Design, build, and maintain scalable data pipelines and ETL workflows using Azure, Spark, and Python. Lead AI/ML engineering efforts and develop robust web APIs for seamless system integration.
Remote Data Engineer Jobs (2,551)
Search = Data Engineer
Architect and maintain the data model, pipelines, and access layers to support healthcare operations and analytics. Lead technical engineering best practices while ensuring data quality and governance for stakeholders.
Develop and maintain data infrastructure and ETL/ELT pipelines for complex linear viewership data using Python and big data frameworks. Collaborate with engineering and data science teams to translate product requirements into technical designs and monitored production systems.
Architect and maintain the data infrastructure to move and transform marketplace data reliably at scale. Own the analytical schema and data quality standards to support internal analytics and customer-facing reporting.
Lead the design, development, and scaling of complex data pipelines and platforms to support strategic decision-making. Provide technical mentorship to junior engineers and collaborate with business leaders to translate requirements into production-ready solutions.
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Lead the design and optimization of enterprise data platforms on Azure, focusing on Azure Fabric adoption and lakehouse architecture. Develop scalable ETL/ELT pipelines and integrate data from various enterprise systems to enable data-driven decision-making.
Design and implement scalable, high-performance data pipelines to ingest and transform data from various sources. Build and maintain secure, tenant-aware APIs and implement observability and monitoring to ensure data reliability.
Design and implement scalable, high-performance data pipelines to ingest and transform data from various sources. Build and maintain secure, tenant-aware APIs and implement observability and monitoring to ensure data reliability.
Architect and develop high-performance datasets and domain-oriented data architecture using dbt and BigQuery. Build and maintain batch and streaming data pipelines to support analytics, machine learning, and business decision-making.
Architect and deliver trusted data sets and modern analytics architectures to support internal teams and external customers. Lead continuous improvement in data management standards and mentor junior engineers to drive scalable data infrastructure solutions.
Junior Data Engineer (Faculty Specialist)
University of Maryland
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Full Time
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7 hours ago
University of Maryland
Design, develop, and support relational and distributed database instances to create stable and secure data platforms. Work within an Agile environment to define, document, and test transportation data analytics applications.
Analyze project requirements to design and support new and existing data systems. Partner with cross-functional teams to deliver data solutions for new business initiatives and monitor implementations.
Lead the design and implementation of data pipelines, schemas, and models to support business intelligence and analytics. Provide technical leadership through coaching and mentorship while collaborating cross-functionally to drive product improvements.
Design and execute scalable data integration pipelines and models to support financial reporting, billing, and revenue teams. Collaborate with cross-functional stakeholders to translate financial pain points into reliable, self-serve data solutions.
Design and execute scalable data integration pipelines and models to support financial reporting, invoicing, and book closing. Collaborate with finance and accounting teams to translate pain points into reliable, self-serve data solutions.
Design, build, and deploy scalable data solutions and pipelines to support AI, Machine Learning, and business intelligence for customers. Collaborate with internal teams and clients to operationalize complex data transformations and ensure data quality and governance.
Lead a team of data engineers to design and maintain data architecture, models, and ETL routines within an Azure environment. Act as a servant leader managing sprint planning, workload prioritization, and technical mentorship for the team.
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Design and develop solutions for data collection, storage, and modeling while ensuring data quality and accessibility for analysts and scientists. Lead technical teams, manage code quality, and participate in pre-sales activities and client technical solutions.
Architect and build robust data frameworks and automated workflows to empower Enterprise Data Lake platforms. Collaborate with Analytics, Sales, and Marketing teams to create curated datasets that drive strategic decision-making.
Architect and develop petabyte-scale data pipelines and self-service platforms to modernize data ingestion and management. Build full-stack internal tools and high-performance APIs to transition the organization toward a Data Mesh approach.
Design, model, and develop the GCP data ecosystem, including data lakes and warehouses, for a client. This involves gathering requirements, optimizing data storage architectures, and mentoring junior data engineers.
Design and implement scalable data processing systems and pipelines on the Azure platform to ingest and transform data from various sources. Collaborate with cross-functional teams to optimize data storage architectures and provide structured data for analysis and modeling.
Build and maintain scalable data pipelines and foundations to support People Analytics and AI-driven tools. Collaborate cross-functionally to translate people-related business problems into technical data products and dashboards.
Do Not Apply - Big Data Engineer 6/8/2026, 10:57:20 AM
BuiltIn Integration Sandbox
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Full Time
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10 hours ago
BuiltIn Integration Sandbox
Collaborate with the patient matching team to design and evolve the product vision for finding therapists. Contribute to the Helix design system and help grow the startup's design team culture and processes.
Design and build scalable real-time and batch data pipelines to power analytics and automation across Kaseya's products. Own the full lifecycle of data platforms, focusing on optimization, reliability, and cross-functional collaboration with Product and Engineering teams.
The Data Engineer is responsible for designing, building, and maintaining complex data processing systems and optimizing pipelines for efficiency. They also provide technical mentorship to junior team members and translate business objectives into technical deliverables and KPIs.
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Design, build, and implement scalable data pipelines and models using Python and SQL to support business intelligence tools. Monitor production pipelines, troubleshoot data quality issues, and maintain code via CI/CD processes.
Lead the design, development, and maintenance of scalable data pipelines and ETL processes for digital analytics platforms. Establish data quality frameworks and collaborate with architects and cross-functional teams to translate business needs into technical specifications.
Design and maintain scalable data pipelines using Python, Spark, and Airflow to support data acquisition and entity resolution. Collaborate with AI/ML teams to optimize ETL processes and deliver AI-native data products within an Agile framework.
Lead the design and scaling of data pipelines and analytics infrastructure using tools like Airflow, dbt, and Python. Partner with cross-functional teams to develop reliable data models and modernize legacy data processes.
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