Lead Data Engineer – GCP Platform Services, Frameworks

Wells Fargo

Lead Data Engineer responsible for designing GCP-based data pipeline development at Wells Fargo. Ensuring data is accurate and consumable via standardized analytics and APIs for finance functions.

Posted 6/3/2026full-timeIselin • New Jersey, North Carolina, Texas • 🇺🇸 United StatesSenior💰 $119,000 - $224,000 per yearWebsite

Tech Stack

Tools & technologies

AirflowApacheBigQueryCloudETLGoogle Cloud PlatformPythonSparkSQLVault

About the role

Key responsibilities & impact

Lead the design and implementation of 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
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
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
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
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

What you’ll need

5+ years of Data Engineering experience, or equivalent demonstrated through one or a combination of the following: work experience, training, military experience, education
4+ years with orchestration tools (Cloud Composer/Airflow) and CI/CD (Cloud Build, Git‑based workflows) for data workloads
4+ Python and Spark for building data pipelines, libraries, and automation tooling
4+ years of advanced SQL and data modeling for analytics and warehousing; experience with ETL/ELT design patterns
4+ years’ experience with automated testing, data quality checks, and monitoring for pipelines and platform services
4+ years’ experience with logging/monitoring stacks (Cloud Logging, Cloud Monitoring, error reporting, metrics dashboards
3+ years of experience with core GCP data services: BigQuery, Dataflow/Apache Beam, Dataproc, Pub/Sub

Benefits

Comp & perks

Health benefits
401(k) Plan
Paid time off
Disability benefits
Life insurance, critical illness insurance, and accident insurance
Parental leave
Critical caregiving leave
Discounts and savings
Commuter benefits
Tuition reimbursement
Scholarships for dependent children
Adoption reimbursement

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills & Tools

data engineeringPythonSQLApache BeamSparkdata modelingETLELTdata quality checksautomated testing

Soft Skills

leadershipcollaborationdocumentationcommunicationenablement