Databricks Architect

Shrive Technologies LLC; Town of Texas (WI); On-site; USD 140,000 - 210,000; Full time

Job summary

Shrive Technologies LLC is seeking a seasoned Databricks Architect to design, implement, and govern enterprise-scale data platforms across major cloud environments. The role emphasizes data architecture, governance, and platform optimization to enable analytics and streamlined data operations.

You will lead migration efforts, define data models, and establish best practices for security, CI/CD, and monitoring.

Qualifications

• 8+ years of data engineering and 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 expertise in streaming platforms: GCP Pub/Sub, Azure Event Hubs, AWS Kinesis, Apache Kafka
• Hands-on experience with producer/consumer architecture decisions and trade-offs.
• Knowledge of data lakehouse architecture and data governance.
• Experience with data integration tools and orchestration frameworks.
• Strong understanding of security, access management, and compliance requirements.

Responsibilities

• Design and implement scalable data lakehouse architectures using Databricks.
• Define enterprise data models, governance standards, and security controls.
• Lead migration of legacy data warehouses and ETL workloads to Databricks.
• Architect batch and real-time data processing solutions using Spark.
• Optimize performance, scalability, reliability, and cost efficiency.
• Collaborate with business stakeholders, data engineers, data scientists, and cloud architects.
• Establish CI/CD, monitoring, and operational best practices for data platforms.
• Provide technical leadership and mentor engineering teams.

Skills

Data engineering

Databricks architecture

Apache Spark

PySpark

SQL

Delta Lake

Data governance

Cloud platforms

Security & compliance

CI/CD for data

Leadership

Education

Bachelor's degree in CS/Engineering/IS

Master's degree preferred

Tools

Azure Databricks

AWS Databricks

GCP Databricks

Unity Catalog

Delta Live Tables

Databricks Workflows

Power BI

Tableau

Job description

Role Summary

The Databricks Architect is responsible for designing, implementing, and governing enterprise-scale data platforms on Databricks. The role focuses on data architecture, cloud integration, data engineering best practices, analytics enablement, and platform optimization across Azure, AWS, or GCP environments.

Responsibilities

• Design and implement scalable data lakehouse architectures using Databricks.
• Define enterprise data models, governance standards, and security controls.
• Lead migration of legacy data warehouses and ETL workloads to Databricks.
• Architect batch and real-time data processing solutions using Spark.
• Optimize performance, scalability, reliability, and cost efficiency.
• Collaborate with business stakeholders, data engineers, data scientists, and cloud architects.
• Establish CI/CD, monitoring, and operational best practices for data platforms.
• Provide technical leadership and mentor engineering teams.

Required Skills

• 8+ years of data engineering and 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 expertise in streaming platforms: GCP Pub/Sub, Azure Event Hubs, AWS Kinesis, Apache Kafka
• Hands-on experience with producer/consumer architecture decisions and trade-offs.
• Knowledge of data lakehouse architecture and data governance.
• Experience with data integration tools and orchestration frameworks.
• Strong understanding of security, access management, and compliance requirements.

Preferred Skills

• Databricks Certified Data Engineer Professional or equivalent.
• Experience with Unity Catalog, Delta Live Tables, and Databricks Workflows.
• Experience with Power BI, Tableau, or other BI platforms.
• Knowledge of DataOps, DevOps, and MLOps practices.
• Education Bachelor's degree in Computer Science, Engineering, Information Systems, or related field.
• Master's degree preferred.