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Senior Data Engineer

About the employer
  • Roche
  • Suisse

Job description

The Position

In Roche’s Pharmaceutical Research and Early Development organisation (pRED), we make transformative medicines for patients in order to tackle some of the world’s toughest unmet healthcare needs. At pRED, we are united by our mission to transform science into medicines. Together, we create a culture defined by curiosity, responsibility and humility, where our talented people are empowered and inspired to bring forward extraordinary life-changing innovation at speed.

This position is located in Scientific Solution Engineering & Architecture, a department within the Data & Analytics function, which pushes boundaries of drug discovery and development, enabling pRED to achieve its goals.

Job mission

As a data engineer, which is an emerging role in pRED’s Data & Analytics organization, you will play a pivotal role in operationalizing the most-urgent data and analytics initiatives for pRED’s digital business initiatives. The bulk of the work is in building, managing and optimizing data pipelines and then moving these data pipelines effectively into production for key data and analytics consumers (like business/data analysts, data scientists or any persona that needs curated data for data and analytics use cases).

You also guarantee compliance with data governance and data security requirements while creating, improving and operationalizing these integrated and reusable data pipelines. You enable faster data access, integrated data reuse and vastly improved time-to-solution for pRED’s data and analytics initiatives. You will be a key interface in operationalizing data and analytics on behalf of the pRED’s business units and organizational outcomes.

Your mission also involves evangelizing effective data management practices and promoting better understanding of data and analytics. You will be working with key business stakeholders, IT experts and subject-matter experts to plan and deliver optimal analytics and data science solutions. In this role you will closely collaborate with colleagues in pRED and group informatics.

Your impact

Build data pipelines: Managed data pipelines consist of a series of stages through which data flows (for example, from data sources or endpoints of acquisition to integration to consumption for specific use cases). These data pipelines have to be created, maintained and optimized as workloads move from development to production for specific use cases. Architecting, creating and maintaining data pipelines will be the primary responsibility of the data engineer.

Drive Automation through effective metadata management:

  • You use innovative and modern tools, techniques and architectures to partially or completely automate the most-common, repeatable and tedious data preparation and integration tasks in order to minimize manual and error-prone processes and improve productivity.
  • You will also need to assist with renovating the data management infrastructure to drive automation in data integration and management.
  • You will apply your data and domain understanding to address new data requirements.
  • You will propose appropriate and innovative data ingestion, preparation, integration and operationalization techniques in optimally addressing these data requirements.
  • You will train counterparts such as data scientists, data analysts, or any data consumers in these data pipelining and preparation techniques, which makes it easier for them to integrate and consume the data they need for their own use cases.

Become a data and analytics evangelist:

  • You will be considered a blend of data and analytics “evangelist”, “data guru” and “fixer”.
  • You will promote the availability of data and analytics capabilities and expertise to leaders in pRED and educate them in leveraging these capabilities in achieving their business goals.

Your profile

  • You have a bachelor’s or master’s degree in computer science, statistics, data management, information science or a related field.
  • An advanced degree (Ph.D.) or equivalent work experience is preferred.
  • You have strong experience with advanced analytics tools for object-oriented programming using languages such Python, R, Java, C++ or similar. This includes ample experience in managing complex software projects using version control (e.g., Git) and knowledge of standard architectural and design patterns.
  • You bring a strong ability to design, build and manage data pipelines for data structures encompassing data transformation, data models, schemas, metadata and workload management.
  • Experience with workflow management tools such as Kubeflow, Vertex AI, Argo Workflows and/or data processing tools such as Spark or Hadoop would be highly valued.
  • You have strong experience in working with large, heterogeneous datasets in building and optimizing data pipelines, pipeline architectures and integrated datasets using traditional data integration technologies.
  • These should include ETL/ELT, data replication/CDC, message-oriented data movement, API design and access.
  • Working with and optimizing existing ETL processes and data integration and data preparation flows and helping to move them in production is a matter of course to you.
  • You have strong experience with popular database programming languages including SQL, PL/SQL and others for relational databases.
  • Further, you also have experience with NoSQL oriented databases such as MongoDB.
  • You have experience in working with message queuing technologies such as Kafka.
  • You have experience in working with data science teams in refining and optimizing data science and machine learning models and algorithms.
  • You have demonstrated ability to work across multiple deployment environments including cloud, on-premises and hybrid, multiple operating systems and through containerization techniques such as Docker, Kubernetes, AWS Elastic Container Service and others.
  • You are adept in agile methodologies and capable of applying DevOps and increasingly DataOps principles to data pipelines to improve the communication, integration, reuse and automation of data flows between data managers and consumers across an organization.
  • Life sciences knowledge or previous experience working in the pharmaceutical business would be a plus.
  • You have strong oral and written communication skills in English.

Our commitment

Roche commits to recognising talent and aptitude. We prioritize encouraging and supporting our employees in their personal journeys by providing a safe, creative space to help them reflect, make decisions and grow in their career. We are confident that we find the most innovative solutions by gaining different perspectives, asking and answering hard questions, and challenging the status quo.

Roche embraces diversity and equal opportunity

in a serious yet enthusiastic way; we are devoted to building a team that represents a range of backgrounds, perspectives, and skills. The more inclusive we are, the better our work will be.

Who we are

At Roche, more than 100,000 people across 100 countries are pushing back the frontiers of healthcare. Working together, we’ve become one of the world’s leading research-focused healthcare groups. Our success is built on innovation, curiosity and diversity.

Basel is the headquarters of the Roche Group and one of its most important centres of pharmaceutical research. Over 10,700 employees from over 100 countries come together at our Basel/Kaiseraugst site, which is one of Roche`s largest sites.

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Besides extensive development and training opportunities, we offer flexible working options, 18 weeks of maternity leave and 10 weeks of gender independent partnership leave. Our employees also benefit from multiple services on site such as child-care facilities, medical services, restaurants and cafeterias, as well as various employee events.

We believe in the power of diversity and inclusion, and strive to identify and create opportunities that enable all people to bring their unique selves to Roche.

Roche is an Equal Opportunity Employer.