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Senior Data Engineer

Job in Boston, Lincolnshire, PE21, England, UK
Listing for: Digital Plastics, Inc
Full Time position
Listed on 2026-02-24
Job specializations:
  • IT/Tech
    Data Engineer, Data Science Manager, Data Analyst, AI Engineer
Job Description & How to Apply Below
Digital Plastics, Inc provided pay range

This range is provided by Digital Plastics, Inc. Your actual pay will be based on your skills and experience — talk with your recruiter to learn more.

Base pay range

$/yr - $/yr

Direct message the job poster from Digital Plastics, Inc

Entrepreneur, Business Leader, Investor, and Strategic Advisor. MIT PhD alum.

Plastik AI is harnessing the power of artificial intelligence to build a Generative Engineering Marketplace to revolutionize the plastic industry, bridging the gap between engineers using plastics and manufacturers creating them. At the core of our platform is Herman, an advanced AI agent designed to match product requirements with ideal plastic compounds. Herman leverages a combination of public and proprietary data to enable rapid and precise material recommendation, which can be easily ordered within a marketplace.

We are looking for a skilled Data Engineer to build a leading caching infrastructure to enable us develop systems to index and search a plastic specific ontology to instantly enable industry leading AI tools access to data that data . Our product combines novel AI-driven agents and tools with a unique user experience, enabling effortless selection, sourcing, and procurement of plastics.

Building a two-sided marketplace is a unique challenge that requires advanced data models across material properties, predictions, pricing, and logistics.

You will work to on a world-class AI team to engineer data pipelines, analysis tools, and custom ontologies to enable reliable and scalable workflows that build our growing ML asset. A key focus will be to prioritize key developments that accelerate features that set our platform apart. We believe our transformative approach unlocks new possibilities in plastics innovation, enabling faster, smarter, and more efficient product development and material discovery to build a more sustainable world.

As part of our cross-disciplinary team, you will work alongside MIT-trained engineers, scientists, and business professionals to build a groundbreaking AI platform for the plastics industry. Join us in transforming how the world approaches plastic materials through cutting-edge technology and innovation.

Job Responsibilities

You will be a member of the AI engineering team and collaborate with the product development and product team to build business-critical workflows.

Data Infrastructure Design & Optimization - Design, build, and maintain robust, scalable, and secure data pipelines and ETL processes to support high-throughput data ingestion and transformation workflows. Implement intelligent caching strategies to reduce compute costs, accelerate data retrieval, and improve application responsiveness across the platform. Develop and manage data lake and warehouse architectures that support real-time and batch data processing for AI and analytics workloads.

Search & Discoverability - Architect and implement semantic and structured search workflows to enhance dataset discoverability and enable faster, more accurate querying across Plastics Ai data sources. Collaborate with AI/ML and front-end teams to expose search capabilities via intuitive APIs and interfaces, improving user experience and insights generation.

Data Analysis & Reporting - Conduct advanced data profiling and analysis to uncover trends, data quality issues, and optimization opportunities across structured and unstructured data assets. Build and maintain dashboards, automated reporting pipelines, and analytics tools to support both internal stakeholders and external users in making data-informed decisions.

Integration & Interoperability - Integrate internal systems with third-party APIs and external data sources to support seamless data exchange, enrich AI model inputs, and expand the scope of automation and analytics. Ensure robust versioning and observability of data flows and transformations to support debugging, reproducibility, and auditability.

AI System Support
- Work closely with ML engineers to prepare clean, labeled, and versioned datasets for training and inference. Ensure efficient data pipelines for model training, evaluation, and deployment.…

Position Requirements
10+ Years work experience
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