Top Data Engineer Jobs

As a Staff Data Engineer, you will mentor engineers, lead the design and architecture of complex software systems, uphold engineering best practices, and drive innovation in collaboration with cross-functional teams. You will ensure alignment with business goals and maintain high standards in software quality and documentation.

The Wireless Data Engineer is responsible for designing and maintaining scalable data architectures for processing large-scale network data. They will develop data flows, ensure data quality, collaborate with teams to meet business objectives, and optimize data processing systems while staying updated on emerging technologies.

As a Data Engineer, you will design and maintain scalable data pipelines using Java and Spark, optimize SQL queries, and implement solutions with Snowflake. You'll collaborate with teams to understand data requirements and ensure efficient data processes, and may develop visualizations with Tableau.

The Senior Data Architect will design and develop data models, enhance data loading capabilities, and collaborate with enterprise partners to optimize data usage. Responsibilities also include managing a team of Data Modelers, prototyping data solutions, and advising on best data practices to support operational and analytic needs.

The Data Engineer will lead the architecture and implementation of both on-premises and cloud-based data solutions while building data pipelines in AWS for data lakes and warehouses, utilizing tools like AWS Glue and Python. Responsibilities include managing ETL processes and ensuring efficient data integration.

As a Senior Lead Data Engineer at Capital One, you will lead a team in building scalable data solutions, collaborating with agile teams, and leveraging big data technologies to transform data handling and enhance governance. You will design, implement, and support cutting-edge cloud solutions while mentoring engineers and ensuring code quality. The role focuses on addressing complex business problems with big data and cloud computing.

The Data Engineer will develop and deliver enterprise applications focusing on data integration and analytics. Responsibilities include building scalable data processing pipelines, supporting data integration, and improving internal data capabilities. The role requires collaboration with IT and business teams to manage data issues and define data architecture strategies.

As a Data Engineer, you will prepare data for AI applications through ETL processes, ensuring data quality, cleansing, and compliance while developing data pipelines for model training and deployment.

As a Data Engineer, you will gather, cleanse, and prepare data for AI models, ensuring high-quality data for research and development. Responsibilities include collecting data from various sources, cleansing and preprocessing it, developing data pipelines, collaborating with machine learning engineers, and implementing efficient data storage solutions.

The ETL Data Engineer will analyze, design, and develop ETL processes, manage complex data workflows using Azure tools, and ensure data integrity and governance. Responsibilities include creating end-to-end pipelines, automating workflows, and collaborating with teams to enhance data systems.

The Sr Talend Data Engineer will develop complex Talend data pipelines, perform data reconciliation and unit testing using SQL, and interact with AWS services, specifically reading data from S3 and writing to Redshift.

As a Data Engineer, you will build and optimize production-grade data solutions on AWS or GCP, develop scalable ETL pipelines, and manage data storage and transformation routines. You will work closely with the Machine Learning and Data Platform team and engage with both technical and business stakeholders.

Looking for a Data Engineer to lead the integration of product, financial, and business systems using SQL, dbt, and Python. Responsibilities include data workflows, data quality, modeling, documentation, collaboration, and data leadership. Requires 5+ years of experience in a SaaS environment and expertise in data engineering tools and cloud services.

The Data Engineer will design, implement, and maintain scalable data stores for business analysis, focusing on data architecture, SQL query optimization, and integration. The role involves documentation, project planning, and collaboration with stakeholders to meet technical standards and business requirements.

The Senior Data Engineer will design and implement ETL processes in a cloud environment, develop monitoring solutions, document datasets, and collaborate with the Data Science team. This role requires building ETL processes and a strong understanding of data modeling.

The Data Engineer will be responsible for developing and deploying data pipelines for streaming and batch data from multiple sources. They will create data models, implement business logic, and work with a variety of technologies including Azure Databricks, Apache Spark, and data storage solutions. Excellent communication skills are required.

The Data Developer Specialist is responsible for the development, testing, and documentation of complex data transformations and services, providing production support, optimizing performance, and mentoring entry-level developers. This role requires expertise in ETL, SQL tuning, and data modeling methodologies to support strategic business initiatives.