Data Architect

Data & Analytics

Reference: #214652

Start Date: ASAP Duration: > 12 months Language: English/Full professional Seniority: Mid level Location: Warsaw (first 2-3 months of office visits once a week, then occasionally) Rate: up to 190 PLN net/h Contract: B2B

Summary

The Data Architect is responsible for defining and implementing the architecture, standards, and best practices for scalable Data Hubs that support various analytical and operational use cases, including Generative AI. The role emphasizes strategic thinking and technical expertise to ensure quality, governance, scalability, and performance of data systems.

Responsibilities

• Data Hub Architecture: Design and oversee the implementation of scalable, efficient data models integrating multiple sources.
• Technology & Standards: Define patterns, templates, and best practices for data engineering.
• Governance & Security: Establish data governance, access policies, and security frameworks.
• Scalability & Performance: Ensure efficient storage, retrieval, and processing of large-scale datasets.
• Real-Time & Batch Processing: Architect solutions for streaming and batch data ingestion, transformation, and updating models.
• Monitoring & Data Quality: Implement automated data validation, anomaly detection, and proactive issue resolution.
• Cross-Team Collaboration: Work with engineers, analysts, and AI/ML teams to align architecture with business needs.
• Documentation & Knowledge Sharing: Maintain comprehensive architecture documentation and mentor engineers.

• Cloud & Data Architecture: Strong expertise in Azure-based data platforms and Databricks.
• Databricks & Spark: Deep knowledge of Databricks, Delta Lake, Apache Spark.
• Data Modeling: Experience with dimensional, relational, and NoSQL models.
• Data Governance & Security: Strong background in data policies, lineage, and compliance.
• Azure Data Stack: Proficiency with Data Factory, ADLS, Synapse, Azure SQL, Event Hubs.
• Automation & DevOps: Experience with CI/CD, Terraform, Kubernetes/AKS, Docker.
• Leadership & Communication: Ability to define strategy, mentor engineers, and drive best practices adoption.
• Documentation & Standards: Strong ability to create and maintain clear architectural documentation.

Nice to Have

• Experience with other cloud platforms or data architecture frameworks.
• Familiarity with data science tools and techniques.