Top Remote Data Engineer Jobs

Design, build, and maintain Snowflake-based pipelines to produce consumer and household identity assets. Write SQL/Python to transform and deduplicate PII, investigate data quality at record level, and improve AI-assisted and rule-based matching engines. Collaborate with Data Science and engineering teams to evaluate matching performance, build evaluation tooling and dashboards, and support CI/CD, QA, and on-call production responsibilities.

Design, build, and scale reliable batch and real-time data pipelines and warehouses. Partner with engineering, data science, and business teams to define data models, improve observability, optimize storage and querying, and evangelize data engineering best practices across the company.

Design, build, and maintain Snowflake pipelines using Python and SQL to produce identity assets. Investigate record-level PII data quality, enhance AI-assisted and rule-based matching engines, build evaluation and monitoring tooling, collaborate with Data Science and Product, and support CI/CD, QA, and on-call responsibilities for production identity pipelines.

Lead architecture and implementation of scalable data systems and pipelines from ingestion to delivery. Own ambiguous, high-impact integrations, improve data quality and reliability, adopt AI-augmented engineering, mentor engineers, and collaborate with Product, ML, and customer teams to ship production solutions.

Design, build, and optimize Snowflake-based data platforms and DBT models. Develop ingestion/replication pipelines, profile source data, ensure data quality, and support analytics and reporting through advanced SQL and collaboration with architects and stakeholders.

Design, build, and maintain scalable batch and streaming data pipelines and analytics-ready data models. Implement cloud (primarily AWS) data platform solutions, data ingestion, transformation, orchestration, and observability. Embed data quality, governance, security, and metadata/lineage practices. Partner with architecture, analytics, and application teams to enable self-service analytics, reporting, and downstream use cases while driving platform evolution and engineering best practices (CI/CD, testing, documentation).

Design, build, and maintain scalable, fault-tolerant streaming data architectures and real-time pipelines using Kafka, MSK, and Kinesis. Implement stream processing, monitoring, security, IaC, and CI/CD. Collaborate with data teams, provide technical leadership, and optimize latency, throughput, and cost for real-time analytics and downstream systems.

The Senior Data Engineer will maintain and improve data infrastructure, design ETL processes, and create high-performance pipelines for analytics and AI initiatives using SQL and Python in cloud environments.

In this role, you'll develop data pipelines, architect scalable data solutions using Snowflake, ensure healthcare compliance, and manage master data management initiatives.

Lead data engineering for a healthcare scheduling platform rebuild: map legacy multi-TB schema, design target schema, build translation layer (views/materialized views and write mappers), ensure data consistency during parallel systems, plan per-tenant cutover with verification and rollback, tune DB performance, instrument data quality/lineage/audit, and mentor engineers.

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 role involves building data platforms and pipelines, integrating AI solutions, and collaborating with product owners to address complex client issues.

Lead design and delivery of production data platforms, pipelines, and analytics. Architect Snowflake/Databricks solutions, build ETL/streaming ingestion, implement dbt transformations, data quality, observability, and governance, support BI and AI/ML feature/data pipelines, and mentor engineers while driving DataOps and platform best practices.

Design, build, and maintain scalable ELT/ETL data pipelines and data models on cloud platforms (preferably Snowflake). Enable batch and near-real-time integrations, ensure data quality/monitoring, create APIs and production-ready datasets for BI, analytics, and ML, optimize performance and cost, document architectures, evaluate new technologies, and mentor engineers.

The Senior Data Engineer will architect event-driven data pipelines, automate ETL processes, and ensure operational excellence in NVIDIA's financial infrastructure.

The Senior Data Engineer will design and maintain data pipelines, write production-grade Python and SQL code, and support AI initiatives while collaborating across teams.

Design and build scalable batch and streaming data pipelines, lead architecture for Lakehouse platforms, and mentor junior engineers while optimizing data quality and performance.

As a Senior Data Engineer, you'll design and maintain data pipelines, collaborate with teams to optimize data processes, and provide mentorship to junior members.

The Lead Data Engineer modernizes and optimizes the Medicaid Market's data platform, manages ETL processes, and partners with the Business Intelligence team to enhance data accessibility and reliability, while also leading contract resources in a complex environment.

Lead data engineering strategy and design scalable data ecosystems. Build and maintain distributed ETL pipelines, enforce data governance (PII/PHI), improve developer efficiency, mentor engineers, and align technical work to business objectives while delivering reliable, monitored production systems.

Design, build, and maintain scalable Databricks-based data pipelines and ELT workflows; develop and document dbt models; define data modeling methodology; ensure data quality, reliability, and scalability; collaborate with clients and cross-functional teams; provide technical guidance and deliver improvements to clients' data infrastructure and analytics capabilities.

As a Senior Data Engineer, you will manage data pipelines, ensure data quality, partner with teams for data-driven decisions, and improve the data platform while maintaining data integrity.

The Senior Data Engineer will create and manage data pipelines, ensuring data quality, collaborating with teams for data-driven decisions, and evolving the data platform.

The AWS Data Engineer designs and maintains data solutions on AWS, implementing scalable pipelines, integrating systems, ensuring security, and optimizing workflows.

The Workday/Fabric Data Engineer will develop and maintain business intelligence initiatives, including reporting, data pipelines, and data warehousing to support strategic objectives at USNH.