About the role

We are looking for an experienced Data Warehouse Engineer to join our team and contribute to the development of a large-scale data platform that supports reporting, analytics, and business decision-making. You will help build and optimize ETL pipelines, design data models, and ensure data quality and reliability while transforming complex business requirements into efficient data solutions.

About the project

The project we are working on consists of a web-based application with over 10,000 current users; It is developed for the entire research community to review, monitor, and manage research portfolios. The main goal of the project is to unite distributed and complex organizational processes into one application and help alleviate administrative burdens.

Who are we looking for?

Skills & Experience

5+ years of professional experience in data warehouse development.
Strong hands-on experience with: T-SQL, stored procedures, query performance tuning, and indexing strategies.
Proven experience building and maintaining ETL pipelines with SSIS (SQL Server Integration Services).
Solid understanding of dimensional modeling (star/snowflake schemas), slowly changing dimensions, and data warehouse design best practices.
Experience with source-to-target mapping, data quality checks, and reconciliation processes.
English — Upper Intermediate or above.

Nice to have

Familiarity with Azure data services (Azure SQL MI, IR, Data Factory, SSIS, Storage Account, Key Vault) as a migration/modernization path.
Experience working with healthcare or other regulated/compliance-sensitive data.
Exposure to CI/CD practices for database and ETL deployments.

Responsibilities

Design, build, and maintain ETL/ELT pipelines using SSIS to move and transform data from operational systems into the data warehouse.
Design and evolve dimensional models (facts, dimensions, SCDs) that support reporting and analytics needs.
Write and tune complex T-SQL queries, stored procedures, and views; troubleshoot performance bottlenecks.
Establish and enforce data quality, validation, and reconciliation processes across the warehouse.
Collaborate closely with Product Owners, Business Analysts, and backend engineers to translate business requirements into data models and pipelines.
Document data flows, schemas, and transformation logic to support maintainability and onboarding.
Serve as an escalation point for data-related production issues; perform root-cause analysis and implement long-term fixes.
Monitor ETL job health and proactively address failures, latency, and data drift.

What we offer

Work:

Flexible working hours;
Collaborative, friendly team environment;
Remote/Hybrid work;

Life:

Company social events;
Annual corporate parties;

Health:

Comprehensive medical insurance;

Education:

Allowances for professional education;
English language courses with native speakers;
Internal knowledge-sharing sessions.

About Proxet

Proxet is a professional software development firm trusted by clients from around the world. With our expertise in AI and machine learning, we help businesses reimagine their possibilities and transform ideas into tangible digital solutions. By providing core services with an emphasis on data practices, we shape the future, one step at a time.

If you’d like to join our Proxet Nation and work closely with high-level professionals and our engineers, fill in the form!