Top Remote Data Engineering Jobs

Manage leased partner network data integration into I-Network, ensure data quality and delivery for client claims systems and regulatory filing, support SFTP access, create requirements and QA sign-off for projects, produce analytical insights, mentor team members, and assist Business Development/National Accounts and project management.

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.

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.

Lead design and delivery of Databricks-based Lakehouse solutions and end-to-end data engineering projects. Build and optimize ETL, streaming and batch pipelines, integrate cloud and on-prem systems, mentor team members, support pre-sales, and ensure governance, security, and platform performance.

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.

Design, build, and operate GTM data pipelines, a unified data lake, and enrichment workflows using cloud data infra, LLMs, and orchestration tools to enable segmentation, ICP scoring, and revenue analytics.

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.