Top Remote Analysis Reporting Jobs in Columbus, OH

Supports healthcare data analytics and research projects by evaluating diverse datasets, developing statistical models, validating and cross-referencing data, analyzing care and outcome patterns, and communicating findings to nontechnical stakeholders and clients. The role includes learning healthcare data types, SAS programming, research design methods, and quality improvement analytics while collaborating across multiple teams and managing concurrent projects.

Designs enterprise Power BI semantic models and executive dashboards, translating ambiguous business questions into KPIs and visual narratives. Integrates data from enterprise sources, improves data quality with engineering teams, and establishes governance for accurate, auditable reporting. Mentors BI professionals, defines modeling and metric standards, optimizes performance and scalability, and influences senior stakeholders through trusted insights.

Design, build, and maintain scalable Snowflake data pipelines and workflows. Ingest, transform, and deliver data from EHRs, claims, APIs, and CRM systems into analytics-ready structures. Optimize Snowflake performance and costs through warehouse sizing, query tuning, data modeling, and security design. Implement orchestration, DevOps, version control, and CI/CD practices while collaborating with client architects and analysts. The role also involves explaining technical tradeoffs, supporting repeatable deployments, adapting to unfamiliar challenges, and mentoring others.

Document and reverse-engineer the client's ServiceNow data model and ITSM/CMDB processes. Design API-based incremental extraction into a Bronze layer and specify Bronze->Silver->Gold mappings. Define DNA crosswalk keys, data-quality gates and KPI confidence scoring, and support pipeline development, observability, and automated testing for ServiceNow as a source system.

Reverse-engineer Procore data model and REST APIs; map Bronze→Silver→Gold datasets with transformation rules and data-quality defects; define crosswalk keys (global Project ID) reconciling Procore, P6, and Yardi; define data-quality gates and confidence scoring; support pipeline development and automated testing; validate Gold datasets against sources and document a reusable template.

Inventory and reverse-engineer M365 and Power Platform workloads to document entities and process flows; produce Bronze->Silver->Gold source-to-target mappings with transformation rules and data-quality defects; reconcile identifiers against core systems; ensure secure extraction per sensitivity and retention policies; define data-quality gates and confidence scoring; and support pipeline development, automated testing, and validation of Gold outputs.

Lead Wpromote’s Reporting Solutions team and strategy, overseeing client-facing BI and analytics products from requirements through production. Drive the shift from bespoke dashboards to scalable, reusable reporting experiences across client verticals. Partner with Data Engineering, Product, Analytics, Media, and clients on data models, metrics, visualization, UX, quality, and roadmap decisions. Guide innovation in self-service analytics, interactive applications, AI-enabled reporting, and conversational analytics while managing team development, prioritization, standards, and stakeholder communication.

Leads data engineering for LillyDirect’s patient analytics platform, designing privacy-first ingestion pipelines, tokenization, identity resolution, consent governance, semantic layers, and analytics-ready data products. Integrates pharmacy and prescription data across enterprise systems while ensuring HIPAA compliance, data quality, governed access, and consent revocation. Partners with product, pharmacy, privacy, legal, cybersecurity, and analytics teams to translate requirements into scalable solutions supporting BI, reporting, self-service analytics, and agentic AI.

Lead data analysis for product and customer decision-making by defining metrics, measuring adoption, engagement, retention, and customer health, and translating complex data into actionable insights. Partner with product, engineering, customer success, and sales teams; automate and improve data processes; support product strategy and customer reviews; strengthen data governance; and mentor analysts.

Lead and develop Analytics Engineers responsible for shared data foundations, platform capabilities, semantic models, developer tooling, and AI-enabled workflows. Define the team vision, operating model, roadmap, standards, and success measures. Partner cross-functionally to prioritize initiatives, improve adoption, guide architecture, and deliver scalable data assets and automation. Drive responsible AI-assisted development, data reliability, testing, documentation, observability, and cost management while contributing hands-on when needed.

Leads enterprise data engineering and platform execution, including modernization roadmaps, cloud transformation, governance, reliability, operational excellence, budgets, vendors, and investment prioritization. Directs multiple engineering managers and teams across platform engineering, data engineering, integration, and operations. Partners with architecture, security, compliance, analytics, clinical, product, finance, and business leaders to deliver secure, scalable, resilient data capabilities supporting AI, interoperability, reporting, and digital transformation.

Design, build, and maintain data pipelines, ingestion and transformation workflows, SQL-based processes, data models, and cloud data infrastructure for a B2B SaaS analytics platform. Monitor pipeline performance and data quality, troubleshoot failures, document data architecture and business logic, and collaborate with engineering, product, and analytics stakeholders.