Databricks Architect
SIMARN Solutions
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.
- ~ Databricks Lakehouse architecture (medallion); Delta Lake; Unity Catalog governance design; Spark/PySpark at scale; batch and streaming ingestion (Auto Loader, Lakeflow); migration from legacy warehouses to Databricks; Azure/AWS data servicesDatabricks
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