Lead Data Engineer

About the 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.

Responsibilities

• 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).

• Develop shared transformation libraries in Python/SQL/Beam (e.g., common SCD patterns, data quality checks, masking/tokenization routines).

• Provide orchestration capabilities via Cloud Composer or Cloud Workflows with reusable DAGs/templates and CI/CD integration.

• Implement robust data modeling (dimensional, data vault, or canonical models) and semantic layers in BigQuery and related tools.

• Enforce data quality, lineage, and observability using standardized metrics, validation rules, and monitoring dashboards.

• Apply security and governance controls: IAM, VPC-SC, CMEK, row/column-level security, and policy-driven access patterns.

• Partner with domain data engineers, analytics, and ML teams to onboard use cases onto platform services and frameworks.

• Document patterns, runbooks, and best practices, and provide enablement through workshops and code examples.

• Contribute to platform roadmap, tool selection, and evaluation of new GCP services and open-source components.

Requirements

• 5+ years of Database Engineering experience, or equivalent demonstrated through one or a combination of the following: work experience, training, military experience, education

• 5+ years of data management experience within Public Cloud (GCP, AWS, Azure)

• 5+ years of hands-on experience of Python or Java, plus Spark SQL for building data pipelines, libraries, and automation tooling.

• 5+ years with orchestration tools (Cloud Composer/Airflow) and CI/CD (Cloud Build, Git-based workflows) for data workloads

Desired Qualifications

• Experience with logging/monitoring stacks (Cloud Logging, Cloud Monitoring, error reporting, metrics dashboards)

• Experience with automated testing, data quality checks, and monitoring for pipelines and platform services

• Knowledge of cloud architecture principles (networking, security, IAM, reliability, cost management)

• Experience with core GCP data services: BigQuery, Dataflow/Apache Beam, Dataproc, Pub/Sub

• Experience with Agile transformations and technology roadmaps

• Experience working with onshore and offshore teams