Senior Data Architect

About the role

Billigence is looking for a Senior Data Architect to design cloud data solutions, lead client engagements and contribute to winning proposals. You will own technical direction across engineering and client work, ensuring high‑quality, production‑ready data pipelines.

Key responsibilities

• Design and build production‑ready data pipelines and architectures using tools such as Databricks, Snowflake, Azure, dbt and Matillion, set standards and review work to maintain quality.
• Lead end‑to‑end client engagements, from requirements gathering to architecture sign‑off, translating business problems into clean technical solutions.
• Support pre‑sales activities by shaping proposals, running proofs of concept and building client confidence before contracts are signed.
• Mentor junior engineers, run tech sessions and webinars, and foster a culture of continuous learning and improvement.
• Identify and propose smarter, faster, or more automated ways to enhance existing processes and solutions.

Required profile

• Proven experience in data engineering and solution architecture with complex, enterprise‑scale deployments.
• Deep hands‑on expertise with Azure services (Data Factory, Synapse, ADLS) and the broader Azure ecosystem.
• Strong practical experience delivering production solutions on Databricks and Snowflake.
• Solid track record building data warehouses on‑premise and in the cloud, with strong data‑modeling fundamentals.
• Experience writing technical proposals and RFP responses, and comfortable engaging with stakeholders from engineers to C‑level executives.
• Conceptual understanding of machine‑learning and GenAI architectures.
• Fluent in Czech and English at a professional level.

Required skills

• Azure (Data Factory, Synapse, ADLS)
• Databricks
• Snowflake
• dbt
• Matillion

What we offer

• International projects using cutting‑edge data tools.
• Extra 10 days of leave, Multisport card, generous learning budget and open bonus structure.
• Hybrid work model with regular meetings in the Prague office (2–3 days a week).
• AI‑friendly environment encouraging experimentation with new tools.
• Collaborative culture focused on teamwork, knowledge sharing and flexibility.
• Continuous learning and development opportunities.