Senior Data Engineer
Digital Plastics, Inc · Boston, United Kingdom ·
- Seniority
- Senior
- Employment
- Full time
- Category
- Data engineering
- Experience
- 5+ years
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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.
$120,000.00/yr - $180,000.00/yr
Direct message the job poster from Digital Plastics, Inc
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. Support experiment tracking, feature engineering pipelines, and KPI-driven experimentation to accelerate innovation cycles.
Governance, Compliance & Ethics- Implement data governance best practices, including metadata tracking, lineage, and access controls. Ensure that data workflows and storage comply with relevant data privacy, ethical, and regulatory standards, particularly in AI training and automated decision-making.
Collaboration & Leadership - Act as a strategic partner to product and AI teams, contributing to the long-term vision and roadmap of data infrastructure and platform capabilities. Mentor junior engineers, contribute to architectural decisions, and help shape a strong data engineering culture focused on reliability, scalability, and impact.
Qualifications
What We Offer:
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Medical insurance
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401(k)
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