Data Engineer
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