Principal Engineer, Data Engineering

Wells Fargo

Confirmed live today High trust
Closes in 4 days Hybrid

Quick summary

Work type
Hybrid
Location
Irving, TX
Employment
Full-time
Posted
3 days ago
Freshness
Confirmed live today
Closes
Oct 6, 2026 (soon)

Market check

Salary context

How this pay compares to similar roles

Similar $194k
$130k most similar roles pay here $265k

This listing doesn't post a salary. Most similar roles pay $162,000–$225,500.

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 34 open roles on FindRole.

Listed pay typically runs $119,000–$224,000 across 17 roles with salary data.

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At a glance

TL;DR · Principal Engineer, Data Engineering

The Principal Engineer - Data Engineering joins the Shared Service Operations Technology team to drive architecture, engineering strategy, and modernization of enterprise-scale data platforms. This leader will design and implement scalable cloud-native data solutions, including data lakes, warehouses, and lakehouse architectures to support operational intelligence and regulatory reporting. Day-to-day responsibilities include establishing engineering standards for batch, real-time, and event-driven processing while managing data ingestion, transformation, and metadata-driven frameworks. The role requires expertise in distributed processing using Spark, Hadoop, and Dataproc, alongside cloud platforms like GCP, AWS, or Azure. Technical skills include Python, Java, SQL, and infrastructure as code tools like Terraform. The candidate will solve complex problems regarding data governance, lineage, and security while building resilient pipelines to ensure auditability and compliance within a highly regulated financial services environment.

What does a Engineer earn in Texas?

Median $182000 from 39 postings across 14 companies.

See salary data

What you'll do

  • Define the enterprise data engineering strategy, architecture standards, and technology roadmap.
  • Design and implement scalable cloud-native data platforms, including data lakes and lakehouse architectures.
  • Architect end-to-end data ingestion, transformation, and delivery pipelines for batch and real-time processing.
  • Drive modernization initiatives involving cloud migration, platform consolidation, and legacy system transformation.
  • Establish engineering standards for DataOps, CI/CD, Infrastructure-as-Code, and automated monitoring.
  • Implement data governance frameworks including lineage, metadata management, and quality controls.
  • Design high-availability data solutions that meet regulatory reporting, security, and compliance requirements.
  • Mentor senior engineers and technical leads while providing oversight for complex enterprise programs.

What we're looking for

  • 7+ years of engineering experience or equivalent through work, training, military service, or education.
  • 5+ years of experience designing and implementing data lakes, warehouses, lakehouse architectures, and enterprise data platforms.
  • 5+ years of expertise in distributed data processing technologies including Apache Spark, Dataproc, or Hadoop ecosystems.
  • 5+ years of experience building cloud-native data solutions using GCP, AWS, Azure, or equivalent platforms.
  • 5+ years of programming experience using Python, Java, SQL, or similar engineering languages.
  • 5+ years of experience in ETL/ELT architecture, data integration patterns, and enterprise data movement strategies.
  • 5+ years of knowledge in security, encryption, access controls, and enterprise risk management requirements.
  • Experience building cloud-native platforms on GCP with specific tools like BigQuery, Pub/Sub, or Dataproc (preferred).

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