Your Role

• Design and implement scalable, reliable, and efficient data architecture to support large-scale data processing and analytics needs

• Develop, maintain, and optimize data pipelines and ensure data quality, reliability, and timeliness for ingestion and processing. Ensure consistent code quality and adherence to technical guidelines across the team

• Scope, plan, estimate and delivers projects, according to aligned roadmaps. Proactively providing projects updates, identifies impediments, project risks and options for mitigation

• Collaborate with data analysts, data engineers and other stakeholders to deliver data solutions that drive insights and support business needs

• Automate repetitive data tasks (testing, deployment, etc.), implement monitoring solutions, and support the production environment to ensure smooth data operations

• Mentor and provide guidance to junior engineers and contribute to the continuous improvement of engineering practices across the team

• Implement data governance practices, ensuring data security, privacy, and compliance with industry standards and regulations (e.g., GDPR)

Your Profile

• A degree in a MINT field or an equivalent educational background

• At least 3-5 years of experience in data engineering, including working with large-scale data processing and management systems

• Demonstrated practice in Python, SQL, Pyspark and DevOps implementation (Azure Devops, Jenkins)

• Experience in design and implementation of complex data pipelines

• Extensive experience in clean, maintainable, and efficient code development

• Strong communication skills in English and the ability to work effectively with both technical and non-technical stakeholders

Your ZEISS Recruiting Team: