Lead Data Engineer

About this role

Within COO Technology, Wells Fargo is seeking a Lead Data Engineer to help shape and scale our cloud‑native data ecosystem. In this role, you will focus on Google Cloud Platform (GCP) services and frameworks, leading the design, build, and operation of reusable data capabilities that power analytics and AI at enterprise scale. The ideal candidate is passionate about standardized frameworks, self‑service data platforms, and governance‑by‑design, enabling secure, reliable, and compliant data solutions across Google Cloud services.

The COO Technology group powers the firm’s most critical operations by modernizing and optimizing enterprise technology platforms that enable resiliency, regulatory excellence, data services, customer experience, and strategic execution across the Chief Operating Office.

In this role, you will

• Design and implement scalable, secure data platforms on Google Cloud using managed services (BigQuery, Dataflow, Dataproc, Pub/Sub, Cloud Storage, Composer).)
• Build reusable frameworks and tooling (ingestion, transformation, quality, orchestration) that can be adopted by multiple product and domain teams.
• Enable self‑service data consumption and governance by standardizing patterns, templates, and platform capabilities rather than one‑off pipelines.
• Design logical and physical data platform architectures leveraging BigQuery, Dataflow/Apache Beam, Dataproc/Spark, Pub/Sub, and Cloud Storage.
• Define and implement standardized ingestion, transformation, and serving patterns (batch and streaming) as reusable blueprints.
• Optimize cost, performance, and reliability of GCP data workloads (partitioning, clustering, storage classes, autoscaling strategies).
• Build opinionated data ingestion frameworks (e.g., config‑driven pipelines, connectors, schema handling, error handling) on top of Dataflow, Dataproc, or Composer.
• Develop shared transformation libraries in Python/SQL/Beam (e.g., common SCD patterns, data qualit...