Presales Engineer, Data & AI

Satori Analytics

. Lead implementation effort estimates for Data & AI proposals from early sizing through the final commercial offer .

Posted 11/3/2026full-timeAthens • GreeceMid-LevelSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in leading Data & AI project implementations, including effort estimation, architectural design, and client engagement. Proficient in SQL, Python, and data engineering practices, with a strong understanding of cloud services and data modeling techniques.

Highest-signal resume keywords

Expert SQLPython ProgrammingData EngineeringClient-Facing Project EstimationAzure Data Factory

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Data ModellingETL/ELTMachine LearningFeature EngineeringData Quality AssessmentStatistical AnalysisCloud Cost EstimationTechnical Proposal WritingRisk ManagementProject Management

Soft Skills

Clear CommunicationStructured WritingClient EngagementProblem SolvingTeam Collaboration

Tools & Technologies

AzureAWSGCPDatabricksSnowflakeKubernetesGitDockerMLOpsAgile Delivery

Certifications & Qualifications

Azure Solutions ArchitectDatabricks CertificationSnowflake CertificationMicrosoft Fabric Certification

Industry Keywords

Data ScienceAI ServicesPublic-Sector TendersRFP ResponsesLakehouse Architecture

Tech Stack

Tools & technologies

AWSAzureCloudDockerETLGoogle Cloud PlatformKubernetesNoSQLPySparkPythonSnowflakeSQLVault

About the role

Key responsibilities & impact

Lead implementation effort estimates for Data & AI proposals from early sizing through the final commercial offer
Build work breakdown structures across ingestion, pipelines, modelling, lakehouse, BI, ML, MLOps, testing, deployment and project management
Convert effort by role into staffing plans, timelines and milestones
Document assumptions, dependencies, exclusions and risks
Size contingency for data quality, integration and model uncertainty
Estimate cloud and licence running costs
Lead discovery workshops with client executives and technical teams
Design end-to-end architectures with Technical Leadership
Identify feasibility, readiness and value concerns before commitment
Write technical sections of proposals and RFP/tender responses
Build quick PoCs and demos with the pre-sales team
Defend solutions and estimates in client meetings
Provide Delivery with clear scope, estimates and assumptions logs
Stay close to early delivery
Maintain estimation models, templates and benchmarks
Calibrate models against actual project results
Build reusable reference architectures and accelerators

Requirements

What you’ll need

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 data engineering and data science
2+ years in a client-facing role scoping and estimating projects
Expert SQL and Python
Strong PySpark
Experience with ETL/ELT, Azure Data Factory and Databricks
Experience with warehouses and lakehouses including Fabric, Databricks and Snowflake
Experience with relational and NoSQL databases
Knowledge of data modelling including star schema, data vault and SCD
Understanding of BI semantic models and dashboards
Solid grasp of learning paradigms and algorithm families
Hands-on EDA, feature engineering and explainability with the Python stack
At least two real-world ML projects delivered independently
Hands-on GenAI, RAG and agentic workflows
Experience with ready-made AI services such as OCR, sentiment and transcription
Production-grade Python experience
Strong knowledge of Azure, AWS or GCP and their data and AI service pricing
Experience with Git, Docker and Agile delivery
Experience producing bottom-up estimates and staffing plans using WBS, three-point estimation or past-project benchmarks
Commercial understanding of effort, risk, contingency, price and margin
Clear, structured writing and confidence explaining trade-offs to executives
Fluent English
PhD in a STEM field is a bonus
Kubernetes and MLOps tooling experience is a bonus
Azure Solutions Architect, Databricks, Snowflake or Microsoft Fabric certifications are a bonus
Experience bidding for public-sector tenders or large enterprise RFPs is a bonus

Benefits

Comp & perks

Competitive salary
Hybrid work model
Remote work from anywhere in the European Economic Area (EU, Switzerland etc.) or UK, up to 6 weeks per year
Training budget for certifications and courses
Training from Microsoft, AWS, Salesforce, Databricks and other top tech partners
Private insurance
Top-tier tech gear