Senior Data Architect

Stack

Responsibilities

• ▹Design and build production-ready data pipelines and architectures using Databricks or Snowflake, Azure, dbt, Matillion or whatever the right tool is for the job
• ▹Own the technical direction, set the standard and review the work so quality does not slip when deadlines get tight
• ▹Lead client engagements end-to-end, from the first requirements call to architecture sign-off, translating business problems into clean technical solutions
• ▹Help with pre-sales: shape the proposal, run the PoC and give clients confidence before the contract is signed
• ▹Grow the team by mentoring junior engineers and sharing knowledge through tech sessions and webinars
• ▹Take in ideas and act on opportunities to make processes smarter, faster or more automated

Requirements

• ▹Proven experience in data engineering and solution architecture, having led complex, enterprise-scale deployments
• ▹Deep hands-on experience with Azure as the primary cloud platform: Data Factory, Synapse, ADLS and the broader Azure ecosystem
• ▹Strong practical experience with Databricks and Snowflake: production solutions designed and delivered on both
• ▹Solid track record of building data warehouses on-prem and in the cloud, with strong data modeling fundamentals
• ▹Experience writing technical proposals and RFP responses, translating architecture decisions into language that wins deals
• ▹Comfortable engaging with stakeholders at all levels, from engineers to C-level
• ▹Conceptual understanding of ML and GenAI architectures: where they fit and how to design for them
• ▹Hands-on, proactive, able to take a project from whiteboard to production without losing momentum
• ▹Fluent Czech and English on a professional level

Soft skills

What we offer

• ▹International projects using cutting-edge data tools
• ▹Extra 10 days of leave
• ▹Multisport card
• ▹Generous annual learning budget
• ▹Open bonus structure
• ▹Local and international knowledge sharing sessions
• ▹Hybrid flexibility: regularly in the Prague office (around 2-3 days a week), free to choose what works best beyond that
• ▹AI-friendly by default: experimenting with new tools and treating AI as a genuine work partner
• ▹Collaborative culture: real teamwork, support, knowledge sharing, flexibility
• ▹Continuous learning and development
• ▹A diverse, global team of friendly data professionals

About the company

Billigence is a global Business Intelligence, Data Analytics and AI consultancy offering services in data governance, cloud architecture, data engineering and data insights.