Top Senior Data Engineer Jobs in Cincinnati, OH

The Staff Data Engineer will enhance the data ecosystem at WeightWatchers by developing data pipelines, collaborating cross-functionally, and ensuring data quality while leading projects and technical initiatives.

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 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.

Design, build, and maintain data models, pipelines, and access layers to support care delivery, operations, and analytics. Ensure data quality, governance, and reliability while optimizing infrastructure and performance. Serve as a technical leader, review code, set engineering best practices, and collaborate cross-functionally to translate business needs into scalable data solutions.

Lead architecture and implementation of cloud-native data platforms on Google Cloud (BigQuery). Build unified batch/streaming pipelines, enforce IaC with Terraform, implement open table formats and governance (Dataplex/Data Catalog), automate data quality/lineage, partner with analytics and product teams, and mentor data engineers.

Responsible for designing, developing, and maintaining databases and ETL systems to support business applications and business intelligence. Collaborates with stakeholders to align business requirements and leads the design of automated solutions for operational efficiency.

The Principal Data Engineer will manage the analytics data architecture, engage cross-functionally, and create reliable data systems using Snowflake and Python on AWS.

Design and implement scalable data warehouse solutions integrating client data with the Ignite platform. Lead SQL Server to Databricks migrations, translate and optimize Spark SQL, build and maintain dbt data models, validate data quality, communicate status to stakeholders, and provide knowledge transfer and onboarding for client and internal teams.

The Data Architect/Data Governance Lead supports the Medicaid Enterprise Data Warehouse by leading data architecture, metadata management, and governance processes, ensuring compliance and scalability.

As a Sr. Data Engineer at Lyra Health, you will build and scale core data infrastructure, design data warehouses, and create efficient data pipelines while collaborating across departments.

The Senior Data Engineer leads the design and optimization of scalable data pipelines for AI-driven analytics while collaborating with cross-functional teams. Responsibilities include ensuring data integrity, automation, and compliance in cloud environments, particularly on Google Cloud Platform, to enhance decision-making processes.

In this role, you will design data architecture, lead integration strategies, mentor engineers, and drive AI infrastructure for cross-division data systems.

Lead the design of DataOps platforms, focusing on scalable data infrastructures and automation frameworks. Oversee robust data orchestration and establish quality frameworks.

Design, build, and automate scalable batch and streaming data pipelines, implement data models and ETL, automate deployments, support ML/experimentation, maintain server architecture, and partner with stakeholders to deliver analytics and data-driven tools.

As a Senior Data Engineer, you will design and maintain data warehouses, ensuring data quality, manage data transformations, and mentor others while partnering with various stakeholders.

As a Senior Data Engineer, you'll transform raw data into datasets, design production pipelines, integrate customer data, and collaborate with various teams to ensure data quality and reliability.

The Senior Data Engineer will design and implement lakehouse architectures, optimize ClickHouse deployments, develop ETL/ELT pipelines, and create data models to support analytical and operational functions.

Lead design and delivery of large-scale data pipelines and warehouse systems. Define technical strategy, enforce data governance, improve developer efficiency, mentor engineers, and align data engineering efforts with business goals to enable analytics and ML at scale.

Lead design and scaling of enterprise data architecture and pipelines. Build and maintain ETL/ELT and CDC/streaming workflows, improve data quality and observability, own schema and warehouse modeling, implement governance (RBAC), and provide cross-functional technical leadership to enable trusted, scalable data for analytics and product teams.

The Senior Data Engineer will design and build data pipelines and infrastructure to support data science and business intelligence solutions, utilizing AWS services and streaming technologies.

As a Senior Data Engineer, you'll define data ontology, collaborate with teams, design data pipelines, and optimize data infrastructures to support analytics for Yahoo Mail.

Build, maintain, and optimize cloud data pipelines and dbt models; design Airflow DAGs; implement dimensional models and BI dashboards; integrate healthcare data with HIPAA-compliant practices; contribute to RAG pipelines and MLOps workflows; review contractor code, monitor data quality, and document designs following governance standards.

Lead architecture and delivery of Boulevard's data platform, building foundational data models, pipelines, and customer-facing analytics. Collaborate with Product and Engineering to create scalable data products, Snowflake data sharing solutions, performant visualizations, and machine learning features (recommendations, forecasting, anomaly detection) to drive data-driven decision-making and product value.

As a Senior Data Engineer, you will design and optimize data pipelines, enhance system efficiency, and collaborate with teams to drive health outcomes using large healthcare datasets.