Position: Senior Data Engineer (AWS)
Company: Intellias
Experience required: 3y
English level: upper

The smava Data Infrastructure is responsible for building the new Data Platform of smava. This team acts as a bridge between the production teams, the Data Scientists and Analytics.

The client's team builds data pipelines for a variety of use cases and considers data engineering to be one of the most interesting areas where software engineering can be combined with challenging algorithmic problems.

In this role, you will develop distributed services that process data in batch and real-time with a focus on scalability, data quality, and business requirements while delivering the groundwork for the governance team. You will have the opportunity to work on challenging data-related problems and building a self-serve data platform.

**And your responsibilities**:
• Develop, test and maintain data infrastructures based on our tech stack combining proprietary and 3rd party solutions: Python(80%), Java (20%),  AWS Ecosystem especially Lake Formation, Glue, MSK;
• Build and develop reusable technology that enables teams to capture, process, store, and serve their data products in an easy way;
• Build and maintain complex and scalable ETL pipelines between internal & external sources;
• Collaborate closely with business stakeholders such as Marketing, Product, Analytics, etc.;
• Drive data quality and governance checks (e.g. validation, consolidation, deduplication, anonymization, GDPR compliance etc.);
• Identify and evaluate current developments and new technologies;
• Teach, guide, and leadless experienced colleagues from a content perspective.

**Requirements**:
• 3+ years as a software engineer. (Python, and basic Java);
• Practical experience in the building:
• ETL / ELT pipelines;
• Data lakes & raw data layers;
• Cloud data warehousing (ideally with AWS MSK; AWS lake formation, Spark, EMR, Glue, Snowflake).
• Familiar with Spring Framework;
• Experience in designing and implementing state of the art, modular data infrastructures - always driven by use cases and end-user value;
• Strong solution focus, constantly trying to reduce the “time to insight” (analytics data) and “time to product enhancement” (production data);
• Good written and spoken English (Upper Intermediate);
• Quick on the uptake, team player, thrives in an international environment.