Zifo
Senior Data Engineer

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Senior Data Engineer - Pharma
We are looking for a hands-on Senior Data Engineer to act as the primary technical reference for building R&D 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 R&D 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.
Role Responsibilities
Technical leadership & hands-on delivery
- Provide hands-on technical expertise across R&D data, analytics, AI and application components, guiding design and implementation from prototype through to validated production.
- Act as the technical escalation point for complex engineering challenges spanning data pipelines, analytics, AI services and full-stack applications.
- Own end-to-end technical design for data products: ingestion, modelling, curation, serving, and the consuming application or API layer.
- Make and document architecture decisions, including technology evaluation and integration into an existing large-scale data ecosystem.
- Ensure delivery commitments are met without trading away reliability, security, maintainability or data integrity.
Collaboration & mentoring
- Align with enterprise and software architects so that squad-level implementation stays homogenous with the wider ecosystem.
- Mentor data engineers, full-stack engineers and data scientists.
- Lead code reviews and set engineering standards (branching strategy, testing expectations, definition of done, observability baseline).
- Identify skill gaps across the team and contribute to capability building, reusable assets and knowledge sharing.
- Translate between scientific stakeholders and engineers.
Reasons to use Rodeo
I’m in my final year doing Economics and I don’t know whether to apply for grad schemes now or do a masters first. What do you think?
Honest answer — it depends on where you want to end up. A lot of top grad schemes (Big 4, civil service, banking) don’t need a masters. Let’s look at the ones you’d be competitive for now, and we can decide if a masters actually adds anything.
Also worth knowing: most autumn 2026 applications are open now. Timing matters more than you think.
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Graduate Consultant — 2026 Scheme
Why you're a good match
StrongYour economics background and your summer at a regional bank line up with what PwC looks for on the consulting scheme. Applications close in four weeks.
See breakdownIt searches the market for you
Every day your agent scans the market matching roles against what actually matters to you, not just keywords on a CV.
Why you're a good match
You’ve got the grades and the economics background, and your bank internship is exactly the experience this scheme looks for. Apply soon — deadlines close within the month.
Experience fit
Your summer at the bank plus your econometrics coursework map directly to the day-one responsibilities on this scheme — client modelling, market briefings, and deal support.
Only hits
No noise. No "maybe this fits." Just roles with a clear explanation of why they're right — and where to focus when applying.
Governance, security & compliance
- Ensure solutions meet data governance, security and compliance requirements relevant to regulated R&D data.
- Embed governance-by-design: lineage, cataloguing, access control, data quality rules and audit trail designed in from the start.
- Partner with data governance, platform and architecture teams on standards adoption.
Qualifications & experience
- Bachelor's or Master's (or equivalent practical experience) in Computer Science, Data Engineering, Life Sciences, Bioinformatics or a related field.
- Multiple 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.
- Experience operating in a matrixed environment.
Required skills
- Deep, production-grade experience on a modern cloud data platform - Databricks and/or Snowflake.
- A track record of shipping data products in pharma or biotech.
Desirable skills
- Data modelling for analytical and product use - dimensional, data vault, medallion/lakehouse patterns.
- Engineering practice: CI/CD, automated testing (including data testing), infrastructure-as-code, observability, access management, cost awareness.
- API and service design; comfort with the application layer that sits on top of the data (e.g. FastAPI, REST/GraphQL, containerised services).
- Full-stack familiarity (React/TypeScript) sufficient to lead a squad that owns the whole product.
- GenAI/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.
- MLOps and model lifecycle management (MLflow or equivalent).
- Metadata, catalog and data quality tooling; semantic layers; knowledge graphs for scientific data.
- FAIR data principles applied in practice.
- Experience with scientific data management platforms.


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About Zifo:
Zifo is a global R&D 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.
A 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.
We 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.
“It took my CV and asked me questions relevant to understanding what kind of jobs to suggest for me. Suggestions were almost perfect. Jobs were exactly what I’ve been looking for.”
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