Databricks Architect
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Job Location:
Los Angeles, CA - USA
Monthly Salary:
Not Disclosed
Posted on:
4 hours ago
Vacancies:
1 Vacancy
Job Summary
Job Title: Databricks Architect
Location : Los Angeles CA (Hybrid)
The Databricks Architect is responsible for designing implementing and optimizing scalable data analytics and data engineering solutions on the Databricks Lakehouse Platform. This role requires deep expertise in cloud platforms (Azure/AWS/GCP) distributed data processing Delta Lake architectures and modern data engineering practices. The architect will collaborate with cross-functional teams to define data strategies ensure platform reliability and enable advanced analytics ML and BI use cases.
Key Responsibilities
- Architecture & Design
- Design end-to-end Databricks Lakehouse architectures for data ingestion processing storage and consumption.
- Define and implement Delta Lake patterns including medallion architecture (Bronze/Silver/Gold).
- Develop scalable data pipelines using PySpark Spark SQL and Databricks workflows.
- Architect solutions for structured semi-structured and unstructured data.
- Engineering & Implementation
- Build robust ETL/ELT pipelines with Databricks notebooks jobs and workflows.
- Design and implement high-performance streaming solutions using Structured Streaming.
- Optimize Spark jobs for cost performance and scalability.
- Implement CI/CD and automation using Databricks Repos Git and DevOps pipelines.
- Cloud & Platform Expertise
- Architect solutions across Azure/AWS/GCP leveraging native cloud services (e.g. Azure Data Factory AWS Glue GCP Dataflow).
- Ensure security governance and compliance through Unity Catalog RBAC and encryption.
- Monitor workloads and optimize cluster configurations for performance and cost.
- Collaboration & Leadership
- Work closely with data engineers data scientists BI teams and business stakeholders.
- Act as a subject matter expert (SME) for Databricks best practices standards and patterns.
- Conduct architectural reviews and guide teams on design decisions.
- Lead PoCs evaluate new features and drive platform adoption.
- Quality Governance & Observability
- Define standards for data quality lineage observability and governance.
- Implement automated testing frameworks for pipelines and notebooks.
- Establish performance baselines and monitoring dashboards.
Required Skills & Experience
Technical Skills
- 7 years of experience in data engineering/architecture.
- 3 years of hands-on experience with Databricks.
- Strong expertise in Spark PySpark SQL and distributed data processing.
- Deep understanding of Delta Lake features: ACID transactions OPTIMIZE ZORDER Auto Loader.
- Experience with workflow orchestration jobs and Databricks REST APIs.
- Hands-on expertise with at least one cloud platform:
- Azure (preferred): ADF ADLS Key Vault Event Hub Azure DevOps
- AWS: S3 Glue Lambda Kinesis
- GCP: GCS Dataflow Pub/Sub
- Familiarity with CI/CD Git DevOps and Infrastructure-as-Code (Terraform preferred).
- Soft Skills
- Strong analytical and problem-solving skills.
- Excellent communication and stakeholder management.
- Ability to lead design discussions and guide technical teams.
- Strong documentation and architectural blueprinting skills.
Preferred Qualifications
- Databricks certifications such as:
- Databricks Certified Data Engineer Professional
- Databricks Certified Machine Learning Professional
- Databricks Lakehouse Fundamentals
- Experience with MLflow Feature Store or MLOps workflows.
- Experience working in regulated industries (BFSI healthcare etc.).
Key Skills
- APIs
- Pegasystems
- Spring
- SOAP
- .NET
- Hybris
- Solution Architecture
- Service-Oriented Architecture
- Adobe Experience Manager
- J2EE
- Java
- Oracle
