Principal Engineer, Data Engineering

Raymond James•Saint Petersburg, FL

1d•Hybrid

About The Position

We are seeking a highly experienced and visionary Principal Engineer to provide technical leadership and drive architectural excellence across our enterprise data platforms. This role requires deep expertise in Python, Oracle database development, CI/CD, Kubernetes, and large-scale data systems, along with the ability to influence cross-functional teams and shape long-term engineering strategy. As a Principal Engineer, you will act as a technical authority and thought leader, responsible for defining architecture standards, driving innovation, ensuring scalability and performance, and mentoring engineering teams. You will partner closely with leadership, product, and operations teams to deliver strategic solutions aligned with enterprise goals.

Requirements

Expert-level proficiency in Python, Oracle database development, and distributed systems design
Deep expertise in CI/CD (Jenkins), Kubernetes, and containerization
Strong experience with data engineering, large-scale data processing, and data pipelines
Advanced knowledge of database performance optimization and data modeling
Strong understanding of cloud platforms (AWS/Azure/GCP) and modern architecture patterns
Experience in enterprise architecture, system integration, and platform engineering
Strategic thinker with ability to connect technical decisions to business outcomes
Strong influence skills across teams without direct authority
Exceptional problem-solving and system-level thinking
Excellent communication skills, including ability to engage with senior leadership and stakeholders
Bachelor’s: Business Administration, Bachelor’s: Computer and Information Science (Required), Bachelor’s: Computer Engineering
General Experience - More than 15 years

Nice To Haves

Experience in Agile/Scrum at scale (SAFe or similar frameworks)
Background in enterprise data platforms, data governance, or financial systems
Relevant certifications in cloud, Kubernetes, database technologies, or DevOps tools

Responsibilities

Define and drive enterprise-level architecture for data platforms, ensuring scalability, reliability, and performance.
Establish engineering standards, design patterns, and best practices across teams.
Lead system design for complex, high-impact initiatives across multiple 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.
Define and enforce data architecture standards for Oracle and other data platforms.
Lead advanced database optimization strategies, including performance tuning, partitioning, and query optimization.
Ensure efficient data modeling, storage, and access patterns across platforms.
Architect and standardize CI/CD pipelines using Jenkins and modern DevOps practices.
Drive adoption of automation-first principles across build, test, and deployment workflows.
Promote DevSecOps best practices and governance controls.
Lead adoption and architecture for Kubernetes-based platforms and containerized applications.
Influence cloud strategy across AWS/Azure/GCP environments (where applicable).
Drive platform modernization and cost optimization initiatives.
Establish frameworks for performance engineering, monitoring, and SLO/SLI definition.
Lead root cause analysis of critical production issues and define systemic improvements.
Ensure systems meet enterprise-grade resiliency and recovery requirements.
Mentor senior engineers and leads, raising the overall technical bar of the organization.
Drive knowledge sharing, standards adoption, and engineering excellence initiatives.
Serve as a role model for engineering best practices and problem-solving.
Collaborate with product, architecture, data governance, and operations teams.
Contribute to enterprise-wide initiatives such as data governance, platform modernization, and integration strategies.
Influence prioritization and decision-making at the program and portfolio level.
Define standards for technical documentation, architecture reviews, and design governance.
Ensure compliance with enterprise policies, data governance, and security standards.