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SIMARN Solutions

Databricks Architect

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Job Description

Databricks Architect at SIMARN Solutions Databricks Architect at SIMARN Solutions in Lemont, Illinois Posted in about 12 hours ago.

Type:

full-time

Job Title :
Databricks Architect Location:

Bolingbrook, IL Remote candidates considered 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. What You'll Do 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. Must-Have Skills 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. Nice to Have Experience with Unity Catalog, Delta Live Tables, and Databricks Workflows . Databricks certification. Experience with Power BI or Tableau . Knowledge of DataOps, DevOps, and MLOps . Bachelor's degree in computer science, Engineering, Information Systems, or a related field preferred.