Top Data Engineer Jobs in Cleveland, OH

As a Data Engineer, you will design and maintain data pipelines, build data storage systems, and support analytics workflows, ensuring data reliability and performance. You will collaborate with engineers to define data structures and improve data management practices.

The Senior Data Engineer at Unchained will design and implement data pipelines, integrate APIs, ensure data governance, and mentor team members while focusing on accuracy and security.

Lead design and implementation of shared, reusable analytics data models and pipelines. Drive standardization, governance, observability, and CI/CD for analytics; partner with Data Science, Infrastructure, and Product to certify metrics, modernize orchestration, and integrate AI-native tooling.

As a Data Engineer, you will build and optimize data pipelines, ensuring accurate data delivery that informs pricing and market analytics at Alt.

The Data Engineer will build and maintain data pipelines, optimize queries, collaborate with teams, and ensure data quality across Google Cloud systems.

The Data Engineer will design and maintain data models on Snowflake, enforce data standards, manage security, optimize SQL, implement CI/CD, and mentor junior staff.

The job involves leveraging AWS and Snowflake for data engineering tasks within a technology-focused company, requiring US residency.

Design, develop, and manage data infrastructure for internal and client projects, focusing on large-scale data pipelines, APIs, and cloud deployments.

The Lead Data Consultant will design and deliver scalable data solutions, manage project teams, and optimize client data environments, ensuring effective project execution and communication.

Lead design and implementation of a unified event-tracking data platform. Collaborate with Data, Product, and Engineering to build reusable event-publishing frameworks, monitoring/alerting, and deprecate legacy systems. Coach mid-level engineers, influence roadmap and processes, manage cloud/SaaS spend, create documentation, and participate in on-call rotations to ensure platform reliability and data trustworthiness.

The Data Engineer will build and optimize data pipelines, manage data flow, and collaborate with Analytics and Business teams to support data-driven insights and systems.

The Data Engineer will design and maintain ETL pipelines and data storage solutions, collaborating with cross-functional teams to ensure efficient data processing and delivery.

The Data Engineer will build and maintain data infrastructure, design data pipelines, and develop reusable frameworks, leveraging technologies like Azure Databricks and PySpark for data processing and transformation.

The Data Engineer will enhance the Enterprise Data Warehouse, modernizing ETL processes, optimizing data transformations, ensuring data quality, and providing production support while collaborating with cross-functional teams.

Design, build, and operate Spark-based ETL pipelines on AWS. Collaborate with stakeholders to deliver reliable data products, ensure data quality and governance, optimize performance, and maintain operational excellence of the data platform.

Lead design and implementation of scalable, HIPAA-compliant data pipelines and platforms for healthcare ML. Build ETL, orchestration, and tooling for processing EHR, claims, pharmacy, and bioinformatics data; collaborate with data scientists to produce modeling-ready datasets and ensure data quality, reliability, and operational excellence.

Design, build, and optimize distributed query solutions using Starburst/Trino. Enable secure, governed data access across cloud and on-premises sources, implement data federation and query optimization, support IAM and governance in a federal environment, develop backend services and CI/CD, and troubleshoot performance in cloud-native systems.

Design, build, monitor, and optimize large-scale ETL/ELT data pipelines and data architecture. Integrate data sources, support analysts and data scientists, automate processes, ensure reliable data delivery, and write maintainable code.

The Data Engineer will manage data extraction pipelines, modernize data systems, implement monitoring tools, optimize workflows, and support compliance requirements using various tools and platforms.

As a Data Engineer, you will build and optimize data pipelines, manage ETL workflows, and ensure efficient data access and quality within the infrastructure.

The GTM Data Engineer designs and manages a customer and revenue data foundation, ensuring data quality and availability for Marketing, Sales, and Customer Success teams, while overseeing data integration and reporting.

Build and operate scalable data pipelines and analytics-ready datasets using Python, dbt, and BigQuery. Develop Looker dashboards, ensure data quality and observability, optimize performance and cost, integrate data workflows with backend services and CI/CD, and support analytics, experimentation, and production use cases.

Design, implement, optimize, and maintain scalable, high-availability database solutions for a SaaS healthcare product. Integrate client data, resolve complex data issues, refactor systems for Azure, optimize MSSQL performance, participate in code reviews, and deliver features within Agile/Scrum to ensure reliable, high-performance data services.

Lead design and delivery of enterprise data centralization and automation for reporting and BI. Build and maintain ETL/SSIS pipelines, data orchestration, file delivery and quality controls, follow SDLC/agile, mentor junior engineers, and partner with business stakeholders to capture requirements and ensure timely data delivery.

Lead modernization of core data systems and build scalable, secure data pipelines for cloud and on‑prem environments. Design data contracts, observability, lineage, and real‑time processing for vulnerability management. Partner with product and leadership to align data strategy and deliver customer-facing data solutions.