Data Engineer

About the role

Design and evolve enterprise data architecture aligned with business and analytics needs. Define and enforce data modeling standards across systems, and architect scalable data pipelines using modern technologies.

Key responsibilities

• Design and evolve enterprise data architecture aligned with business and analytics needs.
• Define and enforce data modeling standards (conceptual, logical, and physical models) across systems.
• Architect and guide implementation of scalable data pipelines (batch & real-time) using Spark, Kafka, Airflow.
• Design efficient data lake and data warehouse architectures using MinIO (object storage) and ClickHouse (OLAP database).
• Collaborate with Data Engineers to ensure data models are optimized for performance and aligned with the data platform standards.
• Work with Product Owners and Business Analysts to ensure alignment between data structures and business requirements.
• Lead data governance initiatives: metadata management, data cataloging, data lineage, and access control.
• Review and validate dbt models and ensure consistency in business logic and transformations.
• Evaluate new technologies and propose architectural improvements to enhance scalability, flexibility, and performance.
• Provide architectural guidance and mentorship to engineering teams.

About you

• 5+ years of experience in data architecture, data modeling, or enterprise data design.
• Strong experience with dimensional modeling, star/snowflake schema, and OLAP performance tuning.
• Proficiency in SQL and Python for data exploration and prototyping.
• Hands-on experience with data processing frameworks (e.g., Apache Spark, Kafka) and orchestration tools (e.g., Airflow).
• Experience designing and working with data lake/warehouse systems such as MinIO and ClickHouse.
• Familiarity with dbt (Data Build Tool) and its role in transformation layer management.
• Strong understanding of data governance, security, and data lifecycle management.