Databricks Data Architect

Work Arrangement: Hybrid - 3 days onsite per week

Contract: 12 months

We are seeking a Databricks Data Architect to design and lead modern cloud data solutions using Databricks and AWS . This is a hands-on architecture role focused on Lakehouse architecture, streaming, performance, governance, and cloud optimization.

Key Responsibilities

• Design enterprise Databricks Lakehouse architectures using Medallion Architecture.
• Architect batch and real-time data solutions using PySpark, Structured Streaming, Kafka, Delta Lake, and AWS .
• Design solutions for late-arriving data, event-time processing, watermarking, CDC, CDF, and streaming recovery .
• Leverage modern Databricks capabilities including Lakeflow/LDP, Serverless Compute, Unity Catalog, Liquid Clustering, Z-Ordering, and Photon .
• Evaluate emerging capabilities including Zerobus, Lakebase-to-Lakehouse synchronization, and LTAP .
• Design and optimize AWS data platforms using S3, Glue, EMR, Kinesis/MSK, Redshift, Lambda, IAM, and CloudWatch .
• Drive performance and cost optimization across Databricks and AWS workloads.
• Establish standards for data governance, security, lineage, CI/CD, and infrastructure as code.
• Lead technical design discussions and mentor Data Engineers.

Required Experience

• 8+ years of experience in Data Engineering, Data Architecture, or Cloud Data Platforms.
• Strong hands‑on experience with Databricks and AWS .
• Expert knowledge of Spark/PySpark and Structured Streaming .
• Strong experience with Kafka and/or Kinesis/MSK .
• Deep understanding of Delta Lake and Medallion Architecture .
• Experience with Unity Catalog, CDF/CDC, Liquid Clustering, and Z-Ordering .
• Strong understanding of Databricks performance and cost optimization .
• Excellent communication and stakeholder management skills.

Preferred: Databricks certification, AWS certification, and experience with newer Databricks capabilities such as Lakeflow, Zerobus, Lakebase, Serverless Compute, and LTAP .