Principal Data Engineer

Job Description Summary

We are seeking a highly experienced Principal Data Engineer to provide technical leadership for mission‑critical Security/Product Master Data Platforms and other enterprise‑scale data platforms that support the entire enterprise. This role requires deep data engineering expertise, strong database and platform engineering skills, hands‑on experience with Oracle, Redshift, Python, Spark, Glue, AWS EMR, and Iceberg, and proficiency using AI to improve engineering productivity, solution quality, and delivery velocity.

The candidate will be expected to lead modernization of enterprise data capabilities toward cloud data lakehouse and medallion architecture while maintaining operational stability, resiliency, performance, security, and enterprise availability. As a Principal Engineer, you will act as the technical authority for enterprise‑wide platforms that manage and distribute critical security, product, and other high‑value enterprise data used across business, operations, analytics, regulatory, and downstream application capabilities.

The ideal candidate combines strong functional understanding of master data and enterprise data domains with hands‑on engineering depth, AI‑enabled engineering practices, and experience transitioning legacy or operational data platforms toward a modern cloud data lakehouse architecture using medallion patterns.

Master Data Platforms and other enterprise‑scale data platforms, ensuring scalability, reliability, availability, performance, and enterprise‑wide reuse. Establish engineering standards, data architecture patterns, integration patterns. Define and drive the target‑state architecture for enterprise Security/Product, and design principles for mission‑critical master data and enterprise‑scale data platforms. Lead system design and modernization roadmaps for high‑impact initiatives across security, product, master data, and other enterprise‑scale data domains.

Provide technical leadership across multiple teams, not limited to a single project or squad. Act as a trusted advisor to leadership on technology strategy, trade‑offs, and long‑term platform evolution. Drive alignment across engineering, data, and platform teams to ensure consistency and reusability.

Lead the design and development of enterprise‑grade Python applications and distributed systems. Oversee architecture and implementation of data pipelines, APIs, and large‑scale data processing frameworks. Ensure solutions are designed with high availability, fault tolerance, and observability.

Lead end‑to‑end engineering ownership for mission‑critical database and master data platforms, including development, support, maintenance, lifecycle management, performance, reliability, and operational excellence. Apply advanced database optimization strategies across Oracle and related platforms, including performance tuning, partitioning, query optimization, resiliency, recoverability, and scalability. Ensure efficient data modeling, storage, and access patterns across platforms. Apply hands‑on expertise in Oracle/ODI, Python, Spark, AWS EMR, Redshift, S3, and Iceberg to design, build, and modernize enterprise data platforms.

Lead transition of legacy and operational master data capabilities toward modern cloud data lakehouse architecture using S3, Iceberg, Redshift, and medallion patterns for ingestion, transformation, curation, quality, and governed consumption.

Strong functional and data understanding of Security/Product Master Data Platforms is required, including how enterprise master data is modeled, governed, integrated, consumed, and supported. Must have experience across core enterprise data domains, including Clients, Accounts, Assets and Liabilities, Trades and Activities, Security/Product Master, with particular depth in Security/Product Master Data. Must have hands‑on experience working with master data platforms supporting these domains, including business meaning, reference data, data lineage, data quality, integration, stewardship,…