Scientific Data Engineer

About the role

This role focuses on integrating laboratory instruments into the TetraScience Data Platform. The primary responsibility involves developing instrument parsers and designing data pipelines to ensure smooth data flow and accessibility. This includes creating user stories, refining data, attributing metadata, and thoroughly testing parsers. The work is crucial for enabling scientific data analysis and accessibility within the platform.

The position requires providing solution guidance to the Systems Integrations team, specifically for integrations between TetraScience and Revvity ELN. While the core task is instrument onboarding, the engineer will also contribute to the strategic implementation of data solutions. Success in this role means efficiently onboarding approximately 50 laboratory instruments and ensuring their data is well-structured and accessible.

Candidates should have a strong background in data engineering, particularly with data from laboratory equipment or software. The role demands proficiency in various programming languages and cloud data technologies, along with expertise in ETL and data warehousing. The ideal candidate will be adept at problem-solving and stakeholder management, translating technical discussions into actionable requirements for data platform integrations.

The salary for this position ranges from $80,500 to $138,000 annually.

Skills that matter here

• Python: This role requires proficiency in Python for developing instrument parsers and data pipelines.
• R: Proficiency in R is expected for data manipulation and analysis within the scientific data engineering tasks.
• SQL: SQL expertise is necessary for managing and querying data within various database systems used in the data pipelines.
• AWS services: Experience with AWS services is required for building and maintaining cloud-based data architectures.
• Snowflake: This role involves working with Snowflake as part of the cloud data platform stack for data warehousing.
• ETL: Expertise in ETL processes is essential for extracting, transforming, and loading data from laboratory instruments into the data platform.

Who this role suits

• Someone with a Bachelor's degree or higher in a technical or life sciences field.
• A professional with at least five years of experience in data engineering, ideally within scientific, manufacturing, or healthcare sectors.
• An individual who excels at analytical problem-solving and can effectively manage stakeholders.
• A candidate with a strong command of English, capable of clear technical communication.

From the employer

Responsibilities

• Onboarding of approximately 50 laboratory instruments onto the TetraScience Data Platform:
• Development of instrument parsers as required
• Design and development of data pipelines to support data flow and accessibility
• Provide solution guidance to the Systems Integrations team on Integration solution guidance between TetraScience and Revvity ELN
• Activities Performed:
• User Story creation & refinement,
• Raw-to-IDS, metadata attribution,
• instrument onboarding,
• parser development, testing, etc..

Note that this does not include integrations of system with ELN, NNCD, Inventory management, etc.

What we expect

• Expertise working with data from laboratory equipment/software, (e.g. LIMS, ELN, etc.)
• Bachelor’s degree in Engineering, Data Science, Life Sciences, Computer Science, or related field; advanced degree preferred.
• 5+ years of experience in data engineering, including data modeling and database design, preferably in a scientific, manufacturing, or healthcare environment.
• Proficiency with Python, R, SQL, and cloud-based architectures (AWS services, Snowflake, Databricks, Redshift).
• Expertise in ETL and DWH.
• Experience with NoSQL and graph databases.
• English language proficiency of B2+
• Strong analytical, problem-solving, and stakeholder-management skills, with the ability to translate discussions into actionable requirements.
• Experience in Data Platform integrations, preferably in Life Sciences/biotech domain.

We offer

• Competitive compensation
• Remote or office work
• Flexible working hours
• Continuous education, mentoring, and professional development programs
• A team with excellent tech expertise
• Certifications paid by the company