Sr Principal Data Architect, Executive Director

Elevate your career by working with new AI and machine learning technologies, focusing on delivering impactful solutions. We provide opportunities to help you reach your full potential, offering the support you need to achieve your career goals. The Employee Platforms technology team is excited to invest in Dublin, establishing an engineering hub focused on the growth and application of innovative technologies to enhance the experience of our 300k+ employees.

Join a dynamic team at JPMorgan Chase that values diversity and creativity. As a Senior Principal Data Architect within Employee Platforms, you'll have the opportunity to sharpen your skills and ambition while pushing the industry forward. You'll be a senior member of a team, developing high-quality data architecture solutions and collaborating with architects to carry out critical technology solutions across multiple technical areas. Be part of a firm that supports your growth and innovation.

As a Senior Principal Data Architect within JPMorgan Chase's Employee Platforms, you serve as a seasoned member of a team to develop high-quality data architecture solutions for various software applications and platforms. You will design and implement data models that support our organization's data strategy, working closely with Data Product Managers, Engineering teams, and Data Governance teams to ensure the delivery of high-quality data products that meet business needs and adhere to best practices.

J.P. Morgan Dublin thrives as a collaborative, tight-knit community, passionately driven by innovation, where curiosity fuels the relentless pursuit of groundbreaking ideas. The culture is centred around exploring new frontiers together by fostering an environment that encourages growth, creativity and forward-thinking.

Job Responsibilities:

• Execute data architecture solutions and technical troubleshooting, thinking beyond routine approaches to build solutions and break down problems.
• Collaborate with Data Product Managers to understand business requirements and translate them into data modelling specifications.
• Create and maintain data dictionaries, entity-relationship diagrams, and other documentation to support data models.
• Create secure and high-quality production code and maintain algorithms that run synchronously with appropriate systems.
• Produce data architecture and design artifacts for complex applications, ensuring design constraints are met by software code development.
• Evaluate data architecture designs and provide feedback on recommendations.
• Represent the team in architectural governance bodies.
• Lead the data architecture team in evaluating new technologies to modernize the architecture using existing data standards and frameworks.
• Gather, analyse, synthesize, and develop visualizations and reporting from large, diverse data sets to improve data frameworks, applications, and systems.
• Idenfity hidden problems and patterns in data proactively and use these insights to drive improvements to coding hygiene and system architecture.
• Contribute to data architecture communities of practice and events that explore new and emerging technologies.

Required Qualifications, Capabilities, and Skills:

• Formal training or certificate in Data Science, Data Architecture, and proficient advanced experience.
• Hands-on experience in data platforms (Databricks), cloud services (e.g., AWS, Azure, or Google Cloud), and big data technologies.
• Strong understanding of database management systems, data warehousing, and ETL processes.
• Excellent communication and collaboration skills, with the ability to work effectively with cross-functional teams.
• Knowledge of data governance principles and best practices.
• Ability to evaluate current technologies to recommend ways to optimize data architecture.
• Hands-on practical experience in system design, application development, testing, and operational stability.
• Experience in developing, debugging, and maintaining code in a large corporate environment with modern programming and database querying languages.
• Overall knowledge of the Software Development Life Cycle.
• Solid understanding of agile methodologies such as continuous integration and delivery, application resiliency, and security.
• Demonstrated knowledge of software applications and technical processes within a technical discipline (e.g., cloud, artificial intelligence, machine learning, mobile, etc.).

Preferred Qualifications, Capabilities, and Skills:

• Familiarity with big data technologies (e.g., Hadoop, Spark).
• Certification in data modelling
• Graph DB experience