Remote Data Jobs • Spark

As the Senior Data Engineer on our team, you will take ownership of designing and scaling the systems and pipelines that power H1’s data platform. This role involves working cross-functionally with engineers, product managers, and stakeholders to deliver high-performance, reliable, and maintainable data solutions. Play a key role in shaping the future of our data infrastructure while mentoring others and driving best practices.

In this role, you will be responsible for designing, developing, and maintaining scalable data pipelines and systems to support a wide range of analytics and business intelligence solutions. You will work closely with cross-functional teams including data scientists, analysts, and engineers to provide data solutions that drive key business decisions.

Join our platform engineering team as a Data Engineer, where you will design, build, and maintain data pipelines and infrastructure that power our analytics and product features. This role requires a blend of strategic vision and hands-on technical skills. You will play a key role in shaping the foundation of Prepared’s engineering culture.

Design, develop, test, deploy, maintain, and improve data systems and services. Perform code reviews and collaborate with peers on software solutions. Collaborate with engineers and product managers to understand data needs. Participate in Agile ceremonies and troubleshoot and fix production issues as they occur. Collaborative with the technical team to solve complex technical and design issues.

This role is ideal for someone who enjoys working across high-volume telemetry sources, optimizing data workflows, and solving schema drift challenges in real-world distributed environments. You’ll be part of the Security Data Platform and ML Engineering team, helping to onboard and normalize security data that powers analytics, detection, and ML workflows across Adobe.

As a Senior Data Engineer, you’ll architect and maintain a highly flexible, enterprise-scale data warehouse that accelerates insights and minimizes redundant work. Leveraging deep expertise in data modeling, governance and Big Data technologies (Hadoop, Spark, Hive, etc.), you’ll design end-to-end ETL pipelines, optimize performance, and build metadata and quality monitoring frameworks.

As a Senior Data Engineer at Nearform your main task will be designing, building, and maintaining scalable data platforms, pipelines, and warehouses using SQL, Python, Spark, and other relevant technologies. You will play a key role in building efficient data solutions, optimizing performance, and ensuring seamless data integration. You'll also design, build, and optimize data pipelines and ETL processes for large-scale data ingestion and transformation.

The Client Services BI & Analytics team strives to create an open, trusting data culture where the cost of curiosity is as low as possible. This specialist role makes data available from new sources, builds robust data models, creates and optimizes data enrichment pipelines, and provides engineering support to specific projects. You will partner with our Data Visualizers and Solution Designers to ensure that data needed by the business is available and accurate and to develop certified data sets. This is a remote position.

This role involves leading the Data Solutions team, building and maintaining internal data products for analysts, data scientists, and product/business teams. You'll help democratize data at scale, enabling teams to generate business value through reliable, well-designed internal solutions covering the full data lifecycle, including ingestion, transformations, ML model development, and data serving.

Help shape the future of healthcare data as a Senior Data Engineer for Accompany Health. Collaborate across the organization with various teams, including Product, Sales, and Clinical Operations, to rewire health care, driving change in healthcare by building products to integrate fragmented healthcare services. Architect and own our data platform strategy, lead the design and implementation of scalable data infrastructure, and create data tools for analytics and data scientist team members.