Databricks Architect

Shrive Technologies; Town of Texas (WI); On-site; USD 150,000 - 200,000; Full time

Job summary

Shrive Technologies seeks a Databricks Architect to design, implement, and govern enterprise-scale data platforms across cloud environments such as Azure, AWS, or GCP. You will lead data architecture efforts, drive data governance, and optimize platform operations.

The role focuses on data engineering best practices, streaming, and security, enabling analytics across business units while mentoring engineering teams.

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.

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 architecture

Databricks

Spark

PySpark

SQL

Delta Lake

Azure Databricks

AWS Databricks

GCP Databricks

Streaming

Security & compliance

Education

Bachelor's degree in CS/related

Master's degree preferred

Tools

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.