Join our dynamic team as a Data Engineer, where you will be instrumental in building and maintaining robust data infrastructure. Your role will focus on developing solutions for data generation, collection, and processing, ensuring the integrity and efficiency of our data pipelines.

This position offers a key opportunity to integrate and manage the systems supporting data analysis within the Swisscom ecosystem. You will collaborate closely with data scientists, analysts, and other key stakeholders to guarantee data is accessible, accurate, and ready for business intelligence and analytical initiatives.

We are seeking individuals with a strong background in data engineering, excellent problem-solving skills, and a proactive attitude. The ability to work effectively both independently and within a collaborative environment, and mentor junior team members, is highly valued.

Design, develop, and maintain sophisticated data solutions for data generation, collection, and processing. Create and manage efficient data pipelines, ensuring high standards of data quality and implementing robust ETL processes. Integrate and unify diverse database systems into the Swisscom ecosystem by developing and maintaining scalable ETL pipelines for large data volumes, while upholding data governance and security. Collaborate within cross-functional teams, including data scientists, analysts, and business partners, to deliver effective data solutions and communicate technical insights to non-technical audiences. Develop and refine data architectures and transformation technologies to meet evolving analytical demands. Manage and optimize databases for peak performance, scalability, and continuous availability. Incorporate data from a variety of sources, including APIs, external cloud platforms, and internal systems. Proactively identify and resolve performance bottlenecks in data processing and optimize database and pipeline efficiency. Implement comprehensive monitoring and logging solutions to ensure data reliability and quality.

A minimum of 2-8 years of experience in Data Engineering is required. Proficiency in SQL, Python, and data warehousing and modeling principles is essential. Experience with AWS services, including AWS Glue, is highly desirable. Familiarity with big data technologies like Hadoop and PySpark, as well as streaming platforms such as Kafka, is a plus. Knowledge of database management systems (SQL, NoSQL, PostgreSQL, MongoDB) and data warehousing solutions (Snowflake, Redshift, BigQuery) is expected. Exposure to DevOps tools like GitLab, Docker, and Kubernetes is beneficial. Candidates should possess strong analytical skills and a proactive approach to problem-solving. An ability to work independently and as part of a collaborative team, with the capacity to coach junior team members, is crucial. Full-time education of 15 years is a prerequisite.