Sr. Data Engineer Digital Surgery Platform

Sr. Data Engineer Digital Surgery Platform (DSP)

At Johnson & Johnson, we believe health is everything. Our strength in healthcare innovation empowers us to build a world where sophisticated diseases are prevented, treated, and cured, where treatments are smarter and less invasive, and solutions are personal. Through our expertise in Innovative Medicine and MedTech, we are uniquely positioned to innovate across the full spectrum of healthcare solutions today to deliver the breakthroughs of tomorrow, and profoundly impact health for humanity. Learn more at https://www.jnj.com/.

Responsibilities

• Work with platform data engineering, core platform, security, and technical quality to design, implement and deploy data engineering solutions.
• Develop pipelines for ingestion, transformation, orchestration, and consumption of various types of data.
• Design and deploy data layering pipelines that use modern Spark based data processing technologies such as Databricks and Delta Live Table (DLT).
• Integrate data engineering solutions with Azure data governance components not limited to Purview and Databricks Unity Catalog.
• Implement and support security monitoring solutions within Azure Databricks ecosystem.
• Design, implement, and support data monitoring solutions in data analytical workspaces.
• Configure and deploy Databricks Analytical workspaces in Azure with IaC (Terraform, Databricks API) with J&J DevOps automation tools within JPM/Xena framework.
• Implement automated CICD processes for data processing pipelines.
• Support DataOps for the distributed DSP data architecture.
• Function as a data engineering SME within the data platform.
• Manage authoring and execution of automated test scripts.
• Build effective partnerships with DSP architecture, core infrastructure and other domains to design and deploy data engineering solutions.
• Work closely with the DSP Product Managers to understand business needs, translate them to system requirements, demonstrate in-depth understanding of use cases for building prototypes and solutions for data processing pipelines.
• Operate in SAFe Agile DevOps principles and methodology in building quality DSP technical solutions. Author and implement automated test scripts as mandates DSP quality requirements.

Qualifications

Required

• Bachelors degree or equivalent experience in software or computer science or data engineering.
• 8+ years of overall IT experience.
• 5-7 years of experience in cloud computing and data systems.
• Advanced Python programming skills.
• Expert level in Azure Databricks Spark technology and data engineering (Python) including Delta Live Tables (DLT).
• Experience in design and implementation of secure Azure data solutions.
• In-depth knowledge of the data architecture infrastructure, network components, data processing
• Proficiency in building data pipelines in Azure Databricks.
• Proficiency in configuration and administration of Azure Databricks workspaces and Databricks Unity Catalog.
• Deep understanding of principles of modern data Lakehouse.
• Deep understanding of Azure system capabilities, data services, and ability to implement security controls.
• Proficiency with enterprise DevOps tools including Bitbucket, Jenkins, Artifactory.
• Experience with DataOps.
• Experience with quality software systems.
• Deep understanding of and experience in SAFe Agile.
• Understanding of SDLC.