Experis® is a global leader in IT professional resourcing, permanent recruitment, project solutions, and managed services. With over 25 years of experience in Switzerland and offices in Zürich, Basel, and Geneva, we connect top IT talent with leading companies. Our mission is to help professionals unlock their potential and thrive in dynamic, future-ready careers.We are looking for a Data Engineer who has a Master's degree in Computer Science or Data Engineering and brings over 5 years experience in data engineering with a track record in architecting and scaling large data systems. Also we are looking for someone with proven experience in building and managing data pipelines and products.Your Tasks & Responsibilities:
Lead Data Pipelines & Storage: Design and build scalable data pipelines for real-time and batch processing. Drive architectural decisions and long-term planning for scalable, FAIR data products.
High-Quality Data Products: Create high-quality data products adhering to FAIR principles. Address complex challenges, ensure compliance, and make strategic decisions to shape data roadmaps.
Collaboration & Integration: Model data landscapes, acquire data extracts, and define secure exchange methods in collaboration with experts and cross-functional teams.
Data Ingestion & Processing: Ingest and process data from diverse sources into Big Data platforms (e.g., Snowflake). Develop ERDs and reusable pipelines for advanced analytics.
Technical Guidance & Governance: Contribute to our Data Mesh Engineering Collective to establish data governance standards, ensure regulatory compliance and data security. Mentor others and promote best practices.
Information Security & Infrastructure Collaboration: Ensure adherence to information security standards. Collaborate with infrastructure teams for tailored tech stacks. Make independent decisions on data strategies.
Innovation & Knowledge Sharing: Shape the data engineering roadmap and set standards for data quality and governance. Proactively share best practices.
Technical Proficiency: Maintain proficiency in data engineering tech stacks, data quality, and observability tools (e.g., Ataccama, Monte Carlo).
Adherence to Standards: Ensure compliance with relevant guidelines and data governance standards. Develop long-term enterprise tools.
Your Profile:
Master's degree in Computer Science, Data Engineering, or a related field.
Over 5 years in data engineering with a track record in architecting and scaling large data systems.
5+ years of experience in leading and mentoring data engineers.
Proven experience in building and managing data pipelines and products.
Skilled in handling structured, semi-structured, and unstructured data.
Proficiency in Python, Java, SQL, or Scala, and experience with big data technologies (e.g., Hadoop, Spark).
Expertise in multiple cloud platforms (AWS, Azure, GCP) and data warehousing technologies (preferably Snowflake).
Deep understanding of Information Security to ensure compliant handling and management of process data.
Familiarity with data modeling and ETL tools.
Knowledge of version control systems like Git and CI/CD pipelines.
Proficiency in implementing robust testing practices and monitoring pipelines for performance, reliability, and data quality.
Client-facing project experience.
Proven ability to communicate complex solutions to varied technical audiences.
Strong organizational and interpersonal skills for delivering results and optimizing resources.
Ability to work independently and collaboratively within a team environment.
Strong ability to influence and collaborate with stakeholders, trust building and reliable delivery of solutions
Preferred Qualifications:
3+ years of experience in the pharmaceutical or healthcare industry.
Experience with REST APIs and integrating data from various sources.
Knowledge of regulatory requirements (e.g., GMP, FDA) and Quality systems.
Experience with AI-driven data solutions and machine learning pipelines.
Experience with ML platforms (e.g., Dataiku).
Knowledge of software engineering best practices (code reviews, testing, maintainability).
