Top Remote Data Engineer Jobs
In this role, the Marketing Data Engineer will architect scalable ETL/ELT pipelines, manage cloud-based data warehouses, and develop data integration solutions. Responsibilities include collaborating with various teams to support analytics, ensure data quality, and optimize performance across data workflows.
As a Data Engineer at Arcadia, you will be responsible for developing solution architecture and data pipeline connectors between client data management platforms and Arcadia's analytic solutions. Your role involves designing connectors, unit testing, participating in scrum methodologies, and ensuring project timelines are met. You'll work collaboratively to enhance and support integrations for healthcare clients.
The Marketing Technology Data Engineer will design and build data solutions for managing and integrating real-time and batch data, focusing on data quality and availability for enterprise clients. The role involves developing data pipelines, implementing CI/CD processes, and collaborating with teams to meet client needs while leveraging Google Cloud services.
As a Principal Data Engineer at Atlassian, you will be responsible for building data solutions that support crucial business decisions. Your role includes developing backend systems, designing data models, managing analytical data pipelines, and enabling a data-driven culture throughout the organization.
As a Principal Data Engineer, you will drive the direction of the Data Warehouse, design and optimize ingestion pipelines, and mentor team members. You will ensure data accuracy, monitor pipelines, comply with regulatory requirements, and collaborate with internal teams for comprehensive data integration.
Headway is seeking a Senior Data Engineer to help create access to affordable, quality mental healthcare across the United States. This role involves collaborating on data infrastructure design, partnering with product/engineering for best practices, creating data pipelines for business insights, and building real-time data pipelines in coordination with the Data Science team.
The Data Engineer will design, implement, and maintain the data infrastructure for analytics and business intelligence at Endpoint. Responsibilities include developing ETL pipelines, managing data warehouses, ensuring data quality, and collaborating with cross-functional teams to optimize data workflows and support data-driven decision-making.
The Data Engineer II role at Bestow involves building scalable data solutions, improving data quality and availability, creating data models and pipelines for analytics and machine learning, and collaborating with various teams to ensure efficient data management.
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As a Senior Data Engineer, you will design and maintain data infrastructure for Square's Marketing team, focusing on web event data. Responsibilities include building data pipelines, translating requirements for ETL processes, analyzing data sources, monitoring pipeline performance, and improving data quality and efficiency. Your work will significantly influence business decisions and reporting accuracy.
The Sr. Data Engineer will design and build scalable data pipelines across various sources to support data-driven decisions and generative AI initiatives. Responsibilities include collaborating with cross-functional teams, implementing data engineering principles, and optimizing performance and security of data applications.
As a Senior Data Engineer, you will focus on building data infrastructure, managing ETL pipelines, collaborating with analysts, maintaining databases, and implementing process improvements. You will lead the development of data services and stay updated with cloud technologies to enhance data handling across the company.
The Senior Data Engineer at Two Barrels will lead the development of data infrastructure and ETL pipelines while collaborating with software and analyst teams. Responsibilities include managing data services/platforms, improving existing data models, and ensuring scalable, cost-effective database design. Staying updated with cloud technologies and implementing process efficiencies are key components of the role.
Develop and maintain data platforms, architect data pipelines, and collaborate with stakeholders to drive operational efficiencies. Improve system performance and ensure data security and compliance. Share knowledge through documentation and mentoring.
Lead data engineer role at Wipfli focusing on the continuous advancement of a modern data lakehouse. Responsible for translating requirements into effective data models, developing in data technologies, managing project life cycle activities, achieving/maintaining proficiency in required skills, and collaborating with team members.
As a Data Engineer, you will manage and optimize data pipelines, develop ETL processes using Python, maintain AWS infrastructure, model data across teams, and assist in report generation and debugging.
The Senior Data Engineer will lead the development of high-impact products, collaborate with Finance and Accounting teams, and take ownership of data services lifecycle. Responsibilities include architecting data models, resolving data integrity issues, and ensuring data solutions align with business needs.
The Senior Data Engineer will design, develop, and manage scalable data architectures and pipelines, primarily using cloud platforms like Azure. Responsibilities include data integration, modeling, optimization, and mentoring. The role emphasizes collaboration with cross-functional teams to ensure data infrastructure supports analytics and drives decision-making.
The Senior Data Engineer will analyze requirements, write and ship code in dbt, design data pipelines, enhance data systems, and mentor junior engineers. This role focuses on leveraging data for strategic business impact and improving developer efficiency through automation within a cloud environment.
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 Cloud Data Engineer will develop and engineer solutions primarily using Python and Spark within AWS Glue, along with managing OpenSearch and DynamoDB. The role also involves programming with Neptune Graph Database, developing REST APIs, and constructing AWS infrastructure elements like IAM roles and policies.
The Cloud Data Engineer will design and implement scalable data processing solutions using PySpark and AWS Big Data technologies, oversee the integration of Palantir, optimize AWS Cloud services, manage AWS Batch workflows, and mentor junior staff while ensuring data quality and compliance with industry standards.
The Lead AWS Data Engineer will design and implement scalable Big Data solutions using AWS services, oversee deployment and management of AWS EC2 instances, and develop Python scripts for data processing. Responsibilities include maintaining AWS EMR, implementing DevOps practices, and mentoring junior team members.
As an Intermediate Data Engineer, you will develop new product features and enhance existing products using ETL (Python + SQL), ETL Pipelines (Airflow), and API (Go) development. This role involves participating in the entire product lifecycle, ensuring the reliability and efficiency of data processing solutions.
The Senior Data Engineer will design, develop, and maintain data pipelines and infrastructure, focusing on optimizing data for AI/ML models. Responsibilities include leading the creation of data warehouses, ensuring data quality, and collaborating with cross-functional teams to meet data requirements for machine learning applications.
The Senior Data Engineer will design and develop robust data pipelines for data ingestion, processing, storage, and retrieval while optimizing data systems for efficiency. They will collaborate with cross-functional teams, enforce data governance policies, and ensure data integrity and compliance with regulations.
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