Joblaze summary

In this role, the Data Engineer at CuspAI focuses on developing and maintaining data pipelines that connect raw chemical data to machine learning models, ensuring high-quality training datasets for researchers. Proficiency in Python, experience with large-scale data processing, and familiarity with workflow orchestration tools are essential for success. This position is ideal for someone with at least three years of experience in data engineering, particularly in scientific environments, who enjoys building scalable systems. CuspAI's interdisciplinary team emphasizes collaboration between AI and materials science, making it a dynamic place for innovation.

Joblaze insights

Listed about a month ago — first seen on Joblaze September 3, 2026. Last confirmed on CuspAI's careers page October 27, 2026.
Python appears in 69.9% of 136 comparable mid data engineering roles; Flyte appears in 0.7% of 136 comparable mid data engineering roles.

Quick facts

How much experience is required?: At least 3 years of relevant experience for this Data Engineer role.
What's the tech stack?: Joblaze extracted these technologies from the posting: Airflow, Dagster, Docker, Flyte, Kubernetes, Prefect.
What seniority level is this role?: CuspAI targets mid-level candidates for this position.
Is this full-time or contract?: Full-time for this Data Engineer role at CuspAI.

From the original posting

The Role

We are seeking a Data Engineer with strong software engineering fundamentals to own, design, develop, test, secure, and deploy data-rich tools, services, and web applications. In this role, you will build the foundational data systems and platforms that enable our materials scientists, machine learning engineers, and partners to collaborate on diverse datasets at scale.

Your Impact

As a key member of our engineering team, you will bridge the gap between complex materials science data and real-world application. You will empower researchers and machine learning models with clean, structured, and accessible data, directly accelerating our ability to discover and design breakthrough materials.

What You Will Do

Own the full software lifecycle of data-rich tools, services, and web applications from design through to deployment and security.
Build scalable data ingestion, processing, and cleaning pipelines to handle both structured and complex unstructured data.
Develop data-intensive Python APIs and intuitive web applications/UIs that allow team members and partners to query, export, analyse, and visualise data.
Implement robust orchestration systems to automate pipeline execution and manage data flows.
Maintain strict standards for data privacy, governance, and security across all data architectures.
Deploy and manage containerised data services using basic infrastructure tooling.

Must Have Skills and Qualifications

Software engineering background with a strong focus on data management.
Deep fluency in Python.
Hands-on experience with at least two database paradigms (e.g., Relational, Document, Columnar, Key-Value).
Proven track record writing data-rich Python APIs and surfacing data through web applications with a UI.
Experience working with complex unstructured data, large-scale datasets, and implementing data privacy standards.
Experience with at least one modern orchestration framework (e.g., Dagster, Flyte, Prefect, Ray).
Fundamental infrastructure experience with basic Docker and Kubernetes.

Bonus Points

Experience working with geographically distributed data.
Experience with modern data lakehouse / warehouse technologies (e.g., Apache Iceberg, Delta Lake, Apache Hudi).
Prior experience collaborating with scientists, domain experts, or ML teams.

What We Offer

A competitive salary: We value and reward impact and growth

Standard company text repeated across CuspAI's postings is omitted here.

Data Engineer