Advise enterprise customers on hybrid-cloud storage solutions, lead technical discovery and proof-of-concept deployments, and partner with sales to advance regional opportunities from initial pitch through technical alignment.
Presales Engineer (Data & AI)
π Description
- Lead implementation estimates for Data & AI proposals, from early sizing through the final commercial offer.
- Create work breakdowns across data engineering, BI, ML, MLOps, testing, deployment, and project management; translate effort into staffing plans and timelines.
- Document assumptions, dependencies, exclusions, risks, contingency, and cloud and licence running costs.
- Lead client discovery workshops and design end-to-end architectures with technical leadership.
- Write technical proposal and RFP responses, build PoCs and demos, and present solutions and estimates to clients.
- Hand over clear scopes to Delivery, stay close to early delivery, and improve estimation models and reusable architectures.
π οΈ Requirements
- A PhD in a STEM field.
- Kubernetes and MLOps tooling for deploying and monitoring models in production.
- Certifications such as Azure Solutions Architect, Databricks, Snowflake or Microsoft Fabric.
- Experience bidding for public-sector tenders or large enterprise RFPs.
β¨ Benefits
- Competitive salary and hybrid work model β come hang out in our Athens office or work remotely from anywhere in European Economic Area (EU, Switzerland etc.) or UK (up to 6 weeks per year).
- Training budget to level up your skills from the top tech partners in the market (Microsoft, AWS, Salesforce, Databricks etc.) β whether it's certifications or courses, we've got you covered.
- Private insurance, top-tier tech gear, and the chance to work with a stellar crew.
Full job description
Are you passionate about Data & AI? π€
At Satori Analytics we bring clarity to enterprise decision making through Data & AI. We are a pure-play Enterprise AI company with 100+ solutions running in production β GenAI agents and assistants, forecasting and optimisation models, digital twins, and the data estates that make them work. Ten years of doing one thing well has given us a 90% client retention and the title of AI & Data Provider of the Year 2026.
We are 120+ engineers, data scientists and AI specialists, working alongside 50+ large enterprises across energy, financial services, retail & CPG, manufacturing and health. We embed our teams inside our clientsβ, ship pro-code and low-code agents, build AI culture from the inside, and build our own IP. Join us as we lead the AI & data revolution in Europe.
Weβre looking for the technical authority in our sales cycle: the person who turns a clientβs business problem into an architecture, a work breakdown, a team and a timeline our Delivery team can sign up to. This isnβt a demo-only role. Youβll estimate the work of data engineers, AI engineers and data scientists and defend those numbers in front of clients and our own engineers, so you need the depth of all three. Within a year, every proposal we send should carry an estimate Delivery has signed off, built on a shared model calibrated against real projects.
What Your Day Might Look Like:
- Own the estimate: Lead the implementation effort estimate for our Data & AI proposals, from early sizing to the final commercial offer.
- Break it down: Build work breakdowns across ingestion, pipelines, modelling, lakehouse, BI, ML, MLOps, testing, deployment and PM, then turn effort by role into a staffing plan, timeline and milestones.
- Name the unknowns: Make assumptions, dependencies, exclusions and risks explicit, size contingency for data quality, integration and model uncertainty, and estimate cloud and licence running costs.
- Run discovery: Lead workshops with client executives and technical teams, design end-to-end architectures with our Technical Leadership, and flag what isnβt feasible, ready or worth building before we commit.
- Write and win: Write the technical sections of proposals and RFP/tender responses, build quick PoCs and demos with our pre-sales team, and defend solutions and estimates in client meetings.
- Hand over cleanly: Give Delivery a clear scope, estimate and assumptions log so what we sell is what we build, and stay close to early delivery.
- Sharpen the model: Maintain Satoriβs estimation models, templates and benchmarks, calibrate them against actuals, and build reusable reference architectures and accelerators.
Requirements
Your Superpowers π
- BSc in Computer Science, Engineering, Mathematics, Physics or a related field, plus an MSc in Data Science, Computer Science or another STEM discipline.
- 6+ years delivering data & AI projects (ideally in a consultancy) across both data engineering and data science, including 2+ years in a client-facing role where you scoped and estimated projects.
- Data engineering: Expert SQL and Python, strong PySpark, ETL/ELT (Azure Data Factory, Databricks), warehouses and lakehouses (Fabric, Databricks, Snowflake), relational and NoSQL databases, data modelling (star schema, data vault, SCD), and a feel for the effort behind BI semantic models and dashboards.
- Data science & ML: Solid grasp of the main learning paradigms and algorithm families, hands-on EDA, feature engineering and explainability with the Python stack, and at least two real-world ML projects you delivered yourself (e.g. churn, CLV, forecasting, recommenders, pricing, segmentation).
- AI engineering: Hands-on GenAI (RAG, agentic workflows), ready-made AI services (OCR, sentiment, transcription), and production-grade Python β you know what it takes to go from notebook to enterprise-grade software.
- Cloud & ways of working: Strong knowledge of Azure, AWS or GCP, including how their data and AI services are priced, plus Git, Docker and Agile delivery.
- Estimation track record: Bottom-up estimates and staffing plans using WBS, three-point estimation or past-project benchmarks, and the commercial sense to see how effort, risk and contingency become price and margin.
- Clear, structured writing and the confidence to explain trade-offs to executives and hold your ground on scope.
- Fluent English; Greek is a strong plus.
Bonus Points for β¨
- A PhD in a STEM field.
- Kubernetes and MLOps tooling for deploying and monitoring models in production.
- Certifications such as Azure Solutions Architect, Databricks, Snowflake or Microsoft Fabric.
- Experience bidding for public-sector tenders or large enterprise RFPs.
Benefits
Perks on Perks:
- Competitive salary and hybrid work model β come hang out in our Athens office or work remotely from anywhere in European Economic Area (EU, Switzerland etc.) or UK (up to 6 weeks per year).
- Training budget to level up your skills from the top tech partners in the market (Microsoft, AWS, Salesforce, Databricks etc.) β whether it's certifications or courses, we've got you covered.
- Private insurance, top-tier tech gear, and the chance to work with a stellar crew.
Ready to create some data magic with us? Hit that apply button and let's get started.
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