Principal Engineer

Job description

**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 groups - Lead 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 thinking - Translate 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 solutions - Provide vision, direction and expertise to leadership on implementing innovative and significant business solutions - Maintain knowledge of industry best practices and new technologies and recommends innovations that enhance operations or provide a competitive advantage to the organization - Strategically engage with all levels of professionals and managers across the enterprise and serve as an expert advisor to leadership **Required Qualifications:** - 7+ years of Engineering experience, or equivalent demonstrated through one or a combination of the following: work experience, training, military experience, education **Job 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 Opportunity** Wells Fargo is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religi