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

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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