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The right expert, exactly when you need them.

Senior data scientists and engineers who work as part of your team — not as a separate agency. Continuity, context, and depth. Not just headcount.
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Embedded experts. Not borrowed bodies.

Traditional staff augmentation gives you a CV and a day rate. Six months later the person knows your systems, and then they’re gone — taking the context with them.

DataTheta’s On-Demand model is different. Our experts work as part of your team — in your standups, in your systems, building your capability — with the backing of the wider DataTheta bench when you need to go deeper.

Embedded Data Engineers

Senior data engineers who own your pipelines, platform, and DataOps practices — working as part of your engineering team, not alongside it.

Embedded Data Scientists

Production-focused data scientists who build and maintain models in your environment — with the commercial sense to prioritise work that moves the business.

Embedded AI Engineers

GenAI and LLM specialists who build, deploy, and maintain AI systems in your infrastructure — across RAG, agents, fine-tuning, and MLOps.

Fractional Data Leadership

A senior DataTheta principal as your part-time CDO or Head of Data — strategy, governance, and team leadership without the full-time cost.

BI & Analytics Specialists

Dashboard developers, semantic layer architects, and analytics engineers embedded in your BI team — clearing backlogs and building lasting capability.

Team Build-out Support

On-Demand experts who help you hire and onboard your permanent team — then hand over gracefully as your internal capability grows.

AI systems in production
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Simple to start. Built to last.

Traditional staff augmentation gives you a CV and a day rate. Six months later the person knows your systems, and then they’re gone — taking the context with them.

DataTheta’s On-Demand model is different. Our experts work as part of your team — in your standups, in your systems, building your capability — with the backing of the wider DataTheta bench when you need to go deeper.

Match

Skills & context brief

You tell us the role, the stack, the team, and what success looks like. We match from our bench — usually within 5 working days.

Meet

Introduction & alignment

You meet the proposed expert before any commitment. If the fit isn’t right, we rematch — no pressure, no cost.

Embed

Structured onboarding

Week-one onboarding focused on context — your systems, your team, your priorities. They’re contributing meaningfully by week two.

Grow

Scale and evolve

Add more experts as needs grow. Swap specialisms as priorities shift. Reduce with notice. The model flexes with your business.

The kinds of experts we embed.

Senior Data Engineer

dbt, Airflow, Spark, Snowflake. Builds and maintains production pipelines. Owns DataOps practices. Comfortable leading technical decisions without hand-holding.

ML Engineer / Data Scientist

Builds and deploys production models. Comfortable in Python, MLflow, and cloud ML platforms. Translates business problems into model requirements — and back again.

AI / GenAI Engineer

RAG systems, LLM agents, prompt engineering, and fine-tuning. Deep experience with LangChain, vector databases, and production AI governance.

Analytics Engineer / BI Developer

dbt, Looker, Power BI, Tableau. Builds semantic layers and dashboards that business teams actually use.

Fractional Head of Data / CDO

Senior principal who leads your data function part-time — setting strategy, governing architecture decisions, and building the team around a clear roadmap.

Data Architect / Principal Engineer

Platform design, technology selection, and technical governance for decisions that are too important to get wrong.

Not agency staff aug. Something better.

Bench Bakcing

Commitment Model

Quality Assurance

Knowledge Transfer

The right fit if this is your challenge.

CDO / Head of Data

Building a data team faster than you can hire

Permanent hiring takes 4–6 months. A DataTheta expert is embedded in 2 weeks — and helps you define the role spec for the permanent hire they’ll eventually train.

CTO / Engineering Lead

A specific data engineering skill gap on a critical project

Your team is strong but missing a specific specialism — Kafka expertise, dbt experience, GenAI production knowledge. We fill the gap without permanent overhead.

CEO / Business Owner

A data function is needed but a full team isn't justified yet

A fractional Head of Data plus one embedded engineer gives you strategic direction and execution capacity at a fraction of the full-time cost.

Programme Director

A data-heavy programme that needs consistent expert resource

Multi-year transformation programmes need experts who stay. Our FTE model gives you employee-like continuity with specialist-firm quality assurance.

Healthcare & Insurance FAQs

Answers to common questions about building clinical data platforms, healthcare AI systems, and production-ready analytics in regulated environments.
We usually match the right expert within 5 working days, with structured onboarding so they can contribute meaningfully by week two.
No. Traditional staff augmentation provides headcount. DataTheta provides embedded experts backed by our wider delivery bench, quality assurance, and knowledge transfer process.
Yes. The FTE model is designed for dedicated, full-time engagement with your team, not resources split across multiple clients.
We provide embedded data engineers, data scientists, AI engineers, BI specialists, data architects, and fractional data leaders.
Yes. You can add more experts as priorities grow, swap specialisms as needs change, and reduce with notice.

Tell us the gap. We'll fill it properly.

Describe the role, the problem, or the project. We’ll propose the right expert and have them ready to start within two weeks.

hello@datatheta.com

Naturally Followed By

Data Foundation & Advisory

A fractional CDO who also owns the data strategy and architecture roadmap — one expert, two outcomes.

Data Engineering

An embedded engineer who executes the DataTheta-designed pipeline architecture — continuity between design and delivery.

AI & GenAI

An embedded AI engineer who maintains and extends the GenAI systems we've built — so they keep improving after go-live.

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