We are looking for an experienced Analytics Engineering Chapter Lead to define, develop, and evolve enterprise-level analytical data layers and modeling standards.
Analytics Engineering Chapter Lead
Tasks
- 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.
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).
Offers
- Full Remote Opportunity
- Friendly & Family-like Atmosphere
- Professional Growth
- Work-Life Balance
Workplace
