Senior DWH Engineer / Data Architect

About The Project We are building a new Data Platform that consolidates data from various third-party SaaS products into centralized analytical environments such as Snowflake, Databricks, and Microsoft Fabric. The platform will provide clients with secure access to reporting and analytics-ready data through Data Warehouses and APIs.

This is a greenfield initiative where the selected engineer will play a key role in defining architecture, selecting technologies, building ETL/ELT pipelines, and establishing the foundation for a long-term Data Platform offering.

Requirements

• 5+ years of experience in Data Engineering or Data Architecture
• Strong commercial experience with Snowflake and/or Databricks or Microsoft Fabric
• Experience designing and building Data Warehouse or Data Lake solutions
• Hands-on experience with Big Data processing
• Strong ETL/ELT pipeline development experience
• Excellent SQL skills
• Experience working with large-scale datasets (terabytes of data)
• Strong understanding of data modeling and performance optimization
• Upper-Intermediate+ English
• Ability to work independently and make architecture decisions

Responsibilities

• Design and implement scalable Data Warehouse and Data Lake architectures
• Build and optimize ETL/ELT pipelines
• Develop data ingestion solutions for multiple third-party SaaS platforms
• Process and transform large volumes of structured data
• Design incremental data synchronization processes
• Evaluate and introduce modern Data Engineering tools and technologies
• Optimize platform performance, scalability, and cost efficiency
• Collaborate with stakeholders to define the future architecture of the platform
• Ensure high-quality, analytics-ready data for reporting and downstream consumer

Schedule: Flexible Part-Time (approx. 20-25 hours per week). Agile schedule with the ability to balance daily workload (4-6 hours/day).No late meetings and overtime.

Why Choose Us? What Do We Offer that's Exceptional?

• Greenfield architecture with no legacy constraints
• Opportunity to build a modern Data Platform from scratch
• Freedom to influence technology choices and architectural decisions
• Challenging Big Data and distributed data processing problems
• High level of ownership and autonomy
• Direct impact on a new strategic company initiative
• Work with the latest technologies in the Data Engineering ecosystem