Principal Data Engineer

Overview

Principal Data Engineer within Stock Plan Services (SPS), Workplace Investing Technology, to architect, build and scale cloud-based data platforms that power analytics, reporting, operational excellence and customer experiences.

What you'll do

• Architect and build scalable, secure, 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.

What you'll need

• 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.
• 10+ years professional experience with multiple successful enterprise data platform deliveries.
• Bachelor's or Master's degree in Computer Science, Engineering, Information Systems, or equivalent experience.

Details

• Location: Bangalore - EGL.
• Shift timings: 11:00 am - 8:00 pm.