Principal Data Engineer

** This position follows a hybrid work model, with an expectation to be in the office 3 days per week at the St. Petersburg, FL Corporate Office location.*
* ** _

Please note:

This role is not eligible for Work Visa sponsorship, either currently or in the future._*
* ** Responsibilities*
* ** Technical Strategy & Architecture*
* + 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.

** Engineering Leadership*
* + 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.

** Solution Design & Development*
* + 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.

** Data & Database Engineering*
* + 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.

** Data Understanding*
* + 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, downstream consumption, and operational support patterns.

+ Ability to partner with business, architecture, governance, operations, and application teams to translate functional data needs into durable platform capabilities and reusable data products.

** CI/CD & Platform Engineering*
* + Architect and standardize CI/CD pipelines using Jenkins and modern Dev Ops practices.

+ Drive adoption of automation-first principles across build, test, and deployment workflows.

+ Promote Dev Sec Ops  best practices and governance controls.

** Cloud & Containerization*
* + Lead cloud modernization of enterprise master data capabilities, including transition to cloud data lakehouse architecture and medallion-based bronze, silver, and gold data layers.

+ Influence AWS-based data architecture decisions, including appropriate use of Spark, AWS EMR, cloud storage, orchestration, data quality controls, and scalable consumption patterns.

+ Drive modernization while preserving operational continuity, enterprise availability, data trust, cost discipline, security, and compliance expectations.

** Performance, Reliability & Scalability*
* + Establish frameworks for performance engineering, observability, monitoring, SLAs, SLOs, SLIs, and operational readiness for enterprise-wide master data platforms.

+ Lead root cause analysis of critical production issues and define systemic improvements across platform reliability, data quality, resiliency, recovery, and downstream dependency management.

+ Ensure the platform meets enterprise-grade resiliency, recovery, security, and availability requirements for mission-critical data distribution.

** AI-Enabled Engineering*
* + Demonstrate proficiency in using AI tools and AI-assisted engineering practices to improve individual and team efficiency, productivity, solution quality, and delivery velocity.

+ Use AI responsibly to accelerate analysis, design, coding,…