Top Analysis Reporting Jobs in Dayton, OH

Drive Data Governance requirements, analyze and validate data, collaborate with stakeholders, and maintain Data Governance artifacts using SQL and Informatica tools.

The Data and Reporting Architect will lead the design of data architectures and reporting systems, addressing complex data challenges and ensuring compliance with regulatory standards. Responsibilities include mentoring engineers, defining data quality frameworks, and collaborating with various teams to implement scalable solutions.

Design, develop, and optimize Tableau dashboards and data sources on Redshift; collaborate with data engineering (dbt) and business teams; own Tableau governance, performance tuning, documentation, training, and ensure data security compliance.

Partner with customers and sales to design and present scalable Databricks Lakehouse architectures, build reference architectures and demos, consult on big data, ETL, and ML projects, validate integrations, and drive technical wins and adoption across accounts.

The Data Solutions Architect at MANSCAPED will manage the enterprise data architecture, ensure security and scalability, and support BI reporting and advanced analytics.

Lead GTM strategy and analytics to build headcount/capacity models, territory optimization, quota setting, predictive models, and BI reporting. Partner with Sales, Marketing, Finance, and Data to inform planning cycles, monitor pipeline and productivity, and deliver executive-level insights for growth and investment decisions.

Serve as the analytics bridge between marketing/operations and data teams: translate business questions and KPIs into clear product requirements, own delivery of treated tables, semantic layers, reports and dashboards, align stakeholders on a single source of truth, run gap analyses, document processes, and ensure delivered data products drive decision-making and adoption.

Support a core set of clients by guiding users on Numerator's Insights platform, performing ad-hoc/custom analyses using proprietary consumer panel data, delivering actionable analytic insights and recommendations, and presenting findings across channels including industry forums and written content.

Build and maintain scalable ETL/data pipelines and internal frameworks to support ML and product teams. Drive architecture, observability, data quality, and engineering best practices across AI/ML workflows and prompt-engineering pipelines.

Build governed gold-layer data models and a single-source metrics layer in Snowflake (dbt); create and optimize dashboards in enterprise BI tools; use AI coding agents and AI-assisted tooling to accelerate development; ensure data quality, governance, and consistency; collaborate with data engineering and stakeholders to deliver trusted analytics for internal and client-facing use.