Top Analysis Reporting Jobs in Dayton, OH

Design, build, and maintain Power BI dashboards and data models using Snowflake and other cloud sources. Collaborate with data engineers/ETL teams, gather stakeholder requirements, implement DAX and Power Query transformations, ensure data governance and performance, and deliver analytics within Agile processes.

Analyze enterprise KPI performance, build baselines and targets, run recurring KPI tracking, and translate findings into recommendations for Finance and program owners. Use modern analytical and AI-augmented platforms to produce defensible target-setting work, performance reads, and clear written and visual narratives that inform planning cycles.

Produce executive-grade briefs from cross-functional research and listening programs under compressed timelines. Shape questions, synthesize quantitative and qualitative evidence, craft recommendations and visuals for C-suite and Board, coach analysts, and track briefing-driven decisions to close the loop.

Design and manage VoC instruments and recurring feedback programs, ensure data quality, synthesize insights, and own the insights repository, decisions journal, and methodology library. Partner with VoC and KM vendors, run institutional-memory rituals (intake, closeout, handoffs), coach peers on VoC craft and documentation, and maintain taxonomy and metadata for enterprise-scale reuse.

Bridge enterprise customers' legacy BI to Hightouch by reverse-engineering complex marketing reports, building reusable reporting frameworks, engineering and documenting semantic/context layers, ensuring accurate SQL generation, and training non-technical marketers while collaborating cross-functionally to deliver reliable, idempotent AI-driven analytics.

Build and maintain large-scale data processing pipelines using Apache Spark (PySpark/Scala) and Python. Design ETL workflows, implement distributed data processing, use version control (Git), and work with cloud platforms (GCP/AWS/Azure).

Design and maintain scalable dbt data models and Looker dashboards; partner with Finance, Product, and GTM to translate requirements into analytics solutions; ensure data quality with Data Engineering; perform analyses, forecasting, and QA to deliver trusted reporting and drive analytics initiatives.

Lead client-facing Data & Analytics engagements across pre-sales, architecture, and delivery. Define strategy, roadmaps, solution designs, and SOWs for modern data platforms, pipelines, governance, analytics, and AI enablement. Drive practice development, create reusable IP, mentor teams, and ensure quality delivery and strong business outcomes.

Design, build, and maintain dbt data models and scalable ELT pipelines; optimize performance-aware SQL on Snowflake; ensure observability, testing, and CI/CD; partner with product and engineering teams to meet analytic needs, mentor engineers, document business logic, and troubleshoot ingestion, transformation, and warehouse issues.

As a Sr. Staff Deployment Strategist, you will drive business transformation by partnering with clients to design and implement AI-powered data intelligence solutions, ensuring value realization and client integration.

Support a Department of State data engineering program: review data policies and governance, define requirements, build and maintain Palantir-based data pipelines, clean and integrate datasets, detect and remediate data fidelity and pipeline issues, produce analyses and visualizations, and coordinate with non-technical users and stakeholders.

Drive enterprise automation by identifying workflow inefficiencies across Home Health, Primary Care, and Pharmacy. Use data analysis, process and journey mapping, and MDM to define opportunities and leading indicators. Partner with product, engineering, clinical, compliance, and operations to design, validate, and scale AI-enabled automation solutions that improve outcomes and efficiency while ensuring regulatory compliance.