Top Data Engineer Jobs

Design, build, and operate a privacy-safe, cloud-based data platform supporting batch and real-time pipelines, analytics, ML/AI, governance, observability, and high pipeline reliability. Partner with stakeholders, set data engineering standards, troubleshoot production incidents, and mentor engineers.

Lead data architecture and hands-on engineering to build a cloud data warehouse on Snowflake using Data Vault 2.0 and dbt. Design standards, implement ETL/ELT pipelines with Python and SQL, ensure data quality and governance, mentor engineers, and support on-prem to cloud migration.

Design, build, and maintain scalable data pipelines, warehouse architecture, and BI solutions. Lead data modeling, integration (CDC/streaming), infrastructure reliability, and governance. Collaborate with data scientists, analysts, and partners, enforce PHI security, mentor teammates, and support on-call and evolving BI technologies.

Build and maintain automated ETL/ELT data pipelines, improve data quality and monitoring, optimize Postgres and BigQuery schemas and queries, develop internal tooling, support data governance (HIPAA), participate in on-call rotation, and collaborate across engineering teams to scale data systems.

The Data Engineer will design and maintain data pipelines, enhance the data warehouse, support machine learning applications, and collaborate with various teams to leverage data effectively.

As a Data Engineer at MAI, you will develop and maintain data platforms, design ETL/ELT processes, ensure data quality, and collaborate with teams to optimize data utilization for analytics and ML applications.

The Senior Data Engineer will build and maintain ETL/ELT pipelines, optimize SQL queries, and collaborate on machine learning workflows, driving data engineering best practices.

The Senior Data Engineer will design and maintain data architecture and integration solutions, develop enterprise data pipelines, enforce data quality, and mentor junior team members while collaborating with business stakeholders.

The Senior Data Engineer will develop and optimize software applications and data platforms for NAVOCEANO, supporting mission-critical solutions, data pipelines, and analytics capabilities.

Lead design and implementation of large-scale data pipelines, ETL, and warehousing. Build and manage databases, ensure data quality/security, collaborate with analysts and scientists, evaluate new technologies, mentor junior engineers, and manage project delivery.

Design, build, and maintain ETL/ELT data pipelines and domain-oriented data products to support a Digital Thread. Ensure data quality, governance, mapping, and discoverability. Apply software-engineering practices (version control, testing, CI/CD, IaC) for production deployments. Integrate manufacturing and operational systems and prepare AI/ML-ready datasets for analytics and predictive use cases.

The Senior Data Engineer will develop data pipelines, analyze geospatial data, implement quality assurance processes, and support database synchronization with APIs, contributing to climate risk financial modeling.

As a Senior Data Engineer, you'll build ETL pipelines, design data ingestion systems, and maintain a multi-cloud ecosystem while collaborating with Data Scientists to transform data into business insights.

The Data Engineer/Scientist extracts insights from complex data sets, optimizes algorithms, ensures data quality, develops BI solutions, and mentors junior team members.

Responsible for utilizing Hortonworks architecture and tools such as Hadoop and Spark for data analysis and engineering tasks. Candidates should have relevant experience and may be considered for contract-to-hire roles.

As a Sr. Data Engineer at Lyra Health, you will build and scale core data infrastructure, design data warehouses, and create efficient data pipelines while collaborating across departments.

The Sr. Ab Initio Data Integration Engineer will maintain ETL processes, troubleshoot performance issues, and provide documentation for the data warehouse environment.

As a Lead Data Engineer, you will architect data foundations for AI applications, lead a team, optimize data pipelines, and ensure data governance.

Responsible for designing, building, and maintaining real-time data ingestion pipelines, ensuring reliable data flow and quality for operational decisions.

Lead modernization and operation of Dutch Bros' data platform: design, build, and maintain scalable Snowflake-based data pipelines and infrastructure, enable real-time ETL/ELT, support analytics and ML workflows, implement CI/CD and IaC, ensure data governance and security, and communicate technical solutions to stakeholders.

Lead design, build, and maintenance of scalable data pipelines and lakehouse infrastructure using PySpark, Databricks, and Airflow. Own data & ML platform (Terraform, Databricks), improve observability, data quality, and developer tooling, and partner closely with Data Science and engineering teams.

The role involves building scalable data platforms, developing data pipelines, mentoring engineers, and enhancing data security while collaborating across teams.

Lead design and delivery of cloud-native lakehouse and data product solutions for Supply Chain. Architect and build ingestion pipelines and ETL using AWS (Glue, S3, EMR, Lambda), Apache Iceberg, Redshift, and Spark. Implement Medallion Architecture and data mesh principles, translate SAP/Blue Yonder data into governed analytics-ready products, enforce metadata, lineage and data quality, and lead a technical engineering team while partnering with business stakeholders.

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