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 meetingsand 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 Originally posted on Himalayas