• Monitor and debug data pipeline issues with support from senior engineers.

• Work closely with analysts, scientists, and product managers to understand data requirements and business context.

• Participate in code reviews, design discussions, and debugging sessions.

• Contribute to documentation and internal tooling to improve team productivity.

• Grow your understanding of domain models, data contracts, and business context.

• Grow into owning workflows end-to-end, improving performance, and contributing to architectural decisions.

Qualifications:

Required:

• Are a recent grad (BS/MS in CS, Data Engineering, or related field) or early-career engineer with 0–3 years of industry experience.

• Strong programming fundamentals and proficiency in Python.

• Exposure to SQL and a desire to work with large datasets.

• Curiosity about real-world data problems, particularly those involving messy, complex data.

• Hunger to learn — you enjoy getting into the weeds, asking good questions, and figuring things out.

• Solid communication skills — able to collaborate effectively with both technical and non-technical partners.

• Attention to detail and a strong sense of ownership.

Preferred:

• Prior internship or co-op in data engineering, analytics, or infra roles.

• Experience with cloud platforms like AWS, GCP, or Azure.

• Exposure to version control (e.g., Git), Docker, or CI/CD.

• Familiarity with distributed data processing (Spark, Hadoop, etc.)

• Contributions to open-source, side projects, or technical blogs.

Company:

Machinify is a SaaS platform that enables non-technical enterprises to build AI-powered products and processes. Founded in 2016, the company is headquartered in Palo Alto, California, USA, with a team of 1001-5000 employees. The company is currently Late Stage. Machinify has a track record of offering H1B sponsorships.