Databricks Architect

About the role

We are looking for an experienced Databricks Architect to design and lead enterprise-scale data platforms and lakehouse solutions. This role will focus on Databricks architecture, cloud data engineering, streaming, governance, migration, and platform optimization across Azure, AWS, or GCP.

Responsibilities

• Design scalable Databricks Lakehouse architectures and enterprise data solutions.
• Lead migrations of legacy data warehouses and ETL workloads to Databricks.
• Architect batch and real-time/streaming pipelines using Spark.
• Define data governance, security, access controls, and enterprise data standards.
• Drive platform performance, scalability, reliability, and cost optimization.
• Establish CI/CD, monitoring, DataOps, and operational best practices.
• Partner with data engineers, data scientists, cloud architects, and business stakeholders.
• Provide architectural guidance and technical leadership to engineering teams.

Requirements

• 8+ years of data engineering/data platform experience.
• 3+ years of hands-on Databricks architecture experience.
• Strong expertise in Apache Spark, PySpark, SQL, and Delta Lake.
• Experience with Azure Databricks, AWS Databricks, or GCP Databricks.
• Strong streaming experience with Kafka, Azure Event Hubs, AWS Kinesis, or GCP Pub/Sub.
• Hands-on understanding of producer/consumer architectures and design trade-offs.
• Experience with lakehouse architecture, data governance, orchestration, security, and access management.

Qualifications

Bachelors degree in computer science, Engineering, Information Systems, or a related field preferred.

Skills

• Experience with Unity Catalog, Delta Live Tables, and Databricks Workflows.
• Databricks certification.
• Experience with Power BI or Tableau.
• Knowledge of DataOps, DevOps, and MLOps.