Principal Engineer

About this role:Wells Fargo is seeking a Principal Engineer.In this role, you will:Act as an advisor to leadership to develop or influence applications, network, information security, database, operating systems, or web technologies for highly complex business and technical needs across multiple groupsLead the strategy and resolution of highly complex and unique challenges requiring in-depth evaluation across multiple areas or the enterprise, delivering solutions that are long-term, large-scale and require vision, creativity, innovation, advanced analytical and inductive thinkingTranslate advanced technology experience, an in-depth knowledge of the organizations tactical and strategic business objectives, the enterprise technological environment, the organization structure, and strategic technological opportunities and requirements into technical engineering solutionsProvide vision, direction and expertise to leadership on implementing innovative and significant business solutionsMaintain knowledge of industry best practices and new technologies and recommends innovations that enhance operations or provide a competitive advantage to the organizationStrategically engage with all levels of professionals and managers across the enterprise and serve as an expert advisor to leadershipRequired Qualifications:7+ years of Engineering experience, or equivalent demonstrated through one or a combination of the following: work experience, training, military experience, educationJob Expectations:Data Modelling & Semantic Architecture Lead enterprise-wide data modelling strategy, including conceptual, logical, and physical models for analytical and operational workloads. Design scalable, high-performance data models optimized for BI, advanced analytics, and AI/ML use cases. Build and standardize semantic layers, canonical data models, and domain-driven data products. Enable knowledge graphs and context-aware data representations to support advanced AI and LLM-driven use cases. Platform Engineering & Architecture Design and implement real-time and batch data architectures on GCP. Develop scalable data pipelines and orchestration frameData Governance, Quality & Trust Establish and operationalize enterprise data governance frameworks, including data ownership, stewardship, and policy enforcement. Implement data quality, lineage, observability, and metadata management practices using modern tooling (e.g., Dataplex, Data Catalog). Define and enforce data contracts and domain-level SLAs in a distributed data mesh architecture. Ensure compliance with privacy, risk, regulatory, and security requirements, particularly for AI/ML and GenAI systems. Data & AI Platform Engineering Architect and deliver scalable real-time and batch data platforms on GCP, supporting enterprise analytics and AI workloads. Develop event-driven and streaming architectures leveraging Pub/Sub, Dataflow, BigQuery, and Cloud Composer. Build reusable data ingestion, transformation, and orchestration frameworks for structured and unstructured data. Enable feature engineering, feature stores, and data pipelines supporting end-to-end ML lifecycle. Predictive AI/ML Engineering Lead the design and implementation of predictive AI/ML frameworks, including model training, validation, deployment, and monitoring. Collaborate with data science teams to build production-grade ML pipelines and ensure scalability, reproducibility, and governance. Enable MLOps practices, including model versioning, experimentation, drift detection, and performance tracking. Drive adoption of advanced analytics and predictive insights to support risk management, operations, and customer experience. Additional Required Qualifications  Strong experience in data engineering, platform engineering, or distributed systems architecture, with a strong focus on enterprise-scale solutions.  7+ years of technical leadership experience, influencing architecture and engineering strategy across multiple teams or business units.  Proven track record of driving large-scale data and AI platform transformations in complex, regulated environments. 7+ years of hands-on experience in data modelling (conceptual, logical, and physical) for both analytical and operational systems.  Deep expertise in dimensional modelling, data vault, or domain-driven data design, supporting BI, AI/ML, and real-time workloads.  Strong experience designing semantic layers, canonical data models, and data products in distributed architectures (e.g., data mesh). 7+ years of experience building cloud-native data platforms at scale, preferably on GCP (BigQuery, Dataflow, Pub/Sub, Cloud Composer, GCS).  5+ years of experience delivering real-time and event-driven data pipelines.  Expertise in designing high-throughput, low-latency ingestion, transformation, and orchestration frameworks. 7+ years implementing data governance frameworks, including metadata management, lineage, quality, and stewardship models.  Strong experience with data contracts, data quality rules, and observability tooling.  Deep understanding of regulatory, privacy, and risk requirements, especially in financial services or similarly regulated industries. Desired Qualifications:Experience in large-scale financial institutions (100k+ employees) or highly regulated enterprises.  Familiarity with federated query engines (Trino/Starburst) and decentralized data governance models.  Exposure to DevSecOps, CI/CD pipelines, and platform automation frameworks.  Experience building and mentoring high-performing engineering and architecture teams. Posting End Date: 26 Jun 2026*Job posting may come down early due to volume of applicants.We Value Equal OpportunityWells Fargo is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, status as a protected veteran, or any other legally protected characteristic.Emp