Top Remote Data Engineer Jobs

Responsible for building scalable data pipelines, transforming data using Python and SQL, and collaborating with teams to ensure data quality and successful analytics solutions.

The role involves writing and deploying scripts for data collection, transforming data sets, diagnosing bugs, and collaborating with other engineers using agile principles.

The Data Engineer I supports the Data Engineering Team by running queries, manipulating data, documenting processes, and resolving data issues.

The Principal Data Engineer will lead the Data Resolution team, focusing on complex data challenges using Spark, system architecture, and mentorship, to optimize graph data pipelines.

As a Data Engineer, you will build and optimize data pipelines, ensuring accurate data delivery that informs pricing and market analytics at Alt.

The AWS Cloud Data Engineer will design, develop, and enhance AWS data environments, build scalable Data Lake solutions, and lead proofs-of-concepts into production.

The job involves leveraging AWS and Snowflake for data engineering tasks within a technology-focused company, requiring US residency.

As an AI Data Engineer, ensure the reliability and accuracy of AI Agents through systematic evaluation and validation, utilizing strong analytical skills and data quality principles.

Develop and maintain cloud data warehouse on AWS, build ETL/ELT pipelines, enhance data quality, and work with analytics teams.

The Lead Data Consultant will design and deliver scalable data solutions, manage project teams, and optimize client data environments, ensuring effective project execution and communication.

Design, develop, and manage data infrastructure for internal and client projects, focusing on large-scale data pipelines, APIs, and cloud deployments.

As a Data Engineer, you will develop and manage the data infrastructure that supports HTS Media's advertising business, build ETL/ELT pipelines, and enable data-driven insights for advertisers and internal analytics.

Design, build, and maintain enterprise data solutions and ingestion/transformation pipelines for operational and analytic needs. Partner with stakeholders, implement data governance, optimize MLOps in cloud/big-data environments, and mentor junior engineers. Use GCP, SQL, Kafka, Python, Teradata, Oracle, Git and related tools.

Join Quora's data infrastructure team to build and maintain data lakes, pipelines, query engines, and dashboards. Work on scalability, cost and performance improvements, participate in planning and on-call rotations, and contribute to tooling and reliability. Mentorship and training provided for new graduates.

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.

Lead design, build, and optimization of Sezzle's large-scale data warehousing and pipelines. Own data infrastructure KPIs/SLAs, improve Redshift performance, evolve the data stack, implement ETL/ELT workflows, and partner with cross-functional teams to deliver reliable, scalable datasets.

As a Data Operations Engineer, you will manage data acquisition, ensure data compliance, maintain data storage security, and collaborate with various teams to support operations.

Provide pre-sales technical leadership for data management and analytics solutions: assess customer needs, design and validate cloud data architectures (warehouses, lakehouses, ETL/ELT, RAG/GenAI), build demos/POCs, and support sales with presentations, integration planning, and technical guidance.

Provide pre-sales technical leadership for field sales: design and validate data management and analytics solutions, lead POCs/demos, perform systems integration, and advise on cloud data platforms, unstructured data processing, RAG/GenAI, ETL/ELT, governance, BI and ML workflows.

Provide pre-sales technical leadership for data management and analytics solutions: analyze customer needs, design and validate cloud data architectures (warehouses, lakehouses, ETL/ELT), lead demos/POCs, integrate unstructured data and RAG/vector workflows, and support field sales to deliver end-to-end analytics and GenAI solutions.

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.

Design, build, and maintain production data pipelines and the unified data model using Snowflake, dbt, and orchestration tools. Optimize, test, document, and monitor ELT workflows, enforce engineering best practices, mentor teammates, and deliver trustworthy data products for analytics and business decisions.

Architect, build, and maintain scalable ELT data pipelines and analytics-ready data marts. Lead dbt modeling, ensure data quality, CI/CD, and documentation. Partner with stakeholders, mentor junior engineers, evaluate tooling (reverse ETL), and drive long-term data platform strategy.

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.

Design, develop, and manage Control-M job flows and enterprise data pipelines. Build job dependencies, monitoring, automation, reruns, and SLA management. Integrate with data platforms (warehouses, Hadoop/Spark), cloud services (AWS/Azure/GCP), SFTP/APIs/storage, and implement scripting (shell/Python) and CI/CD for reliable, high-performance data ingestion, transformation, validation, and downstream delivery.