R&D Data Integrations Engineer — Python

Uncountable Inc.; United States; On-site; USD 90,000 - 110,000; Full time

Benefits offered by this job

Competitive salary and equity

Health and dental insurance

401(k) with employer contribution

Job summary

Uncountable Inc. seeks a scientifically-minded software engineer for the Implementations Engineering team. You will build real, production-grade software connecting the platform to lab instruments and customer environments, using Python and data pipelines.

You'll work directly with customers to understand data landscapes, map schemas, and deliver robust integrations that save scientists hours weekly. This is an ownership-driven role with strong engineering impact.

Qualifications

• Programming experience: Coursework or professional experience equivalent to 4 university-level CS courses.
• Familiarity with Python or another scripting language to process data files.
• Scientific background to understand lab data and instrumentation is a plus.

Responsibilities

• Build data integrations ingesting outputs from lab instruments into the platform.
• Design automated data transfer pipelines connecting ELNs, LIMS, spreadsheets, and databases.
• Write scripts to parse, validate, and transform scientific data formats.
• Collaborate with customer technical teams to map data environments and deliver integrations.
• Maintain and evolve existing integrations as data sources change.
• Contribute to internal tooling and shared libraries to speed future integrations.

Skills

Python scripting

Problem-solving mindset

Customer collaboration

Data interpretation

Education

B.S. in Computer Science or related field

Tools

REST APIs

SQL databases

Excel/CSV pipelines

Job description

Uncountable Inc. seeks a scientifically-minded software engineer for the Implementations Engineering team. You will build real, production-grade software connecting the platform to lab instruments and customer environments, using Python and data pipelines.

You'll work directly with customers to understand data landscapes, map schemas, and deliver robust integrations that save scientists hours weekly. This is an ownership-driven role with strong engineering impact.