

Jobs via Dice
Principal Data Engineer - ML Platform
⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is for a Principal Data Engineer - ML Platform, offering a 12+ month remote contract. Requires 7+ years in software engineering, expertise in Python, Java, and PySpark, and experience with cloud-native data systems, preferably in GCP and Databricks.
🌎 - Country
United States
💱 - Currency
$ USD
-
💰 - Day rate
Unknown
-
🗓️ - Date
April 11, 2026
🕒 - Duration
More than 6 months
-
🏝️ - Location
Remote
-
📄 - Contract
Unknown
-
🔒 - Security
Unknown
-
📍 - Location detailed
United States
-
🧠 - Skills detailed
#Deployment #AI (Artificial Intelligence) #Data Engineering #Python #Batch #PySpark #Databricks #Java #Data Modeling #Debugging #Automated Testing #Spark (Apache Spark) #Computer Science #ML (Machine Learning) #Scala #Data Pipeline #Strategy #Cloud #GCP (Google Cloud Platform) #Leadership #Data Framework
Role description
Dice is the leading career destination for tech experts at every stage of their careers. Our client, Encora, is seeking the following. Apply via Dice today!
Principal Data Engineer - ML Platform
Location: Remote
Duration: 12+ months contract to hire.
About The Role
We are seeking an experienced Principal / Senior Software Engineer, Data & ML Platform to lead the design and development of the foundational data and platform systems that power our AI and machine learning products.
This is a hands-on technical leadership role responsible for architecting scalable, cloud-native infrastructure that enables real-time and batch data services for training, inference, and feedback loops. You will help define the technical direction of our data and ML platform while partnering closely with AI Platform, MLOps, and backend engineering teams.
Key Responsibilities
• Architect and build the core data and software systems that support our AI and ML platforms.
• Design and develop scalable data pipelines, APIs, and platform services for ML and AI use cases.
• Build real-time and batch data frameworks to support model training, inference, and continuous feedback loops.
• Drive platform scalability, reliability, and engineering excellence across distributed systems.
• Partner with cross-functional engineering leaders to shape long-term platform strategy and technical direction.
• Mentor engineers and establish best practices for system design, testing, deployment, and performance optimization.
• Evaluate and implement technologies that improve platform capability, reliability, and developer efficiency.
Qualifications
• Bachelor s degree in Computer Science, Engineering, or related field; Master s preferred.
• 7+ years of experience in software engineering, data infrastructure, ML platform, or related engineering roles.
• Strong expertise in Python, Java, and/or PySpark.
• Proven experience designing and scaling cloud-native data and ML systems, preferably in Google Cloud Platform and Databricks.
• Deep understanding of distributed systems, system design, data modeling, and platform architecture.
• Strong experience building and operating large-scale, data-intensive systems.
• Excellent technical leadership, communication, debugging, and problem-solving skills.
• Experience with automated testing, deployment best practices, and production-grade software development.
Why This Role Matters
This role is critical to building the trusted, scalable data foundation behind our Agentic AI platform. Your work will enable our engineering teams to deliver faster, more accurate, and more scalable AI-powered products across MarTech and AdTech.
Dice is the leading career destination for tech experts at every stage of their careers. Our client, Encora, is seeking the following. Apply via Dice today!
Principal Data Engineer - ML Platform
Location: Remote
Duration: 12+ months contract to hire.
About The Role
We are seeking an experienced Principal / Senior Software Engineer, Data & ML Platform to lead the design and development of the foundational data and platform systems that power our AI and machine learning products.
This is a hands-on technical leadership role responsible for architecting scalable, cloud-native infrastructure that enables real-time and batch data services for training, inference, and feedback loops. You will help define the technical direction of our data and ML platform while partnering closely with AI Platform, MLOps, and backend engineering teams.
Key Responsibilities
• Architect and build the core data and software systems that support our AI and ML platforms.
• Design and develop scalable data pipelines, APIs, and platform services for ML and AI use cases.
• Build real-time and batch data frameworks to support model training, inference, and continuous feedback loops.
• Drive platform scalability, reliability, and engineering excellence across distributed systems.
• Partner with cross-functional engineering leaders to shape long-term platform strategy and technical direction.
• Mentor engineers and establish best practices for system design, testing, deployment, and performance optimization.
• Evaluate and implement technologies that improve platform capability, reliability, and developer efficiency.
Qualifications
• Bachelor s degree in Computer Science, Engineering, or related field; Master s preferred.
• 7+ years of experience in software engineering, data infrastructure, ML platform, or related engineering roles.
• Strong expertise in Python, Java, and/or PySpark.
• Proven experience designing and scaling cloud-native data and ML systems, preferably in Google Cloud Platform and Databricks.
• Deep understanding of distributed systems, system design, data modeling, and platform architecture.
• Strong experience building and operating large-scale, data-intensive systems.
• Excellent technical leadership, communication, debugging, and problem-solving skills.
• Experience with automated testing, deployment best practices, and production-grade software development.
Why This Role Matters
This role is critical to building the trusted, scalable data foundation behind our Agentic AI platform. Your work will enable our engineering teams to deliver faster, more accurate, and more scalable AI-powered products across MarTech and AdTech.





