Top Senior Data & Analytics Jobs in Cleveland, OH

Design, optimize, and scale Snowflake-based data architecture and pipelines. Implement data observability, operationalize MLOps, build semantic enterprise models, and deploy AI-assisted agents and automation for production analytics and commercial data products. Share cross-functional ownership for pipeline resilience, monitoring, and model lifecycle management.

The Sr. Director of Enterprise Measurement will lead performance measurement strategy, ensuring metrics are standardized and integrated within decision-making processes across teams, driving growth and actionable insights.

As a Senior Forward Deployed Data Engineer, you will design and implement data pipelines for media agency clients, manage technical delivery, and ensure data security while mentoring junior engineers and communicating effectively with stakeholders.

Design, build, and operate production-grade data ingestion pipelines and dbt transformations into a Databricks lakehouse. Establish data quality, monitoring, and observability. Partner with Product and Engineering to enable metrics, dashboards, and longitudinal patient analytics supporting clinical and operational decision-making.

The Senior Data Scientist will lead innovative data science efforts, leveraging advanced analytics, visualization, and insights from complex datasets to boost productivity.

The Sr. Data Engineer - Databricks designs and maintains scalable data solutions using Apache Spark and Databricks, ensuring data quality and performance for analytics and reporting.

Design and deliver scalable Power BI data models, dashboards, and reporting solutions. Collaborate with stakeholders, establish visualization governance and best practices, prototype solutions, and own projects end-to-end to enable data-driven decisions across healthcare teams.

The Staff Data Analyst will enhance data usage for strategic decisions, architect scalable models, partner across teams on data solutions, and lead analytics engineering standards.

Design and implement data infrastructure and pipelines, ensuring reliability and quality. Collaborate with teams for data solutions and optimize processes. Coach junior engineers.

Build and maintain automated ETL/ELT data pipelines, improve data quality and monitoring, optimize Postgres and BigQuery schemas and queries, develop internal tooling, support data governance (HIPAA), participate in on-call rotation, and collaborate across engineering teams to scale data systems.