Databricks Architect

We are seeking an experienced Databricks Architect to design, architect, and implement scalable data platforms using the Databricks Lakehouse architecture. The ideal candidate will have extensive experience in modern data engineering, cloud platforms, and enterprise data architecture within the Life Sciences industry . This role requires close collaboration with business and technical stakeholders to deliver secure, scalable, and compliant data solutions. Key Responsibilities Design and implement enterprise-scale data platforms using Databricks. Architect end-to-end data solutions, including data ingestion, transformation, storage, and analytics. Develop scalable ETL/ELT pipelines using Apache Spark and Databricks. Design and optimize Delta Lake architectures for performance and reliability. Collaborate with business stakeholders to understand data requirements and translate them into technical solutions. Define data governance, security, and best practices for the Databricks environment. Optimize workloads for cost, scalability, and performance. Lead architecture reviews, technical design sessions, and code reviews. Mentor data engineers and establish development standards. Integrate Databricks with enterprise data sources, APIs, and reporting platforms. Support production deployments, troubleshooting, and performance tuning. Ensure data solutions align with Life Sciences regulatory and compliance requirements, where applicable. Required Qualifications Bachelor’s or Master’s degree in Computer Science, Information Systems, Engineering, or a related field. 10+ years of experience in data engineering and data architecture. 3–5+ years of hands‑on experience with Databricks. Experience working in the Life Sciences industry (pharmaceutical, biotechnology, medical devices, or healthcare). Strong expertise in Apache Spark (PySpark/Scala/Spark SQL). Strong SQL and Python programming skills. Experience with Delta Lake, Unity Catalog, and Databricks Workflows. Experience with Azure, AWS, or Google Cloud. Strong understanding of data lakehouse architecture, data warehousing, and data modeling. Experience implementing

CI/CD

pipelines and DevOps practices. Excellent communication, leadership, and stakeholder management skills. Preferred Qualifications Databricks Certified Professional Data Engineer or Databricks Certified Solutions Architect. Experience with Azure Data Factory, AWS Glue, or similar orchestration tools. Knowledge of streaming technologies such as Kafka or Spark Structured Streaming. Experience with Power BI, Tableau, or other BI platforms. Familiarity with Life Sciences data standards and regulatory environments (e.g., GxP, FDA 21 CFR Part 11, HIPAA, where applicable). Experience supporting AI/ML or advanced analytics workloads on Databricks. Technical Skills Databricks PySpark Python SQL Unity Catalog Databricks Workflows Git CI/CD Data Lakehouse Architecture Data Modeling Performance Tuning Soft Skills Strong leadership and architectural decision-making abilities. Excellent communication and presentation skills. Ability to engage effectively with business, IT, and executive stakeholders. Strong analytical and problem-solving skills. Ability to mentor and guide technical teams. Work Model Full‑time Onsite Experience working directly with business stakeholders in a Life Sciences environment is highly preferred. #J-18808-Ljbffr Quantum Integrators