• Architect and build scalable, secure, and multi-tenant data platforms that support analytics, machine learning, and real-time business needs.
• Design and deliver resilient batch and streaming data pipelines with strong reliability, observability, and performance.
• Translate business strategy into modern data architectures, engineering standards, and platform roadmaps.
• Establish reusable data models, ETL frameworks, and engineering patterns that accelerate delivery and improve quality.
• Drive operational excellence through proactive monitoring, automation, root cause analysis, and continuous platform optimization.
• Improve data availability, quality, lineage, and governance to enable confident decision-making across business teams.
• Reduce operational effort and infrastructure costs through automation, standardization, and cloud optimization.
• Mentor engineers and influence technical direction through architecture reviews, design forums, and engineering best practices.

The Skills That Are Key to This Role

• 10+ years of experience in Data Engineering, ETL, and Data Platform Engineering with expertise in scalable data architectures, data modeling, and multi-tenant platforms.
• Strong programming skills in Python and advanced SQL, with experience across Oracle, Azure SQL MI, MySQL, and Snowflake, including performance tuning and PL/SQL development.
• Strong expertise in Oracle PL/SQL development, query optimization, performance tuning, indexing strategies, execution plan analysis, and database performance troubleshooting for high-volume enterprise applications.
• Deep expertise in ETL/ELT development using Informatica, Azure Data Factory, Azure Functions, Databricks/Spark, and Python.
• Experience designing and supporting batch, real-time, and streaming data pipelines using technologies such as Azure Event Hub, Kafka, and Kinesis.
• Strong knowledge of Azure cloud services and modern data platform technologies.
• Expertise in DataOps/DevOps practices, including CI/CD, automated testing, Infrastructure as Code, and data quality and observability frameworks.
• Excellent communication, stakeholder management, and cross-functional collaboration skills.
  • Proven ability to lead enterprise-scale data initiatives, mentor engineers, and influence architecture and technology decisions across business domains.