Principal Data Engineer
Il y a 4 heures
, Belgique
Zifo RnD Solutions
Temps plein
Gratuit avec email ou Google
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Gratuit avec email ou Google
ppWe are looking for a hands-on Principal Data Engineer to act as the primary technical reference for building RD data products. The role sits at the intersection of scientific domain, data platform, and engineering delivery. You will guide technical design and implementation across data engineering, analytics, AI and application components within an RD data and AI ecosystem, while carrying accountability for engineering quality, mentoring and delivery outcomes.
This is not a coordination role. You will write code, review code, and own challenging technical problems in diverse innovation ecosystems. /p h3Role Responsibilities /h3 h3Technical leadership hands-on delivery /h3 ul liProvide hands-on technical expertise across RD data, analytics, AI and application components, guiding design and implementation from prototype through to validated production. /li liAct as the technical escalation point for complex engineering challenges spanning data pipelines, analytics, AI services and full-stack applications. /li liOwn end-to-end technical design for data products: ingestion, modelling, curation, serving, and the consuming application or API layer. /li liMake and document architecture decisions, including technology evaluation and integration into an existing large-scale data ecosystem. /li liEnsure delivery commitments are met without trading away reliability, security, maintainability or data integrity. /li liAlign with enterprise and software architects so that squad-level implementation stays homogenous with the wider ecosystem. /li liMentor data engineers, full-stack engineers and data scientists. /li liLead code reviews and set engineering standards (branching strategy, testing expectations, definition of done, observability baseline). /li liIdentify skill gaps across the team and contribute to capability building, reusable assets and knowledge sharing. /li liTranslate between scientific stakeholders and engineers. /li /ul h3Governance, security compliance /h3 ul liEnsure solutions meet data governance, security and compliance requirements relevant to regulated RD data. /li liEmbed governance-by-design: lineage, cataloguing, access control, data quality rules and audit trail designed in from the start. /li liPartner with data governance, platform and architecture teams on standards adoption. /li /ul h3Qualifications experience /h3 ul liBachelor's or Master's (or equivalent practical experience) in Computer Science, Data Engineering, Life Sciences, Bioinformatics or a related field. /li liMultiple years in data engineering, analytics engineering, software engineering or AI platform roles, with at least 3 years operating at technical lead/senior level guiding design and delivery across multiple teams or workstreams. /li liExperience operating in a matrixed environment. /li /ul h3Required skills /h3 ul liDeep, production-grade experience on a modern cloud data platform
- Databricks and/or Snowflake. /li liA track record of shipping data products in pharma or biotech. /li liData modelling for analytical and product use
- dimensional, data vault, medallion/lakehouse patterns. /li liEngineering practice: CI/CD, automated testing (including data testing), infrastructure-as-code, observability, access management, cost awareness. /li liAPI and service design; comfort with the application layer that sits on top of the data (e.g. FastAPI, REST/GraphQL, containerised services). /li liFull-stack familiarity (React/TypeScript) sufficient to lead a squad that owns the whole product. /li liGenAI/LLM engineering in a regulated setting: RAG over scientific documents, evaluation frameworks, guardrails, LLMOps, and a realistic view of where GenAI does and does not belong. /li liMLOps and model lifecycle management (MLflow or equivalent) /li liMetadata, catalog and data quality tooling; semantic layers; knowledge graphs for scientific data. /li liFAIR data principles applied in practice. /li liExperience with scientific data management platforms. /li /ul h3About Zifo: /h3 pZifo is a global RD solutions provider focused on the industries of Pharma, Biotech, Manufacturing QC, Medical Devices, specialty chemicals and other research-based organizations. Our team’s knowledge of science and expertise in technology help Zifo better serve our customers around the globe, including 7 of the Top 10 Biopharma companies. /p pA passion to learn and a spirit of teamwork characterizes us. We revere excellence and the value everyone brings. At Zifo, our culture is one where we debate, challenge ourselves and interact with all alike. /p pWe look for Science – Biotechnology, Pharmaceutical Technology, Biomedical Engineering, Microbiology etc. We possess scientific and technical knowledge and bear professional and personal goals. While we have a “no doors” policy to promote free access within, we do have a tough door to walk in. We search with a two-point agenda – technical competency and cultural adaptability. /p /p
This is not a coordination role. You will write code, review code, and own challenging technical problems in diverse innovation ecosystems. /p h3Role Responsibilities /h3 h3Technical leadership hands-on delivery /h3 ul liProvide hands-on technical expertise across RD data, analytics, AI and application components, guiding design and implementation from prototype through to validated production. /li liAct as the technical escalation point for complex engineering challenges spanning data pipelines, analytics, AI services and full-stack applications. /li liOwn end-to-end technical design for data products: ingestion, modelling, curation, serving, and the consuming application or API layer. /li liMake and document architecture decisions, including technology evaluation and integration into an existing large-scale data ecosystem. /li liEnsure delivery commitments are met without trading away reliability, security, maintainability or data integrity. /li liAlign with enterprise and software architects so that squad-level implementation stays homogenous with the wider ecosystem. /li liMentor data engineers, full-stack engineers and data scientists. /li liLead code reviews and set engineering standards (branching strategy, testing expectations, definition of done, observability baseline). /li liIdentify skill gaps across the team and contribute to capability building, reusable assets and knowledge sharing. /li liTranslate between scientific stakeholders and engineers. /li /ul h3Governance, security compliance /h3 ul liEnsure solutions meet data governance, security and compliance requirements relevant to regulated RD data. /li liEmbed governance-by-design: lineage, cataloguing, access control, data quality rules and audit trail designed in from the start. /li liPartner with data governance, platform and architecture teams on standards adoption. /li /ul h3Qualifications experience /h3 ul liBachelor's or Master's (or equivalent practical experience) in Computer Science, Data Engineering, Life Sciences, Bioinformatics or a related field. /li liMultiple years in data engineering, analytics engineering, software engineering or AI platform roles, with at least 3 years operating at technical lead/senior level guiding design and delivery across multiple teams or workstreams. /li liExperience operating in a matrixed environment. /li /ul h3Required skills /h3 ul liDeep, production-grade experience on a modern cloud data platform
- Databricks and/or Snowflake. /li liA track record of shipping data products in pharma or biotech. /li liData modelling for analytical and product use
- dimensional, data vault, medallion/lakehouse patterns. /li liEngineering practice: CI/CD, automated testing (including data testing), infrastructure-as-code, observability, access management, cost awareness. /li liAPI and service design; comfort with the application layer that sits on top of the data (e.g. FastAPI, REST/GraphQL, containerised services). /li liFull-stack familiarity (React/TypeScript) sufficient to lead a squad that owns the whole product. /li liGenAI/LLM engineering in a regulated setting: RAG over scientific documents, evaluation frameworks, guardrails, LLMOps, and a realistic view of where GenAI does and does not belong. /li liMLOps and model lifecycle management (MLflow or equivalent) /li liMetadata, catalog and data quality tooling; semantic layers; knowledge graphs for scientific data. /li liFAIR data principles applied in practice. /li liExperience with scientific data management platforms. /li /ul h3About Zifo: /h3 pZifo is a global RD solutions provider focused on the industries of Pharma, Biotech, Manufacturing QC, Medical Devices, specialty chemicals and other research-based organizations. Our team’s knowledge of science and expertise in technology help Zifo better serve our customers around the globe, including 7 of the Top 10 Biopharma companies. /p pA passion to learn and a spirit of teamwork characterizes us. We revere excellence and the value everyone brings. At Zifo, our culture is one where we debate, challenge ourselves and interact with all alike. /p pWe look for Science – Biotechnology, Pharmaceutical Technology, Biomedical Engineering, Microbiology etc. We possess scientific and technical knowledge and bear professional and personal goals. While we have a “no doors” policy to promote free access within, we do have a tough door to walk in. We search with a two-point agenda – technical competency and cultural adaptability. /p /p
