Azure Data Architect

O projekcie: We are looking for a Senior Data Architect to shape and evolve an enterprise data platform, with a strong focus on Medallion Architecture (Bronze/Silver/Gold), scalable data modelling, and performance optimisation in large data environments. You will work closely with engineering, analytics, and business teams to design solutions that are reliable, cost-efficient, and ready for BI, analytics, and AI/ML use cases. Wymagania: - Strong track record in data roles such as Data Architect or Data Engineer - Hands-on, in-depth experience with Azure Databricks - Practical knowledge of Medallion Architecture - Excellent SQL skills - Proven capability in data modelling (conceptual, logical, physical) using tools like Erwin, dbt, Lucidchart or equivalent - Experience designing and orchestrating ETL/ELT pipelines (e.g., ADF, Airflow, dbt) - Understanding of tuning strategies for both batch and streaming workloads - Familiarity with governance/security/compliance practices in enterprise environments - Strong communication skills and confidence working with multiple stakeholder groups - Experience in global B2B organisations or domains such as Supply Chain, Sales & Marketing, Manufacturing, Finance Nice to have: - Delta Lake and Apache Spark optimisation experience - Exposure to data mesh / domain-oriented data design - Experience supporting ML teams (data preparation, feature store concepts) Codzienne zadania: - Assess current reporting needs and the way data is organised today, then recommend improvements - Establish a Medallion-style design (Bronze/Silver/Gold) to manage raw, refined, and business-ready datasets - Create and maintain end-to-end data models (conceptual → logical → physical) that serve BI, analytics, and data science teams - Set the rules of the road for governance: data quality checks, lineage, documentation, ownership, and standards - Drive performance optimisation across ingestion, transformations, and querying for high-volume datasets - Work with engineering teams on scalable pipelines and storage patterns that keep costs under control - Evaluate tooling and architectural patterns and introduce improvements where they make sense - Turn business questions into data solutions, balancing speed, scalability, and maintainability - Ensure security and compliance considerations are built into the platform design