2,112 Data Engineering jobs available for remote work from home. Apply for positions such as Senior Engineer Data Foundry - Compliance Ops, Data Modeler, Data Scientist, and more! Discover the best work-from-home or hybrid, full- and part-time jobs.
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The Senior Data Foundry Engineer is responsible for building and scaling user-facing data applications and custom widgets to support the digitization of the Compliance Organization. This role involves managing the full lifecycle of data from ingestion and transformation to ontology design and application deployment.
The Data Modeler will design, develop, and maintain scalable conceptual, logical, and physical data models to support enterprise analytics and reporting. They will collaborate with cross-functional teams to translate business requirements into efficient data structures within Snowflake and AWS environments.
You will develop, validate, and tune statistical and machine learning models while partnering with engineers to ensure they are production-ready. Additionally, you will monitor deployed algorithms for performance and provide actionable business insights to stakeholders.
Design and implement scalable ETL/ELT pipelines, data models, and orchestration workflows to support the Air Force Data Mesh. Develop full-stack application features and APIs to ensure governed data discovery, access, and interoperability.
The Senior Architect will design, develop, and deploy production-ready Agentic AI solutions for enterprise customers, focusing on Office of Finance use cases. They will collaborate with stakeholders to translate business requirements into scalable AI architectures while ensuring governance, reliability, and security.
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The Senior Architect designs and guides scalable, production-ready implementations of the Alteryx One platform for enterprise customers. They serve as a trusted technical advisor, aligning customer data strategies with analytics automation and platform best practices.
Design, build, and maintain robust data infrastructure and ETL/ELT pipelines to ensure data quality and consistency across enterprise systems. Lead the development of data products and an AI context layer to enable scalable analytics and cross-functional data alignment.
You will lead and grow the data engineering team while setting the technical roadmap for data ingestion and pipeline infrastructure. You will also partner with cross-functional leadership to prioritize business needs and ensure high engineering standards across the data platform.
The Data Engineering Leader will architect enterprise-scale data platforms and lead a team of 10-20 engineers to transform healthcare data into actionable insights. This role involves managing platform strategy, financial accountability, and fostering a culture of data engineering excellence and cross-functional collaboration.
Design, develop, and maintain scalable data pipelines and ETL/ELT workflows to support enterprise analytics and reporting. Collaborate with stakeholders to integrate data from multiple sources while ensuring data quality, security, and performance.
You will develop and optimize data systems, including ETL pipelines, storage, and entity resolution infrastructure. Additionally, you will collaborate with data science teams to build data products and automation tools to support organizational goals.
Provide technical leadership and ensure the quality of the Data Foundation platform by managing enterprise data pipelines and data products. Collaborate with cross-functional teams to deliver scalable, trusted, and maintainable data solutions that support advanced analytics and AI initiatives.
Lead the design and implementation of scalable data ingestion and transformation solutions using SQL and dbt. Develop and optimize end-to-end ELT pipelines while enforcing data quality frameworks and Medallion Architecture best practices.
The FP&A Manager will lead the validation of financial data, reconcile reporting systems, and complete the implementation of NetSuite Planning & Budgeting. They will also partner with business unit leaders to drive forecasting, budgeting, and actionable management reporting.
Design, build, and operationalize complex data solutions to support AI, ML, and business intelligence insights. Collaborate with internal teams and customers to provide technical guidance and ensure high-quality data delivery.
Lead the data engineering and analytics engineering teams to define and evolve the company's cloud-based data platform. Ensure data quality, scalability, and governance while acting as a consultant to business leaders to drive data-informed decision-making.
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Define and execute the enterprise strategy for job ingestion, including scraping, ATS feeds, and data normalization to drive business growth. Lead cross-functional teams to ensure high-quality, fresh job data is integrated across all downstream platforms and search engines.
Lead and evolve the data platform organization, including database engineering, data capture, and governance to enable reliable data pipelines. Set the strategy and roadmap for data infrastructure while partnering with cross-functional teams to modernize operational data architecture.
You will design, develop, and maintain scalable data platform services and pipelines to support investment research, trading, and analytics. Additionally, you will collaborate with cross-functional teams to optimize data architecture and ensure high-performance data delivery.
You will co-develop batch and streaming data pipelines and semantic models using Databricks while defining data quality rules and SLOs. Additionally, you will mentor domain teams on data product ownership and engineering best practices to ensure scalable and auditable AI solutions.
Lead and develop a multidisciplinary team of machine learning, data, and backend engineers while providing technical guidance on complex ML systems. Act as a bridge between technical teams and cross-functional stakeholders to ensure reliable delivery and alignment with business goals.
Design, develop, and optimize large-scale data pipelines using Apache Spark and Python while maintaining cloud-based data solutions on Microsoft Azure. Collaborate with cross-functional teams to implement data quality controls, governance, and scalable data architectures.
Design, build, and deploy production-grade generative AI features using LLM APIs and integrated data layers. Collaborate with product and engineering teams to maintain evaluation harnesses and ensure high performance, accuracy, and cost-efficiency in a regulated environment.
You will build and scale infrastructure by implementing standardized AWS footprints, universal CI/CD pipelines, and observability tools. Additionally, you will act as an engineering advocate to support product teams, manage on-call rotations, and ensure compliance with security standards like HIPAA.
The Data Analyst will develop operational analytics and data-driven insights to demonstrate company impact and optimize care navigation service delivery. They will also integrate disparate data sources and provide strategic analysis to support population health program performance.
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The Sr. Manager will lead acquisition performance analytics, including reporting, measurement, and optimization across marketing channels. They will also design experimentation frameworks and partner with cross-functional teams to drive data-informed growth strategies.
Design, develop, and maintain IBM Planning Analytics (TM1) models and applications to support financial planning, forecasting, and reporting. Collaborate with finance stakeholders and actuarial teams to build robust data solutions and ensure data quality.
The Implementation Project Manager oversees the end-to-end delivery of healthcare and medical device connections, managing the project lifecycle from discovery to go-live. This role involves triaging technical issues, coordinating across internal teams, and ensuring regulatory compliance for global data standards.
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