Build and maintain reliable, scalable big data pipelines and commercial products end-to-end. Collaborate with product managers to define requirements and mentor junior engineers through code reviews and technical guidance.
Remote Data Engineer Jobs (2,745)
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Own the backend services and API layer that deliver ML-based predictions and data products to merchants. Lead the technical direction for backend and ML systems, ensuring reliability, observability, and scalability of production workloads.
Design and scale data pipelines and agentic systems to automate data engineering tasks for a large e-commerce platform. Collaborate cross-functionally to develop ML pipelines and maintain reliable data infrastructure for advanced analytics and AI.
Design and maintain backend services, REST APIs, and big data pipelines to power customer-facing insights and analytics. Develop a query engine and scale data processing pipelines to handle large volumes of activity data for the Unified Data Platform.
Design, develop, and maintain scalable data pipelines and cloud-native data platforms to support digital government services. Collaborate with cross-functional teams to transform complex data into actionable insights while ensuring security and performance.
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Sr. GCP Data Engineer (Job-ID 3301)
KANINI Software Solutions
·
Full Time
·
5 Weeks Ago
KANINI Software Solutions
Design and maintain scalable batch and real-time data pipelines on GCP using Medallion Architecture. Develop high-performance data transformations and optimize complex SQL queries for large-scale analytical workloads.
Provide strategic and tactical pre-sales leadership by delivering technical expertise throughout the customer journey, including solution design and POC execution. Act as a technical advisor to enterprise customers and collaborate cross-functionally to align product direction with market needs.
Design and implement complex data solutions, architectures, and scalable pipelines for customers. Translate business requirements into technical tasks to help organizations capitalize on data and AI opportunities.
Design and manage the end-to-end data platform architecture, from integration and transformation to data delivery. Lead the development of robust data pipelines and establish technical standards for data quality and modeling within Databricks.
Design and own the end-to-end data platform architecture, including ingestion, transformation, and serving layers. Lead the development of robust data pipelines and enforce data quality standards to power business-critical decisions.
Design, develop, and optimize scalable data pipelines and solutions primarily using Snowflake. Collaborate with business teams to translate requirements into robust technical solutions and ensure data reliability and traceability.
Take ownership of the data platform roadmap, including the warehouse layer, ingestion pipelines, and transformation strategy. Develop and optimize scalable ELT pipelines while implementing data contracts and observability tooling to ensure data reliability.
Design and implement electrical systems for hyperscale and colocation data centers, including power distribution and backup systems. Develop electrical schematics, calculations, and drawings while ensuring compliance with industry standards and codes.
Design and implement electrical systems for hyperscale and colocation data centers, including power distribution and backup systems. Develop electrical schematics, calculations, and drawings while ensuring compliance with industry standards and codes.
Design and implement electrical systems for hyperscale and colocation data centers, including power distribution and backup systems. Develop electrical schematics, calculations, and drawings while ensuring compliance with NEC and industry standards.
Design and implement electrical systems for hyperscale and colocation data centers, including power distribution and backup systems. Develop electrical schematics, calculations, and drawings while ensuring compliance with industry standards and codes.
Design and implement electrical systems for hyperscale and colocation data centers, including power distribution and backup systems. Develop electrical schematics, calculations, and drawings while ensuring compliance with NEC and industry standards.
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Design and implement electrical systems for hyperscale and colocation data centers, including power distribution and backup systems. Develop electrical schematics, calculations, and drawings while ensuring compliance with industry standards and codes.
Build and maintain data ingestion pipelines from APIs and other sources using Python and SQL. Support marketing data modeling and collaborate with analytics teams to deliver campaign performance datasets.
![Quanata is hiring for remote Senior Data Engineer, MLOps [Remote-US]](/assets/f06abd19-26ed-4c46-9932-662b121216c9.jpg){kind=small}
Design and implement automated machine learning pipelines and infrastructure to shorten the time to market for data science models. This includes managing feature stores, real-time inference services, and implementing ML governance and monitoring.
The role involves building and optimizing data pipeline architectures and tooling to support analytics and machine learning platforms. Additionally, the candidate will supervise junior engineers and collaborate with development teams to create cross-functional solutions.
Design and maintain automated data ingestion pipelines and analytics-ready data models to power the People Data Hub. Collaborate with HRIS and IT to ensure secure, scalable, and governed reporting for workforce analytics.
Design, build, and maintain scalable data models and ELT pipelines to power clinical analytics and operational reporting. Partner with stakeholders to transform raw data into consumable datasets while mentoring other engineers and documenting business logic.
Design, develop, and optimize AI/ML models and pipelines to power cybersecurity behavioral detectors. Collaborate with cross-functional teams to integrate these features into a scalable, fault-resilient platform.
Lead the design and implementation of robust ETL pipelines to process large-scale customer datasets for Distribution Center products. Define the technical vision for data architecture while mentoring engineers and collaborating cross-functionally to improve data quality.
Lead the design and implementation of robust ETL pipelines using PySpark and DBT to process large-scale customer datasets. Define the technical vision for DC data architecture while mentoring engineers and collaborating cross-functionally to deliver scalable data solutions.
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Drive the technical strategy, architecture, and long-term evolution of the data platform, including batch, streaming, and AI-centric capabilities. Lead large-scale initiatives and mentor engineers to elevate technical quality and engineering standards across the organization.
Design, build, and optimize scalable data services, streaming solutions, and cloud-based data platforms. Lead complex cross-functional initiatives and define enterprise-wide data engineering standards and best practices.
Develop and optimize data pipelines using AWS services to integrate multiple information sources for analytical and operational consumption. Ensure data quality, performance, and governance while collaborating with stakeholders to translate business needs into technical data solutions.
Own and develop the gold data layer by transforming raw clinical and operational data into curated datasets for AI model development. Collaborate with researchers and product experts to bridge data semantics with AI needs across various modalities.
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