Flexible Work Model
Work from home, from the office, or in a hybrid format that supports focus and collaboration.
ABOUT THE ROLE
In this role, you will contribute to designing and implementing scalable cloud-based data platforms with a strong focus on Snowflake and modern ELT architectures. You will collaborate with technical and business stakeholders to design reliable data solutions, optimize data platforms, and support organizations in building modern analytics ecosystems within AWS environments. You will participate throughout the full project lifecycle, from solution design and proof of concepts to production implementation.
RESPONSIBILITIES
- Design and support implementation of scalable data platforms and analytics solutions using Snowflake and AWS services
- Design, develop, and optimize ELT pipelines and data transformation workflows using dbt and SQL
- Define data models, data warehouse architectures, and source-to-target mappings to support analytics and reporting workloads
- Collaborate with stakeholders to gather requirements and translate business needs into scalable technical solutions
- Support data ingestion, transformation, and orchestration processes across cloud-based data platforms
- Participate in architecture discussions and contribute to data platform evolution, performance optimization, and engineering best practices
- Ensure data quality, governance, and maintainability through automated testing, documentation, and CI/CD practices
- Create and maintain architecture documentation, data models, and technical design artifacts
- Participate throughout the full project lifecycle, from discovery and PoCs to production implementation
REQUIREMENTS
- Proven experience designing modern data platforms and cloud-based data warehouse solutions
- Strong hands-on experience with Snowflake, including data modeling, performance optimization, and analytics workloads
- Experience designing and building ELT pipelines using dbt, SQL, and modern data engineering practices
- Strong expertise with AWS services supporting modern data platforms
- Proficiency in SQL and Python for data engineering and automation
- Experience with orchestration tools such as Apache Airflow or MWAA
- Understanding of data warehousing concepts, dimensional modeling, and modern data architecture patterns
- Familiarity with CI/CD practices, data quality validation, and version control for data engineering workflows
- Upper-intermediate or higher level of English
SoftServe is an equal opportunity employer. Qualified applicants will receive consideration regardless of race, color, ancestry, ethnicity, national origin, religion, sex, sexual orientation, gender identity or expression, age, citizenship, disability, health condition, marital or family status, veteran status, or any other characteristic protected by applicable law.
Role Summary
Location
Poland
Work type
Remote/Office
Direction
Engineering & Technology
Subdirection
Data & Analytics
Tech level
Lead
Apply Now
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About us
We are a digital engineering and technology consulting company where expertise grows alongside people. For more than 30 years, we have been elevating technology: helping organizations navigate complex business challenges by combining deep engineering knowledge with thoughtful, research-backed innovation. Our teams work across key areas: digital engineering, data and analytics, Сloud, and AI/ML. In each, we deliver practical, scalable solutions rooted in real business needs and measurable human impact.
You bring your perspective and ambition. We create an environment where your work meets clarity, confidence, and purpose.
We offer
Compensation & Benefits
Competitive, market-based pay, benchmarked by role and location — plus health coverage, paid time off, wellness support, and learning opportunities.
People-first Leadership
Approachable leaders who communicate openly, keep teams close to the strategy, and support long-term planning.
Advanced tech communities
Stay close to AI/ML, Cloud, Quantum Computing, IoT, and Robotics communities, with projects built on modern frameworks.