Top Remote Data Engineering Jobs

The Data Architect will lead database management, conduct data analysis, and work with stakeholders to align data requirements with business objectives.

The role involves engineering consumer-level attributes, applying statistical techniques, building dashboards, and collaborating with various teams to enhance credit-related decisions based on data insights.

As a Senior Data Engineer, you will build and optimize data pipelines, integrate AI capabilities, and collaborate across teams to create data-driven solutions, while providing technical leadership and ensuring data quality and governance.

The Manager of Data Engineering will lead the data engineering team, oversee data pipeline design and implementation, manage data governance, and ensure data quality while driving team professional growth.

Develop custom R programming code for PK/PD analyses, ensuring data quality and compliance with CDISC standards while training others and improving programming tools.

As a Data Conversion Specialist, you will manage data extraction, transformation, and loading for client migrations to improveit 360 or MarketSharp, ensuring accuracy, timely conversion, and customer satisfaction.

Lead the architecture and design of an operational data platform, focusing on data unification, streaming integrations, governance, and mentoring teams while ensuring HIPAA compliance.

The Senior Data Engineer will design and develop scalable data architectures, manage ETL processes, optimize databases, and implement MLOps pipelines, promoting data-driven decision-making across the organization.

As a Senior Data & Analytics Engineer, you'll lead data initiatives, manage a team, and ensure data quality while turning insights into actionable decisions across the company.

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.