Architect and maintain enterprise-grade data platforms and scalable pipelines to support analytics and machine learning. Translate business requirements into robust data architectures and manage the end-to-end data engineering lifecycle.
Remote Data Engineer Jobs (2,745)
Search = Data Engineer
Design, build, and optimize HANA-native data models and analytical objects to support S/4HANA and BW/4HANA platforms. Act as the primary expert for diagnosing and resolving HANA performance issues across the SAP landscape.
Lead and grow a team of data engineers to build and maintain pipelines for reporting, analytics, and machine learning. Drive engineering excellence through code quality, architectural decisions on GCP, and cross-functional collaboration with business stakeholders.
Design, build, and deploy scalable data solutions and pipelines to support AI, ML, and BI insights for customers. Collaborate with internal teams and clients to operationalize complex data transformations and ensure data quality.
Design and implement Medallion-layer lakehouse architectures and scalable streaming and batch data pipelines. Optimize large-scale analytics queries and ensure platform reliability through monitoring and troubleshooting.
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Develop and optimize scalable data processes, models, and pipelines using Snowflake, SQL, Python, and Kafka. Collaborate with product leadership and analysts to translate complex requirements into stable data structures within an AI-first, Agile framework.
AWS Data Engineer with BI Connector To snowflake migration Exp(6+ Yrs of Exp & Immediate Joiner looking for)
3Pillar
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Full Time
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4 Days Ago
3Pillar
Develop and maintain scalable ETL/ELT data pipelines using AWS and Snowflake while migrating BI workloads to Snowflake. Optimize data models and ensure seamless connectivity between BI platforms and the data warehouse.
Define and drive the long-term data engineering strategy for the Subscriptions User Understanding domain to improve scalability and reliability. Design scalable batch and streaming platforms while mentoring senior engineers and establishing engineering best practices.
Senior Data Engineer (Snowflake/SQL) - Software Industry
Truelogic
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Full Time
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4 Days Ago
Truelogic
Build and maintain robust ETL pipelines to move data from AWS PostgreSQL databases into Snowflake. Audit and tune SQL queries to optimize production database performance and ensure high availability.
Lead the design and evolution of a cloud-native data platform focusing on scalable batch processing and event-driven workflows. Build and maintain data pipelines, analytical models, and integrate data capabilities with backend microservices.
Design, build, and optimize complex SQL queries and data pipelines within an Exasol environment to support healthcare analytics. Perform chart validation and reconcile data extracts against medical records to ensure clinical and regulatory accuracy.
Build and operate large-scale data systems to power AI training and evaluation pipelines. Focus on ingestion, transformation, quality assurance, and high-throughput delivery of data across diverse modalities.
Lead the architecture and evolution of the data platform, focusing on ingestion, modeling, and governance to support AI and analytics. Set technical standards for the data engineering team and partner with AI engineering to ensure scalable, clean data infrastructure.
Lead data engineering efforts within Palantir Foundry and Databricks to build and optimize data pipelines and ontologies for Army AI2C applications. Provide technical leadership and collaborate with stakeholders to integrate AI/ML capabilities into data-driven products.
Design, develop, and deploy data solutions, including the creation of dashboards and reports to provide business insights. Manage data ingestion, ETL processes, and performance tuning of complex SQL and DAX queries.
Design and maintain data architectures to ensure compliance with global privacy regulations using OneTrust. Automate DSAR workflows and integrate privacy tools with internal data sources like DynamoDB and S3.
Design, build, and maintain scalable data pipelines and ETL/ELT workflows using AWS-native platforms and modern data engineering tools. Lead modernization initiatives to migrate legacy platforms to cloud-native services while mentoring junior engineers.
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Design, build, and maintain scalable data pipelines and ETL/ELT workflows using modern cloud-based tools. Collaborate with cross-functional teams in an Agile environment to optimize enterprise data platforms and support mission-critical analytics.
The role involves writing production Python code to build and maintain data pipelines for the Insights platform. It also requires providing technical leadership to set the platform's direction and improving engineering standards across the team.
Workday/Fabric Data Engineer
University of New Hampshire
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Full Time
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4 Days Ago
University of New Hampshire
Design, develop, and maintain business intelligence initiatives, including data marts and pipelines to support strategic objectives. Provide technical expertise in Workday reporting and lead mid-to-large scale technical projects.
Design and operate large-scale data pipelines to support AI training, evaluation, and multimodal data ingestion. Implement data cleaning, versioning, and high-throughput loading systems to maximize GPU utilization and model quality.
Design and optimize end-to-end ETL pipelines to integrate and operationalize legal data from multiple jurisdictions. Develop data models and retrieval infrastructure to support agent-based AI systems and high-performance search.
Design and implement data loading and integration processes using ETL tools like PowerCenter, IDQ, or DEI. Responsible for requirements gathering, functional testing, and maintaining data pipelines across platforms such as BigQuery and SQL Server.
Design and evolve the core data platform infrastructure, including distributed query engines and lakehouse architecture. Build low-latency streaming and batch ingestion pipelines while ensuring platform reliability through monitoring and SLAs.
Lead the migration and consolidation of data warehouse implementations and design scalable data lake solutions on AWS. Develop robust data pipelines and translate legacy business logic into scalable Spark SQL code within Databricks.
You will build and maintain high-throughput ETL/ELT pipelines while ensuring data reliability through robust observability and monitoring systems. Additionally, you will collaborate with BI and Data Science teams to productize datasets and optimize query performance for cost-efficiency.
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Design and implement production-grade data pipelines to ingest and synchronize structured and unstructured enterprise data for the Reltio Brain. Build secure MCP/API-style tools and RAG systems to provide governed context and retrieval for AI agents.
The role involves designing the end-to-end blueprint for a modern enterprise data architecture to support Agentic AI. It also requires leading technical strategy and governance while managing hybrid-database environments for clients.
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