Job Description

We are seeking a Senior Data Engineer to join our Stellar team and contribute to building world-class products for our clients. By joining Stellar, you’ll become part of a community of 300+ AdTech experts, working alongside seasoned professionals in a culture that values excellence, innovation, and collaboration.

What is Stellar? It is a community, a network, and a dedicated business unit within Sigma Software that specializes in advertising technology solutions. Over the years, we’ve had the opportunity to work with some of the largest AdTech companies in the world. We have helped numerous AdTech startups grow from an idea to a thriving business. Since 2008, we’ve been working with advertising technology businesses to help them envision, build, and support their technology.

We are building a Competence Center where we stay focused on exploring our domain to become the best specialists in the industry. If you are looking to build long-term cooperation, common business development, and building strong relationships with the best Customers, this could be a perfect fit.

• Design, develop, and maintain end-to-end big data pipelines that are optimized, scalable, and capable of processing large volumes of data in real-time and in batch mode
• Collaborate closely with cross-functional stakeholders to gather requirements and deliver high-quality data solutions that align with business goals
• Implement data transformation and integration processes using modern big data frameworks and cloud platforms
• Build and maintain data models, data warehouses, and schema designs to support analytics and reporting needs
• Ensure data quality, reliability, and performance by implementing robust testing, monitoring, and alerting practices
• Contribute to architectural decisions for distributed data systems and help optimize performance for high-load environments
• Ensure compliance with data security and governance standards

Qualifications

• 4+ years of experience in data engineering, big data architecture, or related fields
• Strong proficiency in Python and PySpark 
• Advanced knowledge of SQL (query optimization, complex joins, window functions) and experience with NoSQL databases
• Solid understanding of distributed computing principles and hands-on experience with technologies such as Apache Spark, Kafka, Hadoop, Presto, or Databricks
• Experience designing and managing data warehouses and data lake architectures in cloud environments (AWS, GCP, or Azure)
• Familiarity with data modeling, schema design, and performance tuning for large datasets
• Strong understanding of DevOps practices for automating deployment, monitoring, and scaling big data applications (e.g., CI/CD pipelines)
• At least an Upper-Intermediate level of English

Additional Information

PERSONAL PROFILE

• Excellent communication skills and the ability to work effectively in cross-cultural and cross-functional teams