Lead Data Engineer

Wells Fargo

Closes in 4 days Hybrid

Quick summary

Work type: Hybrid
Location: Irving, TX
Posted: 1 day ago
Closes: Jun 8, 2026 (soon)

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Salary context

How this pay compares to similar roles

Similar $174k

$120k most similar roles pay here $231k

This listing doesn't post a salary. Most similar roles pay $135,000–$212,837.

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 71 open roles on FindRole.

Listed pay typically runs $119,000–$224,000 across 35 roles with salary data.

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At a glance

TL;DR · Lead Data Engineer

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Wells Fargo is hiring a Lead Data Engineer for its Data & Insights team, focusing on designing and building scalable data platforms using Google Cloud Platform (GCP) and enterprise-grade technologies. This senior role involves leading the development of large-scale data pipelines with Apache Spark and GCP-native services, architecting event-driven data platforms with Kafka and Pub/Sub, and optimizing BigQuery for performance and cost efficiency. The ideal candidate will work closely with a team of data engineers, product managers, and data scientists to deliver secure, compliant, and scalable solutions in the Merchant domain, ensuring data quality and governance through enterprise frameworks. Required skills include extensive experience with GCP, Apache Spark, Kafka, and DevOps practices, as well as familiarity with data governance standards and legacy workflow modernization in the credit card industry.

Skills

Google Cloud Platform Apache Spark Apache Kafka BigQuery MS SQL Server MongoDB Teradata dbt Agile CI/CD Jenkins GitLab Tekton Autosys Cloudera Data Platform GraphQL REST SQL NoSQL

What you'll do

Lead the design and development of large-scale data pipelines using Apache Spark and GCP-native services.
Architect event-driven data platforms using Apache Kafka and Pub/Sub for real-time ingestion and processing.
Build and optimize data warehouse architectures using BigQuery, Cloud Storage, and MS SQL Server.
Design and implement real-time streaming solutions using Kafka Streams and Spark Structured Streaming.
Ensure data quality, lineage, observability, and governance through enterprise frameworks and controls.
Optimize BigQuery performance and cost efficiency using partitioning, clustering, and workload management best practices.

What we're looking for

3+ years leading data engineering teams and projects
Expertise in Google Cloud Platform, including BigQuery and Dataplex
Proficient in Apache Spark, Kafka, and dbt for data pipeline development
Experience with large-scale distributed systems like Cloudera Data Platform
Strong background in Agile, CI/CD, and DevOps practices using Jenkins or GitLab

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