Top Analysis Reporting Jobs in Omaha, NE

Designs, builds, optimizes, and tests Snowflake lakehouse architecture and ETL/ELT pipelines integrating Salesforce, marketing, and business data. Develops Bronze, Silver, and Gold data models, semantic layers, and datasets for Power BI, analytics, and AI initiatives. Implements data quality and governance procedures, maintains Git repositories, documents architecture, leads solution design, reviews code, mentors engineers, and communicates technical solutions to stakeholders.

Validate and assure enterprise data quality across source systems, ETL/ELT pipelines, data warehouses, and reporting. Investigate production incidents, design test strategies and automated validation, perform regression and non-functional testing, analyze data quality metrics, support compliance/audit activities, and collaborate with engineering and business stakeholders to improve data governance and controls.

Design, build, and maintain Power BI and Tableau dashboards; analyze large, complex datasets using SQL, Python, and statistical methods; partner with data engineering and business stakeholders to ensure data quality; translate findings into clear, actionable stories and executive-level presentations; support firmwide analytics growth and automation.

Develop, maintain, and migrate reports using SQL Server Reporting Services (SSRS) and Crystal Reports. Manage report migrations and version control using Team Foundation Server (TFS). Collaborate with the team to support reporting requirements and ensure successful report deployments.

Senior analyst to design, develop, and administer databases and applications, build analytics and visualization products, support AI/ML data operations, lead Agile development activities, and operate in classified USSTRATCOM environments.

Serve as an analytics partner to business units to define problems, scope projects, perform in-depth analysis, and deliver actionable insights. Lead technical execution with data engineers/scientists, build dashboards in Looker, apply statistical methods and A/B testing, and drive data literacy and process improvements across the company.

Build and operate large-scale audio data pipelines for AI model training. Responsibilities include discovering data sources, improving data-processing systems for quality, throughput, and cost, collaborating with AI scientists, and owning engineering projects through continuous improvement.

Build and operate large-scale audio data pipelines for AI model training. Responsibilities include discovering data sources, developing reliable processing systems, optimizing data quality, throughput, and cost, and collaborating with AI scientists. The role requires ownership of engineering projects from discovery through continuous improvement in a distributed, ambiguous environment.

Build and operate large-scale data pipelines that acquire, process, and improve audio datasets for AI model training. The role focuses on data quality, throughput, cost optimization, production systems, and collaboration with AI scientists. Responsibilities include discovering data sources, developing reliable processing systems, and owning engineering projects from discovery through continuous improvement.

Designs and maintains production data ingestion pipelines, layered analytics-ready data models, and reliable automated data foundations. The role integrates client data from APIs, files, Databricks, and shared-data sources; implements testing, monitoring, schema-change handling, and safe reprocessing; and supports application, analytics, and future AI use cases. It also requires collaboration with product teams, strong communication, cloud data warehouse experience, and AI-native development practices.

Reviews and annotates video and audio clips, evaluates AI-generated multimedia descriptions, moderates content against project guidelines, and provides detailed written feedback. The role requires consistent high-volume data labeling, confidentiality, independent remote work, collaboration, and participation in process improvements.

Reviews short video and audio clips, annotates visual and auditory content, evaluates AI-generated descriptions, and provides clear written feedback. Applies project guidelines consistently, flags unclear or noncompliant content, maintains data quality and confidentiality, collaborates remotely with project coordinators, and suggests improvements to annotation and quality assurance processes.

Designs and maintains secure, reliable data platforms, including relational data models, migrations, pipelines, monitoring, data quality processes, and self-service reporting access. The role protects PHI and PII through access controls, encryption, audit logging, and governance in a HIPAA environment. It also involves backend API development, code reviews, security reviews, stakeholder collaboration, and mentoring teams on data practices.