Pozíció leírása / Job description

We are looking for an experienced Analytics Engineering Chapter Lead to define, develop, and evolve enterprise-level analytical data layers and modeling standards.

Data Modeling: Design and maintain performance-optimized, denormalized structures for reporting and analytics.
Pipeline Optimization: Build and refine transformation pipelines between core data layers and the reporting front-end.
Standards & Governance: Define and enforce naming conventions, modeling guidelines, and engineering best practices.
Technical Leadership: Mentor Analytics Engineers, conduct code reviews, and ensure high-quality output.
Stakeholder Collaboration: Act as a bridge between Data Engineers and BI developers to translate requirements into robust data structures.
System Improvement: Continuously scale and optimize analytical datasets for better maintainability.

Elvárások / Requirements

SQL: Advanced skills for complex transformations and performance tuning.
DBT (data build tool): Extensive experience in managing transformation frameworks.
Azure Synapse: Proven experience in cloud-based data warehousing.
Power BI: Ability to design high-performance layers specifically for BI consumption.
Data Architecture: Solid understanding of dimensional modeling and denormalization.
Technical Leadership: Ability to make architectural decisions and lead a technical team.

Nice to Have

Databricks: Experience with Spark-based processing is a significant plus.
Modern Workflows: Familiarity with CI/CD, version control (Git), and automated testing of data models.
Large Ecosystems: Experience working with diverse data consumers (Data Science, BI, and Finance).

Amit nyújtunk / Benefits