Principal Data Engineer

• Designs and develops complex data integration solutions.
• Implements innovative solutions for financial advisors using the latest technology in a collaborative and engaging environment.
• Independently designs, develops, and implements data integration solutions using best practices across both cloud-based and traditional infrastructure technologies.
• Delivers data centric data integration solutions with transformation logic to be consumed by customers.
• Performs software configuration management, test automation, version control, and static code analysis.
• Integrates data with end-to-end development activities.
• Creates, updates, and maintains technical documentation for software-based projects and products.
• Solves production issues.
• Interacts with business partners to understand business requirements and assist in generation of technical requirements.
• Participates in architecture, technical design, and product implementation discussions.
• Develops and implements advanced data engineering frameworks.
• Advises senior leadership on data infrastructure and technology solutions.
• Mentors junior engineers.
• Performs independent and complex technical and functional analysis for multiple divisional initiatives.

Bachelor’s degree in Computer Science, Engineering, Information Technology, Information Systems, or a closely related field (or foreign education equivalent) and five (5) years of experience as a Principal Data Engineer (or closely related occupation) designing, building and supporting scalable data pipelines for large scale ETL, real-time, batch systems and reporting platforms in a financial services environment.

Or, alternatively, Master’s degree in Computer Science, Engineering, Information Technology, Information Systems, or a closely related field (or foreign education equivalent) and three (3) years of experience as a Principal Data Engineer (or closely related occupation) designing, building and supporting scalable data pipelines for large scale ETL, real-time, batch systems and reporting platforms in a financial services environment.

• Demonstrated Expertise designing and developing data pipelines for data warehouses (ETL), using Python within Agile frameworks (Scrum), in a financial services domain; integrating the data pipelines with PL/SQL; creating batch jobs using schedulers; and identifying bottlenecks in ETL packages.
• Demonstrated Expertise building and maintaining ETL pipelines using Python; developing SQL scripts or stored procedures to process large datasets in relational environments; and improving data workflows and data availability for business operations using PL/SQL with databases (Oracle, Postgres or Snowflake).
• Demonstrated Expertise applying DevOps principles throughout the software development life cycle (SDLC); and building and promoting CI/CD pipelines using Jenkins, and Bitbucket or GitHub to automate deployments.
• Demonstrated Expertise improving system reliability and supporting continuous delivery of data engineering solutions, using Cloud platforms -- AWS or GCP; delivering real time reports with actionable insights to stakeholders.

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Fidelity’s Onsite Working Model

Fidelity is transitioning to a full-time onsite working model through a phased rollout across regions and roles. Currently, some roles and locations require 100% onsite presence, while others require less. Onsite expectations are likely to evolve as the rollout continues. This transition does not apply to fully remote roles.

Information Technology Please be advised that Fidelity’s business is governed by the provisions of the Securities Exchange Act of 1934, the Investment Advisers Act of 1940, the Investment Company Act of 1940, ERISA, numerous state laws governing securities, investment and retirement-related financial activities and the rules and regulations of numerous self-regulatory organizations, including FINRA, among others. Those laws and regulations may restrict Fidelity from hiring and/or associating with individuals with certain Criminal Histories.