data architecture, reporting, and the analytics team. Set analytics strategy, oversee data engineering roadmap, build dashboards, apply statistical and ML methods, and translate insights into executive-level decisions.

The SAP IBP Analyst will optimize supply chain planning processes in e-commerce, focusing on SAP IBP modules, system integrations, and stakeholder management.

Collects and organizes information for user manuals, training, installation guides, proposals, and reports. Edits functional descriptions and system specifications. Prepares and maintains systems, programming, and operations documentation and procedures. Maintains internal documentation library, supports financial/administrative tasks, coordinates documentation services, and works with Agile teams in a secure remote environment supporting government projects.

Lead design and ownership of ZoomInfo's PLG measurement system, define KPIs and leading indicators, analyze end-to-end customer journeys, diagnose growth issues, and influence product investments. Build AI-native, automated analytics workflows, reporting, and monitoring while partnering cross-functionally to prioritize experiments and scale insights that drive adoption, retention, monetization, and expansion.

Build and maintain the product analytics data foundation: design scalable dbt models, define semantic models and governed metrics, partner with Engineering on instrumentation, certify datasets for BI tools, monitor pipelines and data quality, and use AI to accelerate analytics engineering workflows.

Lead complex data, analytics, AI, and cloud transformation engagements as a trusted advisor: manage delivery, scope, budget, stakeholders, and teams; design scalable data platform solutions; drive business development, mentoring, and practice improvements.

Own end-to-end data pipelines (ingest, dbt transformations, BigQuery warehousing) and consolidate the analytics stack into a single source of truth. Build and maintain dbt models with tests and documentation, establish data quality and observability, own product analytics and instrumentation, partner with GTM and marketing on reporting, and prepare for high-volume/streaming ingestion.