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Raymond James Financial

Wealth management, banking, and investment services

Principal Data Engineer

Data EngineeringConfirmed live in the last 24 hours
Full-timeSt. Petersburg, FL, USANo salary listed

About the Job

Requirements

  • At least 15 years of progressive engineering experience, including technical leadership for enterprise-scale data, database, or platform engineering capabilities.
  • Strong hands-on data engineering experience with Python, Oracle/ODI, Spark, AWS EMR, Redshift, Iceberg, and large-scale data processing patterns.
  • Experience developing, supporting, maintaining, and modernizing mission-critical database, master data, or enterprise-scale data platforms in production environments.
  • Strong functional and data understanding of Security/Product Master Data Platforms, with working knowledge of enterprise data domains such as Clients, Accounts, Assets and Liabilities, Trades, and Activities.
  • Experience with cloud data lakehouse architecture, medallion patterns, data quality controls, lineage, governed consumption, and reusable data product patterns.
  • Proficiency using AI tools and AI-assisted engineering practices to improve productivity, solution quality, documentation, troubleshooting, and delivery velocity.
  • Strong communication, technical influence, and cross-functional leadership skills to engage engineering, architecture, governance, operations, product, and business stakeholders.
  • Experience in Agile/Scrum at scale, such as SAFe or similar frameworks.
  • Experience in financial services, wealth management, capital markets, Security/Product Master Data, or enterprise reference data platforms.
  • Experience leading modernization of enterprise master data or reference data platforms from legacy technologies toward cloud data lakehouse, medallion architecture, or governed data product models.
  • Experience with enterprise data governance, data quality, lineage, stewardship, metadata management, and enterprise consumption patterns at scale.
  • Experience applying AI-enabled engineering practices to improve development efficiency, operational productivity, solution quality, and delivery velocity.
  • Required bachelor's degree in Business Administration, Computer and Information Science, or Computer Engineering.
  • Expert-level proficiency in data engineering and large-scale data processing using Python, Oracle/ODI, Spark, AWS EMR, Redshift, Iceberg, distributed systems design, and modern platform engineering patterns.
  • Deep expertise in CI/CD using Jenkins, Kubernetes, and containerization.
  • Strong experience designing, building, and operating data pipelines, APIs, batch and near-real-time data processing capabilities, data quality controls, lineage, and enterprise consumption patterns.
  • Experience modernizing legacy or operational platforms into cloud data lakehouse architecture using medallion patterns, including bronze, silver, and gold layers, curated data products, and governed consumption.
  • Experience developing, supporting, maintaining, and modernizing mission-critical database and master data platforms in production environments.
  • Strong functional understanding of enterprise master data domains, especially Security/Product Master, with exposure to Clients, Accounts, Assets and Liabilities, Trades, and Activities.
  • Advanced knowledge of database performance optimization, data modeling, platform reliability, and production support for mission-critical data platforms.
  • Strong understanding of cloud platforms, including AWS, Azure, and GCP, and modern architecture patterns.
  • Experience in enterprise architecture, system integration, and platform engineering.
  • Strategic thinking to connect technical decisions to business outcomes.
  • Strong influence across teams without direct authority.
  • Problem-solving and system-level thinking.
  • Ability to engage senior leadership and stakeholders through clear communication.

Responsibilities

  • Provide technical leadership for mission-critical Security/Product Master Data Platforms and other enterprise-scale data platforms supporting the enterprise.
  • Establish engineering standards, data architecture patterns, and integration patterns.
  • Define and drive target-state architecture 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 and advise 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 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 provide high availability, fault tolerance, and observability.
  • Own end-to-end engineering for mission-critical database and master data platforms, including development, support, maintenance, lifecycle management, performance, reliability, and operational excellence.
  • Apply 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.
  • Use 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.
  • Partner with business, architecture, governance, operations, and application teams to translate functional data needs into durable platform capabilities and reusable data products.
  • Architect and standardize CI/CD pipelines using Jenkins and modern DevOps practices.
  • Drive automation-first practices across build, test, and deployment workflows.
  • Promote DevSecOps practices and governance controls.
  • 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 use of Spark, AWS EMR, cloud storage, orchestration, data quality controls, and scalable consumption patterns.
  • Maintain operational continuity, enterprise availability, data trust, cost discipline, security, and compliance during modernization.
  • Establish performance engineering, observability, monitoring, SLAs, SLOs, SLIs, and operational-readiness frameworks for enterprise-wide master data platforms.
  • Lead root cause analysis of critical production issues and define systemic improvements in platform reliability, data quality, resiliency, recovery, and downstream dependency management.
  • Ensure platforms meet enterprise-grade resiliency, recovery, security, and availability requirements for mission-critical data distribution.
  • Use AI tools and AI-assisted engineering practices to improve efficiency, productivity, solution quality, and delivery velocity.
  • Use AI responsibly to accelerate analysis, design, coding, testing, documentation, troubleshooting, and operational support while maintaining sound engineering judgment, security, and governance.
  • Identify opportunities to apply AI to improve technical solutions, reduce manual effort, improve platform reliability, and accelerate modernization initiatives.
  • Mentor senior engineers and leads, raise the organization's technical bar, drive knowledge sharing and standards adoption, and support engineering excellence initiatives.
  • Model engineering best practices and problem-solving.
  • Travel less than 25%.

About the Company

Raymond James Financial

Wealth management, banking, and investment services

Raymond James Financial provides a range of financial services to individuals, corporations, and municipalities, organized into five segments: Private Client Group, Capital Markets, Asset Management, RJ Bank, and Other. Its offerings include financial planning and advisory services, investment banking and research, asset management products, and banking and lending through RJ Bank, earning revenue from advisory fees, commissions, and net interest income. The firm differentiates itself with a strong focus on personalized, client-centric service where financial advisors tailor strategies to each client and foster long-term relationships. Its goal is to help clients achieve their financial objectives by delivering comprehensive solutions across wealth management, banking, and capital markets through a multi-segment business model.

Company size
Not listed
Company stage
IPO
Headquarters
Saint Petersburg, Florida
Founded
1962

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