Pre-Sales Solution Architect - Data & AI
Warszawa, Krucza 50, Kraków, Aleksandra Lubomirskiego 20, Wrocław, Świdnicka 40, Katowice, -, Gdańsk, -, Warszawa, Country code: PLFull-TimeSenior
Salary4272 - 6714 GBP per month b2b currencySource=conversion; 4946 - 7772 EUR per month b2b currencySource=conversion; 5691 - 8944 USD per month b2b currencySource=conversion; 4543 - 7138 CHF per month b2b currencySource=conversion; 21000 - 33000 PLN per month b2b currencySource=original
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Job Details
- Experience
- 8+ years in solution architecture, data architecture, or pre-sales, with at least 4 years specifically designing enterprise data platforms and analytics solutions.
- Required Skills
- PythonArtificial IntelligenceMachine LearningData engineeringData scienceDatabricksLLMGenerative AI
Requirements
- 8+ years of experience in solution/data architecture or pre-sales.
- Minimum 4 years designing enterprise data platforms and analytics solutions.
- Hands-on expertise in at least two of: Databricks, BigQuery, Redshift, Microsoft Fabric.
- Experience designing solutions on AWS, Azure, and GCP.
- Proficiency with batch and streaming pipelines (dbt, Airflow, Fivetran, Spark, Kafka, Kinesis, Flink).
- Understanding of lakehouse/data mesh principles and open table formats (Delta, Iceberg, Hudi).
- Experience with AI/ML and GenAI data foundations (vector databases, RAG, MLOps).
- Skilled in RFP/RFI responses and delivering technical presentations.
- Excellent communication and interpersonal skills.
- Willingness to travel up to 30% for client engagements.
Responsibilities
- Lead data-centric discovery across source systems and latency/quality requirements.
- Design modern data platforms including lakehouse, data mesh, and event-driven patterns.
- Architect AI-ready data foundations, feature stores, and RAG pipelines.
- Build and deliver high-signal proofs of concept for data migration and analytics.
- Own the technical narrative for RFx responses, SOWs, and proposals.
- Present at executive briefings and architecture deep dives.
- Embed data governance, lineage, and security/privacy into all blueprints.
- Provide technical leadership across the pre-sales and data practice.
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