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Lead the design and evolution of an enterprise AWS data platform, building scalable data pipelines and setting engineering standards for a global digital signage and customer experience company.
Senior Data Engineer building and maintaining large-scale cloud data infrastructure, ETL pipelines, and data lake architectures in the healthcare domain using Python, PySpark, Azure, Snowflake, Databricks, and Terraform.
Senior Data Engineer designing and building scalable, cloud-native data platforms with event-driven ingestion pipelines, primarily using Spark/PySpark, Databricks/Snowflake, and a major cloud provider (Azure preferred).
Software Engineer building a cloud-native, microservices lottery platform using React, Node.js, MySQL, Docker, and Kubernetes across the full delivery lifecycle from design through production support.
Software Engineer building and operating a cloud-native, microservices-based lottery platform using React, Node.js, MySQL, Docker, and Kubernetes across the full delivery lifecycle.
Business Analyst working with a Product Owner on a Data Warehouse environment, gathering and documenting business/data requirements, writing User Stories, and bridging business and technical teams in an agile setup.
Build and deploy data pipelines and AI integrations for government customers, deploying Scale’s software onsite and syncing customer data to the platform.
Data Engineer supporting DEA's case management modernization, designing and maintaining scalable ETL pipelines for data ingestion, migration, and integration using SQL, Python, and cloud data platforms.
ThreatDown is looking for... A transformative Senior Director of Revenue Operations that owns the systems, data, and processes that drive ThreatDown's revenue engine while leading a multi-quarter transformation to…
The Data Engineer will design, build, and maintain scalable ETL/ELT pipelines and optimize data warehouse architecture in Snowflake. They will collaborate with business teams to ensure data integrity and accessibility for analytics and reporting.
Build and maintain digital analytics data pipelines and infrastructure for a fintech/insurance client, focusing on ingestion, transformation, and delivery of data for AI-driven products and MarTech integrations.
GENERAL SUMMARY: Under the direction of a Manager, Director or Lead/Experienced developer, implements a comprehensive program to extract data using a computer programming language or collect data, then analyze it and…
About ClickHouse Recognized on the 2025 Forbes Cloud 100 list, ClickHouse is one of the most innovative and fast-growing private cloud companies. With more than 4,000 customers and ARR that has grown over 250 percent…
Qualifications: Relevant Degree or Diploma in IT Computer Science Data Science or related field Cloud or Data Engineering certifications advantageous Requirements: 3+ years Data Engineering experience Experience with…
Role : Senior Integration Engineer Client : Government of North Carolina(NCFast) Work Type : Onsite Location : Raleigh,North Carolina Duration : 12 Months(Extendable) Payrate : 70$ Per Hour eSystems Inc. is a…
Build and optimize large-scale data pipelines and datasets using SQL, Snowflake, Databricks, Spark, and Azure services to support ML/AI and business analytics for Paychex's HCM platform.
Employee Applicant Privacy Notice Who we are: Welcoming, collaborative and having the opportunity to make an impact - is how our employees describe working here. SoFi Tech Solutions (formerly Galileo Financial…
Who We're Looking For - Lifecycle Operations Manager Clearlink is building a centralized Lifecycle Marketing function to power scalable, compliant, performance-driven email programs across our portfolio of brands —…
Computer Vision Engineer owning end-to-end image processing pipelines for space domain awareness, training/customizing models (Unet, ViT, ResNet) in PyTorch/TensorFlow, with strong C++ programming and classical vision (OpenCV) skills.
Builds and optimizes cloud-based data pipelines (ETL/ELT) using Microsoft Fabric/Azure Data Factory, focusing on API integrations, Lakehouse/Data Warehouse architecture, and stakeholder collaboration.
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