Databricks Architect

Inherent Technologies; Illinois; Hybrid; USD 140,000 - 200,000; Full time

Job summary

Inherent Technologies is seeking a Databricks Architect to design, implement, and govern enterprise-scale data platforms across cloud environments. You will lead data lakehouse architectures on Databricks, defining data models, governance, and security controls while migrating legacy data warehouses to modern pipelines.

The role requires strong expertise in Spark, PySpark, SQL, and Delta Lake, with hands-on experience in Azure, AWS, or GCP Databricks and streaming platforms.

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.
• Knowledge of streaming platforms: Pub/Sub, Event Hubs, Kinesis, Kafka.
• Security, access management, and compliance requirements.

Responsibilities

• Design and implement enterprise-scale data lakehouse architectures on 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 using Spark.
• Establish CI/CD, monitoring, and operational best practices for data platforms.
• Provide technical leadership and mentor engineering teams.

Skills

Data architecture

Cloud data platforms

ETL pipelines

SQL Spark Python

Data governance security

Education

Bachelor's degree

Master's degree

Tools

Azure Databricks

AWS Databricks

GCP Databricks

Job description

Position: Databricks Architect

Location: Bolingbrook, IL *(Remote ok) *

Duration: 1 Years

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.