Top Remote Data Engineering Jobs

Lead design, build, and optimization of a Snowflake-centric cloud data platform and dbt transformation layers. Develop reliable pipelines from sources like Salesforce, ensure data quality, performance tuning, and compliance with PHI/PII/HIPAA. Collaborate with analytics, product, and engineering teams to deliver scalable, documented, analytics-ready datasets and platform standards.

Design and implement end-to-end data and analytics solutions using Microsoft Fabric and Azure. Lead data modeling, ETL pipelines, BI reporting (Power BI), data governance, and performance optimization. Collaborate with stakeholders, provide technical leadership, and deliver scalable, secure data platforms to support business insights and decision-making.

Lead data conversion processes, provide expert guidance on Oracle Cloud, and ensure the successful implementation of conversion solutions while collaborating with stakeholders.

Design and develop simulation frameworks for backtesting trading strategies, while collaborating with quantitative researchers on new trading ideas.

The Marketing Data Scientist will analyze data, onboard clients, develop data pipelines in R, and propose improvements to enhance efficiency.

Lead the design and architecture of production-grade data systems for reporting, focusing on data quality, performance, and engineering standards while mentoring team members.

As the GTM Engineer, you'll build Mento's revenue systems, automate workflows, clean data, and collaborate with sales and marketing teams to drive revenue growth.

The Solutions Architect oversees project architecture and delivery, acts as a product liaison, and contributes to the professional services development for Trimble's Construction One platform.

The Senior Data Engineer will focus on Data Modeling, utilizing SQL, Snowflake, and Apache Airflow to develop efficient data models and deliver data products.

Design, build, and maintain production data pipelines and tooling (CI/CD, testing, validation) using Snowflake, dbt, and orchestration tools. Model, transform, document, and optimize data to produce reliable curated datasets for analytics and solutions, enforce engineering best practices, and mentor teammates while ensuring scalability, observability, and data integrity.