Top Remote Data Engineering Jobs in Lexington, KY

Design and enhance data management and analytics functions, build data assets, establish engineering standards, and enable self-service data access for analytics at Danaher.

Lead architecture and hands-on engineering to design, scale, and govern a cloud-native lakehouse using Databricks and Microsoft Fabric. Build batch/streaming pipelines, ensure HIPAA-compliant PHI handling, produce analytics-ready datasets, mentor engineers, and drive platform strategy, governance, and reliability.

As an AI Engineer, you'll work closely with customers to understand their needs, train and deploy models, and build scalable AI systems.

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.

Ensure timely, high-quality data conversions from legacy systems to new platforms. Work with Implementation Specialists and Project Managers to execute conversion tasks, validate data integrity, troubleshoot issues, support deployments, and assist scheduling and customer communications.

The Energy Analyst will enhance data systems for market data utilization, collaborating with engineers to improve data handling and quality assurance processes, driven by a passion for clean energy.

The role involves architecting data solutions, building data products in Snowflake, establishing data standards, and enabling self-service data access while ensuring data quality and compliance.

Lead legacy-to-SaaS data migrations: design and execute ETL, extract/transform/load data, validate integrity, map business workflows to target models, engage clients, document processes, support governance, and train stakeholders to ensure accurate, secure conversions.

The Database Administrator will manage Oracle Banner ERPs, supporting installations, upgrades, and configurations while ensuring database security and performance.

The Data Engineer will build and maintain data pipelines, ensuring high-quality and scalable data systems while working on analytics and machine learning accessibility.