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TetraScience

TetraScience

www.tetrascience.com

2 Jobs

150 Employees

About the Company


TetraScience is the Scientific Data and AI Cloud company with a mission to accelerate scientific discovery and improve and extend human life.

The Tetra Scientific Data and AI Cloud(TM) is the only open, cloud-native platform purpose-built for science that connects lab instruments, informatics software, and data apps across the biopharma value chain and delivers the foundation of harmonized, actionable scientific data necessary to transform raw data into accelerated and improved scientific outcomes.

Through the Tetra Partner Network, market-leading vendors access the power of our cloud to help customers maximize the value of their data.

Listed Jobs

Company background Company brand
Company Name
TetraScience
Job Title
Technical Account Manager (TAM), United Kingdom
Job Description
**Job Title:** Technical Account Manager (TAM) **Role Summary:** Serve as the primary technical partner for pharmaceutical and biotech customers, translating business objectives into architecture, implementation, and adoption of TetraScience’s data‑and‑AI solutions. Drive customer ROI, mitigate risk, and ensure long‑term project success through strategic planning, stakeholder alignment, and technical leadership across the sales‑to‑delivery lifecycle. **Expectations:** - Act as trusted advisor and senior technical liaison for strategic accounts. - Deliver proactive, prescriptive guidance on scientific data and AI architectures. - Accelerate adoption, manage risk, and achieve measurable business outcomes for customers. - Support sales growth through technical enablement, demos, and solution mapping. - Coordinate with internal product, engineering, and partner teams (e.g., Databricks, Google) to align roadmaps and resolve escalations. **Key Responsibilities:** - Serve as the primary technical point of contact for assigned strategic accounts. - Lead end‑to‑end lifecycle engagement from pre‑sales through delivery and ongoing adoption. - Conduct regular technical health reviews, identify risks, and recommend optimizations. - Develop and present tailored product demonstrations and ROI calculations. - Support proof‑of‑concepts, co‑innovation projects, and expansion opportunities. - Manage escalation resolution and ensure timely issue remediation. - Build and maintain senior‑level relationships with scientists, R&D IT analysts, and internal stakeholders. - Contribute to RFP/RFI responses with detailed technical specifications. - Oversee project timelines, scope, and stakeholder coordination to ensure on‑schedule delivery. **Required Skills:** - 5+ years senior technical architecture experience in life‑sciences or related R&D IT environments. - Strong knowledge of scientific data, AI, and analytics workflows. - Proficiency with cloud data platforms (AWS data services, Azure, Google Cloud) and cloud RDBMS (Snowflake, Redshift) and NoSQL/Databricks. - Experience with big‑data technologies (Spark, data warehousing). - Data modeling (logical, physical, conceptual) and data governance/quality concepts. - Familiarity with BI/analytics tools (Tableau, Power BI, QlikView). - Commercial tech sales support and ability to map business requirements to technical solutions. - Excellent communication, stakeholder management, and negotiation skills. - Ability to create technical demos, proposals, and conduct enablement sessions. **Required Education & Certifications:** - Academic background in a scientific discipline (e.g., biology, chemistry, bioinformatics, or related life‑sciences field). - Equivalent or additional 5+ years professional experience in life‑sciences data, R&D IT, or informatics. - Relevant certifications (e.g., AWS Certified Solutions Architect, Snowflake, Databricks, or other cloud/data platform credentials) are a plus but not mandatory.
Manchester, United kingdom
On site
Mid level
07-11-2025
Company background Company brand
Company Name
TetraScience
Job Title
Scientific Data Engineer - EMEA
Job Description
**Job Title** Senior Scientific Data Engineer – EMEA **Role Summary** Lead the design, development, and delivery of production‑grade data engineering solutions for scientific lab data. Act as a mentor and technical lead for junior engineers while collaborating closely with Product Management and Solution Architecture to translate business requirements into scalable, high‑quality data models, integration pipelines, and automated workflows. **Expectations** - 8+ years of data engineering or equivalent experience. - Extensive, hands‑on expertise in Python and SQL (8+ years). - Proven track record of leading cross‑functional projects, managing requirements, and meeting delivery milestones (6+ years). - Experience managing multiple customer‑focused implementation projects and driving sustainable processes (4+ years). - Strong communication, attention to detail, and ownership of project outcome. - Deep familiarity with life‑science data streams, wet‑lab instruments, and scientific data formats (.txt, .xls, .pdf, .raw, .fid, etc.). **Key Responsibilities** - Architect and implement scalable data models, prototypes, and integration solutions that drive customer success. - Conduct design sessions, translate business requirements into technical specifications, and guide solution development. - Build and maintain robust data pipelines, including file parsers for diverse scientific instrument outputs. - Enforce quality through unit tests, integration tests, and utility functions; act as the quality gatekeeper. - Lead process and technology improvements company‑wide to enhance product quality and developer experience. - Manage Agile sprint commitments, surface and resolve team inefficiencies, and ensure timely delivery. - Mentor junior data engineers, provide technical guidance, and model leadership across the team. **Required Skills** - Python (3+), SQL, and relational/NoSQL database design. - Data pipeline construction (ETL/ELT) and orchestration tools. - Unit testing, integration testing, and continuous integration practices. - Agile / Scrum methodology, sprint planning, and backlog grooming. - Strong analytical problem‑solving and debugging skills. - Excellent verbal and written communication, stakeholder engagement, and cross‑team collaboration. - Domain knowledge in life sciences, laboratory instrumentation, and scientific data formats. **Required Education & Certifications** - Bachelor’s degree in Computer Science, Data Science, Engineering, or a related technical field. - (Optional) Advanced certifications in data engineering, cloud platforms, or life‑science data standards may be advantageous.
London, United kingdom
Hybrid
Senior
22-11-2025