Databricks Architect
Listed on 2026-08-11
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IT/Tech
Data Engineering, Data Warehousing, Cloud Computing: Infrastructure & Operations
Job Title:
Databricks Architect (Onsite)
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.
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.
- 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.
- 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 Dev Ops practices.
- Excellent communication, leadership, and stakeholder management skills.
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