Top Remote Data Engineering Jobs in Lexington, KY

Lead end-to-end data science initiatives: design, deploy, and monitor production ML models for credit risk, pricing, collections, and fraud. Partner cross-functionally to integrate models, set development standards, mentor team members, and maintain reliable, scalable machine learning pipelines and monitoring systems.

Lead the ML Data Enablement team to define strategy and execution for accelerating third-party and internal data onboarding, enforce data quality and SLAs, build metadata and lineage standards, and deliver scalable data infrastructure and workflows to reduce time-to-production for ML models.

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 Business Systems Specialist will support data conversion, collaborate with IT and Operations teams, and ensure successful data integration across various business lines.

The Snowflake Data Consultant will lead the modernization of data models from Oracle to Snowflake, focusing on performance and scalability while managing complex migrations and collaborating with teams.

The Data Engineer role involves designing, implementing, and optimizing data infrastructure and pipelines on Azure, ensuring performance and compliance.

The Data Engineer I at Storable supports the design and maintenance of data pipelines, works with ETL processes, optimizes workflows, and collaborates with various teams to enhance data accessibility and reliability.

The Senior Data Engineer will develop data engineering solutions, manage ETL workflows, and establish a new data practice while collaborating with stakeholders.

Design and maintain data pipelines for analytics and operational decision-making. Collaborate with teams to ensure reliable data systems and governance, utilizing Python and SQL.

The DMS Data Engineer is responsible for analyzing raw data, building data systems and pipelines, conducting complex data analyses, and collaborating on projects to enhance data quality and reliability.