Top Senior Data & Analytics Jobs in Columbus, OH

Build, operate, and improve Tala’s production data synchronization and change data capture pipelines across global markets. Deliver reliable, low-latency data to Snowflake using AWS, Kafka, Spark Structured Streaming, and lakehouse technologies. Improve scalability, performance, cost efficiency, data quality, monitoring, testing, CI/CD, and infrastructure as code. Troubleshoot incidents, lead root-cause analyses, document operational practices, contribute to architecture decisions, and collaborate with data, analytics, product, credit, and business teams.

Designs, builds, and optimizes enterprise data pipelines, warehouses, lakes, semantic models, and ETL/ELT solutions. Develops SQL and Power BI solutions, leads data modeling, ensures data quality and governance, resolves performance issues, and contributes to data architecture. Collaborates with HR stakeholders, analysts, data scientists, and technology teams to deliver scalable analytics and reporting platforms.

Build and maintain dbt SQL models, data pipelines, curated datasets, reports, and dashboards supporting state partners, customers, Finance, Operations, and executives. Own external and internal Metabase environments, support the data warehouse, and establish consistent metric definitions across technical and non-technical teams. The role also requires analytics support, stakeholder communication, and experience with Airflow, Python, and Git-based workflows.

Analyzes site performance data, identifies KPI root causes, synthesizes field feedback, and develops actionable recommendations for a multi-year SAP S/4HANA transformation. The role prepares executive reporting for Steering Committee, sponsor, and stage-gate reviews; tracks value realization; designs reporting templates, data models, and recurring tracking mechanisms; and supports leadership decision-making. It partners with field and business stakeholders and may guide analysts without formal supervisory responsibility.

Leads the enterprise business intelligence and analytics strategy, manages BI and data analysts, and oversees analytics roadmaps, projects, platforms, dashboards, and vendor relationships. Translates complex data into actionable financial and business insights, supports SAP and Power BI platform upgrades, manages delivery timelines and resources, and coaches team members. The role also drives stakeholder engagement, continuous improvement, talent development, and data-driven decision-making across the organization.

Analyze personal loan product performance, customer behavior, funnel conversion, campaigns, and key performance metrics. Design measurement frameworks, identify tracking gaps, conduct root cause analysis, develop A/B tests, support analytics infrastructure, and create dashboards. Partner with Product, Engineering, Data Science, and Business teams to translate insights into product improvements and increased origination volume.

Analyzes complex business data to identify trends, develop models, dashboards, and actionable insights. Collaborates with leaders and cross-functional teams, supports data governance, validates data integrity, applies statistical and predictive techniques, and communicates findings to technical and non-technical audiences. Provides mentorship to junior analysts and may lead projects. Occasional business travel may be required.

Lead advanced Amazon and commerce analytics using Amazon Marketing Cloud, advertising, and retail data. Build queries, dashboards, reports, tests, forecasts, and actionable client-ready recommendations. Partner with client, media, operations, data science, and reporting teams to support investment, optimization, and retail decisions. Ensure analytical quality, documentation, automation, and measurement rigor while identifying growth opportunities and communicating technical insights to clients.

The Senior Data Analyst will support Growth and Product teams through paid-channel analysis, user journey optimization, activation and retention insights, and churn reduction. Responsibilities include developing experiments, analyzing ad network performance, improving tracking and instrumentation, ensuring data quality, and enabling self-service analytics. The role requires translating complex data into actionable recommendations and communicating effectively across technical and non-technical teams in a fast-paced SaaS environment.

Design, build, and optimize enterprise ETL/ELT pipelines, cloud data lakes, lakehouse solutions, data models, and semantic layers across AWS and Azure. Ensure data quality, security, performance, reliability, and governance while supporting analytics, reporting, and AI initiatives. Collaborate with product, engineering, IT, and business stakeholders to translate requirements into scalable data solutions, monitor pipeline health, troubleshoot issues, and improve data architecture and practices.

Own Step’s analytics data models, transformation pipelines, metric definitions, semantic layer, and data quality practices. Partner with Product, Marketing, Engineering, Risk, Growth, and Finance to establish trustworthy data foundations and enable self-service analysis. Build reusable query, visualization, and code components; apply AI-augmented workflows; and collaborate with data scientists, analysts, and platform engineers. The role requires strong SQL, modeling, pipeline, BI, communication, and independent ownership skills, with occasional travel for team onsites.