Top Analysis Reporting Jobs in Cincinnati, OH

Maintain and monitor Snowflake data warehouse and ingestion pipelines. Troubleshoot file/load/data quality issues, operate SFTP/drop-zone/file automation, support scheduled loads, build dbt models and tables, document runbooks, and serve as backup for core warehouse operations while collaborating with engineering and IT.

Lead development of enterprise data and analytics systems using Snowflake and Python. Build and optimize data pipelines on AWS (Lambda, Step Functions, ECS), write advanced SQL, and apply domain knowledge of asset management and financial markets.

Lead design and scaling of ELT pipelines and analytics schemas on Snowflake. Build Looker views, CI/CD automation, and orchestration workflows (Prefect/Airflow). Ensure production reliability with monitoring (Datadog, Monte Carlo), partner with cross-functional teams, and provide technical leadership including code reviews, testing, and end-to-end ownership of data integrity and platform trustworthiness.

Leads and develops a data engineering team implementing data integrations for partner campuses. Owns implementation approaches, scalable delivery processes, data mapping, validation, reconciliation, quality controls, project health, and capacity planning. Partners with Product, Launch, and Partner Success teams to resolve technical and partner challenges, improve integrations, and support adoption. Provides technical mentorship, design and code reviews, stakeholder communication, and continuous process improvement.

Own and improve Vanta’s engineering, product, and design data systems by onboarding signal sources, standardizing data at ingestion, mitigating failure modes, and ensuring information is trustworthy and queryable. Build pipelines, internal tools, prototypes, and AI-enabled solutions; replace manual processes with engineering controls; collaborate with data producers and consumers; and help teammates develop their technical building skills.

Analyze datasets to generate reports and visualizations that inform business decisions. Produce regular reporting, create data visualizations, and work cross-functionally to support data-driven strategies with attention to accuracy.

Leads the strategy, architecture, and execution of an enterprise data platform supporting analytics, machine learning, operational systems, and AI applications. Manages and mentors data platform engineers while remaining hands-on with architecture, reliability, technical direction, and troubleshooting. Oversees pipelines, orchestration, governance, security, observability, data contracts, migrations, and platform operations. Partners cross-functionally to translate business needs into scalable technical solutions and communicates decisions to technical and non-technical stakeholders.

Organise and curate large amounts of raw material: extract key points from transcripts, collate and maintain clean spreadsheets, tag and categorise links and documents, and create findable information structures following or suggesting systems.

Leads data engineering strategy, architecture, delivery, support, and lifecycle management for secure, scalable cloud and hosted data solutions. Collaborates with technical and business stakeholders to deliver complex datasets, establish enterprise data standards, manage data engineering teams, and oversee maintenance, change management, capacity planning, business continuity, disaster recovery, and regulatory security requirements. The role also evaluates third-party tools and supports Azure DevOps, SDLC, CI/CD, and technical innovation.

Design, build, and optimize scalable cloud data pipelines and infrastructure. Maintain and refactor SQL and ETL processes, automate data workflows, ensure data quality/security, and troubleshoot complex issues. Provide technical leadership and mentor junior engineers while collaborating with stakeholders to translate requirements.