Design and maintain business-critical data systems and ETL pipelines using GCP to provide real-time data across various business tools. Analyze data to create business insights and build machine learning models to identify customer churn and upsell opportunities.
Remote Data Engineer Jobs (2,431)
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Design and build modern data-centric software applications and pipelines to support clinical and operational processes in healthcare. Mentor junior data engineers and collaborate with Product, Platform, and Architecture teams to deliver scalable data solutions.
Build and maintain ELT data pipelines and dbt models to transform raw game data into reliable datasets. Collaborate with cross-functional teams to ensure data quality and contribute to data architecture decisions in a startup environment.
Design and build scalable data pipelines on the Databricks Lakehouse Platform for ingestion, transformation, and augmentation. Collaborate with cross-functional teams to translate data requirements into actionable models and ensure data quality.
Design, build, and maintain scalable data pipelines and infrastructure to support critical business decisions. Develop Databricks dashboards and collaborate with stakeholders to translate reporting needs into technical solutions.
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Lead the design and delivery of scalable data pipelines and end-to-end analytical solutions. Serve as a technical advisor and mentor to the data engineering team while ensuring security and regulatory compliance.
Design, build, and maintain end-to-end data pipelines from extraction to production deployment in the cloud. Collaborate with cross-functional teams to integrate large datasets and deliver data-driven business insights.
Design, build, and optimize ETL pipelines using Microsoft Fabric and Medallion Architecture to support data-driven decisions. Collaborate with stakeholders to integrate new data sources and maintain data quality, governance, and security standards.
Develop and maintain scalable data warehouse architectures and optimized data pipelines for enterprise-wide business intelligence. Establish data governance standards and tune system performance for efficient query processing and batch loads.
Design, implement, and operate scalable cloud-native data pipelines and platform components on AWS for an IoT Insurance Data Platform. Build and maintain ETL/ELT workflows, event-driven architectures, and data lakehouse components to support analytics and machine learning.
Design and implement cloud-native data pipelines and trade lifecycle solutions to support processing, reconciliation, and settlement. Onboard complex financial data sources and maintain a unified trade architecture.
Design and implement data extraction pipelines from SAP HANA to AWS S3 and manage the write-back path into SAP BW/BW4HANA. Collaborate with PySpark engineers to ensure raw SAP tables are transformed into trusted datasets for business analysts.
Design, develop, and maintain ETL/ELT processes and data pipelines using Oracle Data Integrator (ODI 12c). Collaborate with stakeholders to ensure data quality and support cloud-based data architectures and visualization initiatives.
Design, build, and maintain scalable data platforms, pipelines, and warehouses using SQL, Python, and Spark. Collaborate with stakeholders to translate business requirements into efficient data engineering solutions and ensure data quality and governance.
Develop and operate modern data architecture and intricate processing pipelines to meet business objectives. Collaborate with data scientists to implement scalable models while ensuring data governance, security, and quality.
Design, build, and maintain scalable systems for a commerce analytics platform, focusing on streaming pipelines and data lakehouse architecture. Responsibilities include evolving data models, managing infrastructure as code, and ensuring observability across production environments.
The role involves migrating SSIS packages to Azure Data Factory and building ingestion pipelines for iBuy and Scorecard processes. It also requires implementing a data quality framework and an audit layer with automated stakeholder alerting.
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Design, build, and optimize ETL/ELT pipelines to transform data into actionable datasets. Partner with product teams to develop reporting tools and maintain data lakes for ML engineering solutions.
Design and maintain scalable data pipelines and infrastructure within the Google Cloud environment using tools like Airflow and dbt. Collaborate with cross-functional teams to deploy BI dashboards and ensure robust data governance and quality.
The role involves designing and developing automation solutions to improve business process efficiency and quality across the Services division. It also requires managing project coordination, reporting status to senior management, and mentoring junior team members.
Design and develop automation solutions to improve quality and efficiency across the Services division. Manage project coordination, status reporting, and the implementation of business process improvements for the Merchant Offers business.
The role involves modernizing a Marketplace Analytics Data Platform by replacing legacy ETL scripts with software-engineered data models. You will build scalable data pipelines and establish validation standards to ensure data reliability across the enterprise.
Drive the technical vision and strategy for advertising data infrastructure by building scalable data pipelines and analytical tools. Lead cross-functional initiatives to enhance advertising products through data-driven insights and mentor other engineers.
Design and operate large-scale ingestion systems to transform raw multimodal data into clean, AI-ready datasets. Own the end-to-end data processing layer, ensuring high throughput, reliability, and security for sensitive data.
Design and operate scalable systems that transform high volumes of identity data from third-party integrations into product primitives. Establish observability, SLOs, and technical vision for a world-class data infrastructure to support engineering and AI teams.
Lead the modernization of a healthcare data platform by migrating an MSSQL XML object store to a scalable, cloud-native AWS architecture. Design and implement the reporting layer and data pipelines to enable performant SQL-based queries for business stakeholders.
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Design and maintain scalable Azure-based data pipelines and lakehouse solutions. Lead data governance implementation and advise clients on MDM frameworks and metadata management.
SCADA & Automation Engineer - Data Centers
NEI Electric Power Engineering
·
Full Time
·
5 Days Ago
NEI Electric Power Engineering
Responsible for the engineering design, installation, and testing of SCADA and PLC systems, specifically using SEL equipment for data centers. The role involves producing configuration files, creating electrical diagrams, and performing field commissioning and troubleshooting.
Design, develop, and maintain data pipelines using ETL/ELT processes to ingest and transform data into the data warehouse. Collaborate with data scientists and analysts to ensure data quality, consistency, and the delivery of actionable insights.
Design and maintain robust cloud-based data pipelines and infrastructure on GCP to support AI and machine learning models. Ensure healthcare data compliance with HIPAA and HITECH while integrating disparate clinical datasets using interoperability standards.
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