Join Sigma Software’s AdTech Competence Center — a 300+ team of experts delivering innovative, high-load, and data-driven advertising technology solutions. Since 2008, we’ve been helping leading AdTech companies and startups design, build, and scale their technology products.

We focus on fostering deep domain expertise, building long-term client partnerships, and growing together as a global team of professionals passionate about AdTech, data, and cloud-based solutions.

Does this sound like an exciting opportunity? Keep reading, and let’s discuss your future role!

CUSTOMER

Our client is an international AdTech company developing modern, privacy-safe, and data-driven advertising platforms. The team works with AWS and cutting-edge data technologies to build scalable, high-performance systems.

PROJECT

The project revolves around the development of a next-generation AdTech platform that powers real-time, data-driven advertising. It leverages AWS, Python, and distributed data frameworks to process large-scale datasets efficiently and securely — enabling businesses to make smarter, faster, and more informed marketing decisions.

Design, develop, and maintain robust data pipelines and ETL processes using Python, SQL, and PySpark
Work with large-scale data storage on AWS (S3, DynamoDB, MongoDB)
Ensure high-quality, consistent, and reliable data flows between systems
Optimize performance, scalability, and cost efficiency of data solutions
Collaborate with backend developers and DevOps engineers to integrate and deploy data components
Implement monitoring, logging, and alerting for production data pipelines
Participate in architecture design, propose improvements, and mentor mid-level engineers.

Personal Profile:

Strong communication and collaboration skills in cross-functional environments
Proactive, accountable, and driven to deliver high-quality results.

5+ years of experience in data engineering or backend development
Strong knowledge of Python and SQL
Hands-on experience with AWS (S3, Glue, Lambda, DynamoDB)
Practical knowledge of PySpark or other distributed processing frameworks
Experience with NoSQL databases (MongoDB or DynamoDB)
Good understanding of ETL principles, data modeling, and performance optimization
Understanding of data security and compliance in cloud environments
Fluent in English (Upper-Intermediate level or higher)

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