Senior Data Engineer
Role details
Job location
Tech stack
Job description
At Roche, we thrive to deliver more benefits to our patients as part of our 10-year Pharma vision. An integral part of achieving this vision is to deliver new and innovative data analytics solutions to our scientists across Pharma Technical Operations (PT). To do so, we have formed a new organization called PT Digital and Operational Excellence (PTE) with the aspiration to digitally transform and become a lean organization.
PTE is the organization that catalyzes the global development and execution of PT's Digital and Operational Excellence strategy to enable PT to realize our performance promises. We build a strong cross-functional and inclusive community, put the power of data into the hands of our people, further develop the Lean and Digital skills across PT, and scale up our Digital and Advanced Analytics solutions, for the benefit of our colleagues and patients.
We aim to activate data citizenship and digital mind, revolutionize our FAIR data ecosystem and systems landscape, re-design excellent processes, and generate transformative insights. We collaborate closely with global functions to deliver impactful value to our patients., PTE will work in partnership across major global business functions, establishing and implementing an overall Digital / Technology strategy and driving the delivery and scale of key data & digital solutions in support of our vision.
As a Senior Data Engineer at Roche PT, you will play a pivotal role in developing and optimizing the data infrastructure that powers our pharmaceutical operations and data products. Working in multidisciplinary teams - alongside data scientists, subject matter experts, and fellow data engineers - you'll curate, transform, and construct features integral to our modeling approaches. You will also support the delivery of data products and establish standards to guide data product teams across PT, fostering consistency and quality. Additionally, you'll coach junior data engineers, helping implement best practices and data engineering standards.
This role calls for a collaborative, open-minded individual who values learning from colleagues, thoughtfully challenges ideas, and prioritizes impactful work. We seek someone who thrives in a dynamic environment, has a passion for continuous learning, and can be relied upon to work in the best interest of the team.
Main Responsibilities
- Design and build scalable data pipelines and storage solutions for real-time and batch processing aligned with SME needs.
- Lead the creation of FAIR (Findable, Accessible, Interoperable, Reusable) data products that enhance decision-making and maintain data integrity, availability, and performance across platforms.
- Collaborate with process experts to model data landscapes, obtain extracts, define secure exchange methods, and shape data products.
- Acquire, ingest, and process data from diverse sources into Big Data platforms (e.g., Snowflake).
- Develop ERDs and reusable pipelines, working with data scientists to map data to hypotheses and prepare it for advanced analytics.
- Uphold data governance standards to ensure regulatory compliance and secure sensitive data. Address data quality issues to maintain asset accuracy and reliability.
- Follow best practices in data engineering, including data contracts and validation, to ensure quality and integrity.
- Mentor junior engineers, fostering a culture of innovation and continuous improvement in engineering practices (DevOps, Data Streaming, etc.).
- Proficiency with data quality and observability tools, including Ataccama and Monte Carlo.
Additional Responsibilities
- Ensure adherence to Information Security standards across engagements.
- Collaborate with infrastructure teams to provide a technology stack tailored to project needs and aligned with our standards.
- Contribute to templates and best practices for the technology stack.
- Apply innovative techniques to deliver impact for clients and support internal R&D initiatives.
Requirements
- Education: Bachelor's or Master's degree in Computer Science, Data Engineering, or a related field.
- Experience:
- 6+ years in data engineering with experience in designing large-scale systems.
- Experience in leading junior data engineers across projects.
- Business skills:
- Client-facing project experience in collaborative teams is beneficial. Proven ability to clearly communicate complex solutions to audiences of varied technical levels. Strong organizational and interpersonal skills to deliver results, build relationships, and optimize resources.
- Preferred Qualifications:
- 3+ years of experience in the pharmaceutical or healthcare industry.
- Knowledge of regulatory requirements (e.g., GMP, FDA) and Quality systems.
- Experience with AI-driven data solutions and machine learning pipelines.
Roche embraces diversity and equal opportunity in a serious way. We are committed to building a team that represents a variety of backgrounds, perspectives, and skills. The more inclusive we are, the better our work will be.