Top Remote Data Engineer Jobs

The Data Architect will design scalable data models, transform raw data into actionable insights, and deploy analytics solutions for healthcare providers, with a strong emphasis on SQL proficiency and cloud technologies.

As a Senior Data Engineer at Polymarket, you'll scale the data platform, manage analytics and serving layers, and ensure data correctness across teams.

Design and deliver scalable, reliable data services and microservices for real-time and batch processing. Build REST APIs, model data across SQL/NoSQL stores, drive data quality, own deployment/monitoring/incident response, set technical standards, and mentor engineers.

The role involves building and owning data pipelines, maintaining data quality, and creating reporting systems that provide insights to various teams. The candidate will also design AI-ready data infrastructure.

As the Senior Data Engineer for Enrichment, you'll design data pipelines, maintain contact datasets, ensure data quality, and optimize vendor relationships while working with a talented team.

Design and scale data infrastructure, ensure data quality and governance, collaborate with teams on data products, and modernize practices.

Design and maintain data systems for business-critical insights, connect data across platforms, build ETLs, and support business data decisions.

The Data Engineer builds and maintains data infrastructure, develops data pipelines, ensures data quality, and collaborates with teams for insights.

The Senior Data Analytics Engineer will develop data pipelines, support data-driven decision-making, collaborate with stakeholders, and improve data quality and processes.

As a Senior Data Engineer, you will design and maintain scalable data pipelines, focusing on architecture, ingestion, storage, and analytics on GCP. You'll collaborate with stakeholders and optimize data structures for performance while ensuring adherence to data governance and compliance standards.

Design, build, and own end-to-end data systems and pipelines powering payments, fraud response, and reporting. Implement streaming and batch integrations, APIs, and workflow orchestration. Define data correctness with monitoring, alerting, and tests. Create reusable patterns and collaborate with stakeholders to clarify requirements and tradeoffs.

Lead and define architectural solutions for data pipelines, mentor teams, optimize ETL/ELT processes, and ensure data governance in a client-facing environment.

Design, build, and maintain scalable data pipelines and AWS data platform services focusing on AWS technologies and collaboration with data teams.

As a Data Services Engineer, you will support clients by developing data products and solutions, manage projects, and collaborate across departments.

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.

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.

The Senior Data Engineer will design and optimize data pipelines from SAP to Databricks, focusing on CDC and stream processing. Responsibilities include managing Kafka components, CI/CD pipelines, and ensuring data quality while collaborating with various teams.

Lead Data Engineer responsible for defining architecture, engineering standards, and best practices for the enterprise data platform, collaborating with distributed teams for modernization and scalability.

As a Senior Data Engineer, you'll design and maintain scalable data pipelines, optimize workflows with dbt and Snowflake, and mentor teams across functions to enhance data reliability and performance.

Design and maintain a dbt-based business data layer for GTM metrics, centralize and reconcile multi-source data, implement automated data quality and reconciliation checks, align and document metrics with stakeholders, mentor analytics team, and lead root-cause investigations into complex data anomalies.

Lead and mentor a distributed data engineering team while architecting and building a next-generation, largely open-source data platform. Own hands-on POCs, pipeline design, schema and query optimization, ETL reliability, observability, testing, and CI/CD. Evaluate and recommend technologies, drive migration from vendor lock-in, and translate advertising and market research needs into robust technical solutions.

Lead design and ownership of a modern data platform: ingestion, Snowflake governance, pipeline reliability, migrations, data contracts, observability, and AI-enabled tooling. Partner with Analytics, Engineering, and vendors to deliver trustworthy data products and operate production pipelines.

The Principal Data Platform Engineer leads the architecture and development of the enterprise data platform, focusing on analytics, data science, and AI/ML capabilities. They establish standards for data quality and observability, design data ingestion and processing patterns, and mentor team members to enhance technical capabilities.

Own and operate Databricks production pipelines for Sugar Predict: monitor, alert, incident response, SLA reporting, performance and cost optimizations, migrate legacy ETL, onboard tenants, enforce Delta Lake architecture and multi-tenant isolation, apply security and governance, enable observability, maintain runbooks, and support CI/CD and on-call rotations.

Design, build, and operate scalable batch and streaming data pipelines and a lakehouse on AWS. Implement ETL/ELT, CDC, metadata/catalog and governance, automated AWS provisioning (IaC), CI/CD for data pipelines, data quality and lineage, observability, and documentation while collaborating across teams.