Senior Databricks Architect

We are seeking an experienced Senior Databricks Architect to design and deliver scalable, high-performance data platforms for our Financial Services clients. The ideal candidate will have deep expertise in Databricks, cloud data architectures, and modern data engineering practices, with a strong focus on building governed, secure, and efficient data ecosystems., * Architect and implement end-to-end data solutions using Databricks Lakehouse Platform

• Design and develop scalable data pipelines using PySpark, Spark, and SQL
• Lead cloud data platform implementations on AWS/Azure/GCP
• Drive modernization of legacy data systems to cloud-native architectures
• Implement Medallion Architecture (Bronze, Silver, Gold layers)
• Ensure data governance, security, and compliance (especially for Financial Services)
• Collaborate with business stakeholders, data scientists, and engineering teams
• Optimize performance, cost, and reliability of data pipelines
• Mentor and guide data engineering teams and provide architectural leadership., As a Senior Backend Engineer specializing in Node.js and AWS, you will play a pivotal role in shaping the future of AI systems. Your expertise will contribute to the development of…

• 1 month ago, As a Senior Backend Engineer specializing in Python, you will play a critical role in shaping the future of AI systems. Your expertise will directly influence how models learn, rea…
• 1 month ago

• 12+ years of experience in Data Engineering / Data Architecture
• Strong expertise in Databricks, PySpark, and Spark ecosystem
• Hands-on experience with cloud platforms (Azure, AWS, or GCP)
• Experience with data orchestration tools (Airflow, ADF, etc.)
• Solid understanding of data modeling, ETL/ELT, and distributed systems
• Experience with Delta Lake and Unity Catalog is a plus
• Strong knowledge of Financial Services domain (Banking, Insurance, Capital Markets)
• Excellent problem-solving and stakeholder management skills., * Databricks certifications
• Experience with real-time data processing (Kafka, streaming)
• Exposure to AI/ML pipelines and MLOps
• Knowledge of regulatory and compliance frameworks in Financial Services