Pay
In line with similar jobs
$140K–$200K against $127K–$190K, the middle half of what similar US postings state.
From 2,232 postings in the last year. Stated ranges, not salaries paid.
Senior Scientific Data Engineer
New York, United States
Live, first seen by us 25 days ago- Pay
USD 140,000–200,000/year — pay source
Company-paid Life Insurance, LTD/STD The salary range for this position is $140,000 - $200,000 USD Annually. The salary range posted reflects our target baseline for this role. Final compensation is determined by a thorough evaluation of factors including the candidate’s specific experience, localized market data, and internal team equity.
Read the full posting- Work setting
On-site — work setting source
Work setup in the employer’s posting: On-site
From the employer’s posting- Employment
Full-time — employment source
Employment type in the employer’s posting: Full-time
From the employer’s posting
What you’ll work on
Full postingDesign and build bidirectional integrations between Tetra OS and customer systems like ELN and LIMS
Build data schemas and parsers for lab instrument, manufacturing and CRO/CDMO data
Deploy and test solutions in customer environments and troubleshoot across the full stack
Create designs backed by test automation to prove expected behaviors
Mentor junior scientific data engineers and lead internal design sessions
From the employer’s posting
design and build bidirectional integrations between Tetra OS and customer systems such as ELN, LIMS, MES, and process historians
design and build comprehensive data schemas and parsers for scientific data from R&D lab instruments, manufacturing, CRO, CDMO, ELN, and LIMS sources
Deploy and test solutions in customer environments, including cloud, on-premises, and hybrid networks, and troubleshoot across the full stack when something breaks
Create and enforce designs with quality backed by comprehensive test automation to prove expected behaviors
You will also mentor other scientific data engineers, lead internal design sessions
What you’ll bring
All qualificationsCore experience
- 8+ years building data products as a Data Engineer or in a similar field.
- 8+ years working in Python and SQL with a focus on data, integrations, and scientific applications.
- Expertise in Python and working knowledge of JavaScript, TypeScript, Node, and React.
- Experience working with non-clinical data and lab scientists.
- Familiarity with the biotech and pharmaceutical industry and regulated environments such as GxP.
- Familiarity with networking, CI/CD, and full stack development.
Qualification wording
8+ years building data products as a Data Engineer or in a similar field.
8+ years working in Python and SQL with a focus on data, integrations, and scientific applications.
Expertise in Python and working knowledge of JavaScript, TypeScript, Node, and React.
Experience working with non-clinical data and lab scientists.
Familiarity with the biotech and pharmaceutical industry and regulated environments such as GxP.
Familiarity with networking, CI/CD, and full stack development.
Benefits in the posting
Full benefits wording- Stock options in a VC-backed Series C company
- 100% employer-paid benefits for all eligible employees and immediate family members
- 401(k)
- Unlimited paid time off (PTO)
From the employer’s posting.
About TetraScience
We help the world’s leading life sciences firms turn fragmented scientific data into AI-native assets and scientific workflows that accelerate discovery, development, and manufacturing.
In the employer’s words · Read in context
Posting record
Report an error- Status in our records
- Live
- First seen by us
- Oct 15, 202625 days ago
- Recorded sightings
- 26
- Last seen by us
- Nov 9, 2026
- Employer says posted
- Oct 13, 2026
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.
How this job compares
Time since we first saw it
Day 25
Similar jobs usually come down between day 5 and day 54.
From 12,127 similar postings that came down. Coming down is not always a hire.
TetraScience is hiring
11 open jobs
Open jobs by the week we first saw them, last 12 weeks.
- Data Engineer hiring is picking up
- Takes jobs down at a usual pace
- 9% of open jobs were reposted
See how this role fits your experience
Add your resume and we’ll mark which of these tools you already use, and point out anything in the posting that could rule you out.
- JavaScript
- Python
- SQL
- TypeScript
- AWS
- Databricks
- S3
- Snowflake
- React
Where the posting names them
- 8+ years working in Python and SQL with a focus on data, integrations, and scientific applications. - Expertise in Python and working knowledge of JavaScript, TypeScript, Node, and React. - History leading customer-facing implementation projects across cross-functional teams, managing requirements, timelines, and delivery milestones.
- Act as a forward deployed engineer for a portfolio of biotech, pharmaceutical, and scientific customers. Own the technical relationship, understand their scientific workflows, and deliver solutions that move their programs forward. - Drive AI agents to design and build bidirectional integrations between Tetra OS and customer systems such as ELN, LIMS, MES, and process historians, including serverless push and pull pipelines, stateful connectors, and full stack data applications in Python and TypeScript. - Drive AI agents to design and build comprehensive data schemas and parsers for scientific data from R&D lab instruments, manufacturing, CRO, CDMO, ELN, and LIMS sources, across formats such as .xlsx, .pdf, .txt, .raw, .fid, and many other vendor binaries.
- 8+ years building data products as a Data Engineer or in a similar field. - 8+ years working in Python and SQL with a focus on data, integrations, and scientific applications. - Expertise in Python and working knowledge of JavaScript, TypeScript, Node, and React.
- Familiarity with networking, CI/CD, and full stack development. - Familiarity with cloud engineering on AWS, including core services such as S3, Lambda, ECS, SQS, SNS, EC2, and CloudWatch. - Excellent communication skills, attention to detail, and the confidence to take control of project delivery.
About TetraScience TetraScience is the Scientific Data and AI Company building Tetra OS, the operating system for scientific intelligence. We help the world’s leading life sciences firms turn fragmented scientific data into AI-native assets and scientific workflows that accelerate discovery, development, and manufacturing. TetraScience’s growing ecosystem of strategic partners includes NVIDIA, Databricks, Thermo Fisher Scientific, Snowflake, Google, and Microsoft. In connection with your candidacy, you will be asked to carefully review “The Tetra Way,” authored by our CEO, Patrick Grady; it is impossible to overstate the importance of this document, and you should take it literally as you decide whether our mission, culture, and expectations are right for you.
Your next step
Complete your application on apply.workable.com. The employer’s form will show what is required.
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Has TetraScience posted this job before?
Yes. We’ve followed 2 other Senior Scientific Data Engineer jobs there since June 2026. All 2 are still up.
Demand for Data Engineer roles
New Data Engineer postings at the employers we follow are up 7% over the last 6 weeks compared with the 6 before.
Each bar is one week of new postings. The darkest bars are the last 6 weeks.
Counted from the hiring pages we’ve followed for at least five weeks, so employers we add don’t look like growth. Updated weekly.
About the role
We file this job under Data Engineer, by the work the posting describes.
Data engineers build and run the pipelines that copy data out of apps and outside services into a warehouse or lake, and fix them when a source changes or a load fails.
Expect SQL, Python, a cloud platform, a scheduler such as Airflow, and often tools for large data such as Spark or Kafka.
An analytics engineer works one step later, turning the raw data a data engineer lands into clean tables people can query.
US government figures for database architects
- Median yearly pay, May 2025
- $139,500
- Expected change, 2025 to 2035
- 9.4% more jobsagainst 3.5% for all jobs
The government has no code for data engineers, so these figures are for the closest group, database architects, which includes data integration and data warehousing specialists.
Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-1243.
Job description
About TetraScience
TetraScience is the Scientific Data and AI Company building Tetra OS, the operating system for scientific intelligence. We help the world’s leading life sciences firms turn fragmented scientific data into AI-native assets and scientific workflows that accelerate discovery, development, and manufacturing. TetraScience’s growing ecosystem of strategic partners includes NVIDIA, Databricks, Thermo Fisher Scientific, Snowflake, Google, and Microsoft.
In connection with your candidacy, you will be asked to carefully review “The Tetra Way,” authored by our CEO, Patrick Grady; it is impossible to overstate the importance of this document, and you should take it literally as you decide whether our mission, culture, and expectations are right for you.
What You Will Do
You will join TetraScience's forward deployed teams as a senior, hands-on engineer. In this role, you will work directly with biotech, pharmaceutical, and scientific companies, bringing advanced data and AI technologies into the labs that research, develop, and manufacture medicines. You will work alongside customer scientific, engineering, and IT teams to design, build, and ship integrations and data products on Tetra OS that serve scientific teams across the globe. You will also mentor other scientific data engineers, lead internal design sessions, and partner with Product Managers and Solution Architects to turn customer, product, and engineering objectives into commercialized solutions.
- Act as a forward deployed engineer for a portfolio of biotech, pharmaceutical, and scientific customers. Own the technical relationship, understand their scientific workflows, and deliver solutions that move their programs forward.
- Drive AI agents to design and build bidirectional integrations between Tetra OS and customer systems such as ELN, LIMS, MES, and process historians, including serverless push and pull pipelines, stateful connectors, and full stack data applications in Python and TypeScript.
- Drive AI agents to design and build comprehensive data schemas and parsers for scientific data from R&D lab instruments, manufacturing, CRO, CDMO, ELN, and LIMS sources, across formats such as .xlsx, .pdf, .txt, .raw, .fid, and many other vendor binaries.
- Deploy and test solutions in customer environments, including cloud, on-premises, and hybrid networks, and troubleshoot across the full stack when something breaks.
- Work with product managers, solution architects, business analysts, data architects, and ML engineers to understand business requirements, recommend outcomes, and build best-in-class data products based on consensus.
- Create and enforce designs with quality backed by comprehensive test automation to prove expected behaviors.
- Lead process and technology improvements supporting product quality, developer experience, and platform capabilities.
- Rally the team to finish Agile sprint commitments. Actively surface team inefficiencies and resolve them.
- Drive results. Bring pragmatic urgency to resolving blockers and unclear requirements, and make things happen.
- Provide mentorship to junior scientific data engineers and show leadership on every front.
Requirements
- 8+ years building data products as a Data Engineer or in a similar field.
- 8+ years working in Python and SQL with a focus on data, integrations, and scientific applications.
- Expertise in Python and working knowledge of JavaScript, TypeScript, Node, and React.
- History leading customer-facing implementation projects across cross-functional teams, managing requirements, timelines, and delivery milestones.
- Experience working with non-clinical data and lab scientists.
- Familiarity with the biotech and pharmaceutical industry and regulated environments such as GxP.
- Familiarity with networking, CI/CD, and full stack development.
- Familiarity with cloud engineering on AWS, including core services such as S3, Lambda, ECS, SQS, SNS, EC2, and CloudWatch.
- Excellent communication skills, attention to detail, and the confidence to take control of project delivery.
- Ability to quickly understand a highly technical product and communicate effectively with customers, product management, engineering leadership
Benefits
- Competitive compensation
- Stock options in a VC-backed Series C company
- 100% employer-paid benefits for all eligible employees and immediate family members
- 401(k)
- Unlimited paid time off (PTO)
- Flexible working arrangements
- Company-paid Life Insurance, LTD/STD
The salary range for this position is $140,000 - $200,000 USD Annually. The salary range posted reflects our target baseline for this role. Final compensation is determined by a thorough evaluation of factors including the candidate’s specific experience, localized market data, and internal team equity.
Source details
Source notes
Source excerptsSelected passages from the saved posting. Check the full description for conditions and exceptions.
- Pay
Company-paid Life Insurance, LTD/STD The salary range for this position is $140,000 - $200,000 USD Annually. The salary range posted reflects our target baseline for this role. Final compensation is determined by a thorough evaluation of factors including the candidate’s specific experience, localized market data, and internal team equity.
- Location & working pattern
New York, United States
- Drive AI agents to design and build comprehensive data schemas and parsers for scientific data from R&D lab instruments, manufacturing, CRO, CDMO, ELN, and LIMS sources, across formats such as .xlsx, .pdf, .txt, .raw, .fid, and many other vendor binaries. - Deploy and test solutions in customer environments, including cloud, on-premises, and hybrid networks, and troubleshoot across the full stack when something breaks. - Work with product managers, solution architects, business analysts, data architects, and ML engineers to understand business requirements, recommend outcomes, and build best-in-class data products based on consensus.
- Work authorization
No clear work-authorization passage found. Eligibility is unconfirmed.