Top Remote Data & Analytics Jobs in Columbus, OH

Build and own Snout’s data foundation, including PostgreSQL and dbt warehouses, ingestion pipelines, dimensional models, data quality, documentation, and reliable rebuilds. Reconcile data from veterinary practice-management systems, support LLM/AI tooling, translate stakeholder needs into technical plans, and establish the foundation for a future data team and analyst.

Develop and maintain BI reports and dashboards for the Mortgage Lending Division. Analyze large datasets, identify trends, validate reportable data, and support regulatory reporting such as HMDA and Fair Lending Analysis. Collaborate with business teams to gather requirements, automate reporting processes, document data definitions, and provide training on reporting tools. The role also supports data dictionaries, exception reporting, and operational improvements.

Leads data product engineering across Natera’s data platform, building certified, AI-ready analytics products and self-service experiences. Establishes standards, golden paths, data quality, governance, observability, and measurable delivery practices across domains. Drives AI-native engineering, agentic development, and productivity improvements while hiring and developing engineering teams. Requires hands-on technical leadership across Python, SQL, dbt, Snowflake, AWS, orchestration, and regulated healthcare data environments.

Develop and maintain Power BI, SSRS, SQL, recurring, and ad hoc reports for the Mortgage Lending Division. Analyze large datasets, validate regulatory reporting data, identify trends, automate reporting, and provide actionable insights. Collaborate with business units, support HMDA and fair lending reporting, document data dictionaries and procedures, and train users on reporting tools.

Administers and secures Oracle databases supporting DISA contract systems. Responsibilities include database installation, tuning, access management, outage response, disaster recovery, security patching, STIG compliance, scripting, release support, data modeling, legacy data migration, reconciliation, and system integration. The role also supports Appian data stores and coordinates database changes with DISA, hosting providers, ISSOs, and development teams.

Build and maintain SQL-based marketing analytics infrastructure, data models, dashboards, and reporting. Analyze marketing channels, affiliates, conversion funnels, cohorts, revenue, profitability, and partner performance. Translate complex findings into actionable recommendations for budget allocation and optimization. Ensure data quality, governance, documentation, and metric consistency while partnering cross-functionally with Marketing, Sales, Finance, Operations, Product, and Technology. The role is a hands-on individual contributor with potential responsibility for mentoring or managing one analyst.

Leads enterprise data engineering strategy and architecture, designing scalable cloud data platforms, pipelines, models, governance, and AI-assisted engineering solutions. Establishes technical standards, security, observability, and reusable frameworks; influences architecture decisions across teams without direct management. Mentors senior engineers, partners with business and technical stakeholders, and remains hands-on with cloud technologies, software architecture, data modeling, and platform design.

Own go-to-market funnel reporting, dashboards, data quality, and analysis for Sales, Marketing, and RevOps. Integrate CRM and marketing data, monitor lead scoring and attribution models, investigate funnel performance, identify root causes, and provide actionable recommendations. Maintain reporting systems, audit data hygiene and tool adoption, and communicate insights clearly to non-technical stakeholders in a remote-first SaaS environment.

Leads analytics, data architecture, outcomes measurement, health economics and outcomes research, ROI modeling, governance, and client reporting. Manages a multidisciplinary data team and partners with Engineering, Product, executives, and payer stakeholders to translate clinical and financial evidence into actionable decisions. Oversees accurate, repeatable analyses and communicates findings through dashboards, white papers, presentations, and impact briefs.

Leads analytics, reporting, data modeling, automation, AI-agent development, and quality assurance for revenue cycle operations. Creates Power BI and Excel reports, analyzes complex healthcare and operational datasets, develops scalable warehouse models, and delivers actionable insights to leadership. Uses SQL, cloud data platforms, Git, Python, and AI-assisted tools to improve reporting efficiency, accuracy, and decision support.