Top Remote Data & Analytics Jobs in Lincoln, NE

As a Senior Data Engineer, you'll transform raw data into datasets, design production pipelines, integrate customer data, and collaborate with various teams to ensure data quality and reliability.

The EHSS & Quality Senior Analyst leads data management for EHS, ESG, and Quality goals, ensuring compliance and driving continuous improvement initiatives. Responsibilities include data collection, analysis, and reporting, as well as the development of dashboards and automation processes.

As a Senior Data Analyst, you will analyze game telemetry data, translate business needs into insights, and guide technical teams. You will also lead exploratory data analysis and maintain data quality practices.

The Senior Manager of Data Insights will lead a team to optimize data sharing and governance, develop data strategies, and deliver actionable business intelligence across Docker's operations.

As a Senior Data Analyst, you'll define analytics strategies, implement data infrastructure, perform analyses, and leverage AI to enhance decision-making across the organization, focusing on personalized coaching outcomes.

The M365 Power Platform Specialist will design and implement automation solutions using Microsoft tools to enhance workflows and optimize business processes while collaborating with stakeholders to deliver tailored solutions.

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.

Lead and scale the data analytics organization, guiding teams, driving product analytics strategy, and integrating AI to enhance data-driven decision-making across the company.

The Lead Implementation Specialist is responsible for data integration, reporting, and visualization, ensuring compliance, facilitating client support, mentoring, and driving continuous improvement in data processes.

Lead design and delivery of large-scale data pipelines and warehouse systems. Define technical strategy, enforce data governance, improve developer efficiency, mentor engineers, and align data engineering efforts with business goals to enable analytics and ML at scale.