Lead Data Engineer

Wells Fargo

Closes in 3 days Hybrid

Quick summary

Work type
Hybrid
Location
Iselin, NJ · Charlotte, NC · Irving, TX
Salary
$119,000–$224,000 / yr
Posted
4 days ago
Closes
Jun 9, 2026 (soon)

Market check

Salary context

Competitive pay

How this pay compares to similar roles

Similar $182k
This role $172k
$106k most similar roles pay here $237k

This role pays less than 55% of similar roles. Most pay $146,800–$217,725 — the shaded band above. At the midpoint, this role pays about $172k versus about $182k for comparable roles.

Based on 240 similar postings.

Employer

About Wells Fargo

Wells Fargo & Company is one of the largest banks in the United States, providing banking, investment, mortgage, and consumer and commercial finance products and services nationwide. Industry: Banking & Financial Services

Wells Fargo currently has 91 open roles on FindRole.

Listed pay typically runs $151,000–$239,000 across 54 roles with salary data.

Most-posted roles

View all roles at Wells Fargo

At a glance

TL;DR · Lead Data Engineer

Wells Fargo’s COO Technology team is hiring a Lead Data Engineer to drive the development of their cloud-native data ecosystem on Google Cloud Platform (GCP). This senior role involves designing and implementing scalable, secure data platforms using GCP services like BigQuery, Dataflow, and Pub/Sub, while also building reusable frameworks for ingestion, transformation, and orchestration. The ideal candidate will enable self-service data consumption through standardized patterns and governance-by-design principles, ensuring compliance and reliability across multiple teams. Required skills include 5+ years of experience in database engineering, public cloud management (preferably GCP), hands-on expertise with Python or Java, Spark SQL, and CI/CD tools like Cloud Composer. Knowledge of cloud architecture, data quality checks, and automated testing is highly desirable as the role demands robust security controls and seamless collaboration with cross-functional teams to onboard use cases onto platform services.

What you'll do

  • Design and implement scalable, secure data platforms on Google Cloud using managed services.
  • Build reusable frameworks for ingestion, transformation, quality, and orchestration across teams.
  • Enable self-service data consumption by standardizing patterns and templates for governance.
  • Optimize cost, performance, and reliability of GCP data workloads with partitioning and autoscaling.
  • Develop shared transformation libraries in Python/SQL/Beam for common SCD patterns and masking.

What we're looking for

  • 5+ years of Database Engineering experience or equivalent
  • 5+ years of data management in Public Cloud (GCP, AWS, Azure)
  • Hands-on expertise with Python/Java and Spark SQL for data pipelines
  • Extensive use of orchestration tools like Cloud Composer/Airflow and CI/CD practices
  • Deep knowledge of core GCP data services including BigQuery, Dataflow, Dataproc
  • Experience with cloud architecture principles such as networking, security, IAM
  • Proven ability to work effectively in Agile environments and contribute to technology roadmaps

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