
Principal, Data Engineer
Job Description:
Note: Fidelity will not provide immigration sponsorship for this position.
The Role
The Principal Data Engineer is a senior technical leadership position responsible for driving the enterprise data strategy and shaping how data engineering is executed across the organization. This role acts as the technical authority for data engineering, defining engineering excellence, setting standards, and guiding teams in the design, delivery, and operation of modern data platforms—primarily leveraging Microsoft Fabric.
You will translate business and finance transformation goals into scalable, governed data architectures while remaining hands-on for critical designs. This role is ideal for a seasoned engineering leader who owns end-to-end delivery and is passionate about building durable, well-governed, enterprise-scale data platforms that support analytics and future AI/ML workloads.
Key Responsibilities Include:
- Leading implementation of the enterprise data strategy and aligning it with business and finance transformation goals.
- Serving as the principal technical authority for data engineering across teams and programs.
- Defining and evolving the target-state data platform using Microsoft Fabric and Azure services.
- Establishing and enforcing data engineering best practices, coding standards, modeling patterns, and DataOps practices.
- Implementing engineering excellence controls (quality gates, observability, reliability, production readiness).
- Championing modern engineering automation and deployment practices.
- Designing, developing, and overseeing enterprise-scale pipelines, ETL/ELT processes, and data models.
- Guiding teams in building performant, governed lakehouse, warehouse, and semantic models.
- Staying hands-on for critical architectures and complex engineering challenges.
- Partnering with business and analytics teams to translate requirements into high-quality data solutions.
- Acting as a trusted advisor to senior leaders on risks, tradeoffs, and technical direction.
- Mentoring engineers to raise technical maturity across the organization.
- Ensuring solutions meet enterprise expectations for availability, reliability, performance, and cost efficiency.
- Overseeing operations, monitoring, troubleshooting, and continuous improvement of data pipelines.
- Driving modernization of legacy workflows into cloud-native, Fabric-based platforms.
The Skills and Expertise You Bring
Required Qualifications
- Demonstrated experience as a Lead or Principal Data Engineer, owning architecture and delivery of enterprise-scale data platforms.
- Deep hands-on experience with Microsoft Fabric and/or Azure data services (Fabric Lakehouse, Data Factory, Synapse, Databricks).
- Strong ability in data modeling, ETL/ELT design, and modern data warehousing concepts.
- Proficiency in programming languages such as Python or Scala.
- Proven ability to establish and enforce engineering standards and best practices.
- Advanced SQL capability and strong understanding of modern data architectures.
- Excellent communication skills with the ability to influence technical and non-technical stakeholders.
Preferred Qualifications
- Bachelor’s degree in Computer Science, Engineering, or related field.
- Experience supporting finance or enterprise reporting use cases, with understanding of financial data domains.
- Familiarity with CI/CD, DevOps, DataOps, and governance tooling.
- Experience modernizing legacy data platforms into cloud-native architectures.
- Experience implementing AI/ML solutions in Azure + Fabric environments.
- Knowledge of Microsoft Purview and enterprise data governance frameworks.
The Team
Success in this role means elevating the overall capability and maturity of the data engineering organization while enabling enterprise-wide transformation. You’ll collaborate closely with:
- Data Engineers & Senior Engineers — guiding, mentoring, and elevating engineering excellence across teams.
- Business Analysts & Finance Stakeholders — translating business needs into scalable data solutions and enabling advanced analytics.
- Architecture & Analytics Teams — defining target-state architectures, semantic models, and governed data assets.
- Senior Leadership — advising on risks, tradeoffs, and strategic direction for enterprise data capabilities.
What Success Looks Like
- A well-governed, clearly defined enterprise data platform aligned with strategic goals.
- Consistent, high-quality engineering practices adopted across the organization.
- Scalable, reliable pipelines enabling finance transformation and advanced analytics.
- A more mature, high-performing data engineering team shaped through strong leadership and mentorship.
Certifications:
Category:
Information TechnologyMost roles at Fidelity are Hybrid, requiring associates to work onsite every other week (all business days, M-F) in a Fidelity office. This does not apply to Remote or fully Onsite roles. Some roles may have unique onsite requirements. Please consult with your recruiter for the specific expectations for this position.
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.
