Top Remote Analysis Reporting Jobs in Columbus, OH

Architects and leads enterprise data engineering platforms, including scalable ETL/ELT pipelines, streaming frameworks, cloud infrastructure, data warehouses, and AI/ML data systems. Establishes engineering standards, governance, monitoring, data quality, security, and schema management practices. Designs AI agents using LLMs, partners across business and infrastructure teams, and makes high-impact architectural decisions for reliable, secure, multi-region data environments.

Analyze market, customer, sales, pricing, and operational data to generate insights and support strategic decisions. The role includes pricing guidance, deal approvals, sales training, contract and vendor compliance, revenue forecasting, reporting, process automation, and special projects. The analyst will collaborate with Finance and cross-functional teams to identify growth opportunities, improve performance, and address business challenges.

Analyzes complex program data across Family and Youth Peer Support Services, ensuring data quality, managing reporting systems, developing dashboards and performance reports, identifying trends, and delivering actionable insights. The role coordinates cross-site reporting, supports data collection and process improvement, presents findings to leadership and external stakeholders, and provides technical guidance and training to program staff.

Designs, builds, secures, monitors, and supports scalable data platforms across public and multi-cloud environments. Develops batch and streaming pipelines, ELT processes, data lakes, warehouses, APIs, and integrations with transactional systems. Works with SQL and NoSQL databases and technologies including Spark, Hadoop, Databricks, Snowflake, Kinesis, and Lambda. Leads projects, presents to leadership, collaborates with clients and Scrum teams, troubleshoots issues, and enables analytics and machine learning initiatives.

Designs and oversees enterprise data architectures spanning databases, warehouses, lakes, integrations, and cloud environments. Translates business requirements into scalable, secure, and cost-efficient solutions; establishes data modeling, governance, quality, metadata, and security practices; guides engineers and analysts; optimizes infrastructure; and maintains architecture documentation. Requires extensive Databricks, data engineering, big data, cloud, and stakeholder leadership experience.

Lead data strategy and execution for emerging sectors, transforming large consumer datasets into accurate, scalable client insights. Responsibilities include resolving data-quality issues, designing workflows, maintaining sector taxonomies, partnering with product, revenue, engineering, and insights teams, and coaching analysts. The role requires hands-on analysis, production-grade data workflow development, stakeholder communication, and ownership of quality standards and methodologies in a rapidly evolving environment.

Analyzes business and system requirements, translates them into functional designs, and supports technology enhancements and quality initiatives. Collaborates with stakeholders on project scope, timelines, testing, demos, and implementation. Monitors system usage, investigates errors and exceptions, assists with UAT, tracks project progress, communicates risks, and serves as a technology subject matter expert within the mortgage and secondary market domain.

Lead technical design and hands-on development of Pantheon’s data platform, extending ingestion, curation, retention services and ML/LLM infrastructure. Mentor engineers, drive architecture and engineering standards, operate in a DevOps model, partner cross-functionally, and participate in on-call support to ensure reliable, compliant data access and analytics.

Own and evolve UJET’s data platform, including MySQL CDC replication to BigQuery, dbt transformations, Terraform infrastructure, pipelines, data quality, observability, and Looker models. Build reliable, analytics-ready datasets and trusted metrics for internal and customer-facing reporting. Partner with Analytics, Finance, Product, and Engineering to deliver scalable data solutions, improve platform reliability, optimize performance and costs, and establish development standards and guardrails.

Design, implement, and maintain data pipelines, integrations, and data architecture using Snowflake and related tools. Support insurance-sector consulting engagements by analyzing data, developing solutions, troubleshooting engineering issues, and presenting recommendations to clients. Collaborate with cross-functional stakeholders, apply data governance and quality practices, and contribute to multiple initiatives. The role requires consulting experience, financial services knowledge, strong communication, and travel of up to 75%.