Job Overview

We are looking for a highly senior, deeply hands on Databricks Lead to lead a large‑scale Oracle‑to‑Databricks migration, covering schema migration, code conversion, and ODI job modernization. The ideal candidate has extensive experience building enterprise-grade data platforms on Databricks, has executed at least one greenfield Databricks implementation, and is exceptionally strong in PySpark, Spark SQL, framework development, and Databricks Workflows.

Key Responsibilities

• Architect, design, and implement cloud-native data platforms using Databricks (ingestion → transformation → consumption).
• Lead the full Oracle → Databricks migration including schema translation, ETL/ELT logic modernization, and ODI job replacement.
• Develop reusable PySpark frameworks, data processing patterns, and orchestration using Databricks Workflows.
• Build scalable, secure, and cost‑optimized Databricks infrastructure and data pipelines.
• Collaborate with business and technical stakeholders to drive data modernization strategy.
• Establish development best practices, coding standards, CI/CD, and DevOps/DataOps patterns.
• Provide technical mentorship and create training plans for engineering teams.
• Contribute to building MLOps and advanced operations frameworks.

Required Qualifications

• 14+ years in Data Engineering/Architecture with at least 4+ years hands-on Databricks experience delivering end‑to‑end cloud data solutions.
• Strong experience migrating from Oracle/on‑prem systems to Databricks, including SQL, PL/SQL, ETL logic, and ODI pipelines.
• Deep hands-on expertise in: 
  • PySpark, Spark SQL, Delta Lake, Unity Catalog
  • Building reusable data frameworks
  • Designing high‑performance batch and streaming pipelines
• Proven experience with greenfield Databricks implementations.
• Strong understanding of cloud-native architectures on AWS and modern data platform concepts.
• Solid knowledge of data warehousing, columnar databases, and performance optimization.
• Good understanding of Agile/Scrum development processes.
• Bonus: Experience designing Data Products, Data Mesh architectures, Data Vault or enterprise data governance models.
• Good Understanding of Golde Gate.