The Position
Diabetes is a pesky monster and that's putting it mildly. If you're serious about helping us face it head-on, come join us! Being a global leader in integrated Personalized Diabetes Management (iPDM), Roche Diabetes Care collaborates with pioneers around the globe, including people with diabetes, caregivers, healthcare professionals, and payers. We aim to transform and advance care provision and foster sustainable care structures. Under the brands RocheDiabetes, Accu-Chek, and mySugr, comprising glucose monitoring, insulin delivery systems, and digital solutions, we unite with our partners to create patient-centered value.
By building and collaborating in an open ecosystem, connecting devices and digital solutions as well as contextualizing relevant data points, we aim to support the optimization of therapy and enable better-informed therapy decisions. Your upcoming mission:
Lead the design and implementation of the data & analytics architecture ensuring compliance, quality, and sustainable growth of the platform.Build scalable data pipelines to integrate and model datasets from different sources that meet functional and non-functional requirements.Provide the technology, tools, and data to support data scientists and analysts in R&D, One Medical, and Commercial teams.Manage the technical backlog on the Data & Analytics Platform.Ensure data quality by implementing and monitoring a data quality framework together with the data source teams.Work with data infrastructure to triage infrastructure issues and drive to resolution.Collaborate with cross-functional stakeholders to understand their business needs.Formulate and complete end-to-end analysis that includes data gathering, analysis, ongoing scaled deliverables, and presentations.Foster a data-driven culture throughout the team and lead data science projects that will have an impact throughout the organization.Help to grow our data team with exceptional engineers.Essential skills for this mission: BS degree in Computer Science or related field.8+ years relevant experience as a Data Engineer, building Data Platforms, Datalakes, and Business Intelligence solutions.Proficient in implementing data pipelines (using Pyspark, Spark SQL, Scala), orchestration tools/services (Airflow, data factory), and testing frameworks.Proficient with Software Engineering best practices, such as unit testing and integration testing, and software development tools, such as Intellij, Maven, Git, Docker among others.Experience in one of the main cloud services (AWS, Google Cloud, or Azure) with Big Data services (EMR, Databricks, Synapse, HDInsight, Kinesis, etc.).Experience in databases (columnar, NoSQL, and relational databases: Redshift, DynamoDB, Aurora, Postgres, and/or Snowflake), data modeling, and data management tools (Hive, Jupiter, Zeppelin, and/or Databricks).
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