About this role:

Wells Fargo is seeking an SDET/Test Engineering Lead to join the Shared Service Operations Technology (SSOT) team and lead quality engineering, test automation, and data validation efforts for the SSOADS platform.

The ideal candidate will bring extensive experience leading quality engineering initiatives for modern data platforms, including data lakes, data warehouses, ETL/ELT pipelines, big data ecosystems, and cloud-native analytics environments. This individual will establish testing standards and automation frameworks while leading a team responsible for validating data ingestion, transformation, reconciliation, conformance, reporting, and regulatory data delivery processes. The role will partner closely with engineering, architecture, and product teams to ensure the integrity, accuracy, and reliability of critical enterprise data assets.

In this role, you will:

• Lead quality engineering strategy and governance for enterprise-scale data platforms and data pipelines.
• Define and implement comprehensive testing frameworks for batch, streaming, and event-driven data processing solutions.
• Establish automation standards for data validation, reconciliation, regression testing, and data quality certification.
• Design and oversee testing across ingestion, conformance, curated, and reporting layers.
• Develop automated validation solutions for BigQuery, GCS, Dataproc, Spark, Cloud Composer, Pub/Sub, and related GCP services.
• Define and implement Data Quality (DQ) testing practices including completeness, accuracy, consistency, timeliness, uniqueness, and reconciliation controls.
• Drive shift-left testing practices within Agile delivery teams.
• Lead test planning, test execution, defect triage, and release certification activities.
• Partner with Data Engineers, Architects, Product Owners, and Business SMEs to ensure data requirements are testable and measurable.
• Establish CI/CD-integrated automated testing and quality gates for data pipelines.
• Develop strategies for performance, scalability, and resiliency testing of data processing workloads.
• Ensure compliance with regulatory, audit, governance, and data lineage requirements.
• Define and track quality metrics, test coverage, defect leakage, and release readiness KPIs.
• Mentor QA engineers, SDETs, and data testers while promoting automation-first testing culture.
• Collaborate with production support teams to identify root causes of data issues and implement preventative quality controls.
• Evaluate and implement modern testing tools and frameworks to improve efficiency and reduce operational risk.

Required Qualifications:

• 5+ years of Software Engineering experience, or equivalent demonstrated through one or a combination of the following: work experience, training, military experience, education
• 5+ years of experience in Quality Engineering, Data Testing, or Test Automation.
• 5+ years of experience leading QA teams or test strategy initiatives.
• 5+ years of experience testing ETL/ELT pipelines, Data Warehouses, Data Lakes, and Big Data platforms.
• 5+ years' experience validating large-scale datasets in BigQuery, Teradata, Oracle, SQL Server, or similar platforms.
• 5+ years of experience with test automation using Python and/or Java.
• 2+ years of experience working with Apache Spark and distributed data processing validation.

Desired Qualifications:

• Experience integrating automated testing into CI/CD pipelines.
• Experience building automated data validation and regression testing frameworks.
• Knowledge of data quality testing methodologies and controls.
• Hands-on experience with SQL-based data validation and reconciliation testing.
• Strong understanding of Agile, DevOps, and Shift-Left testing practices.
• Experience creating test strategies, test plans, and quality metrics.
• Excellent stakeholder management and communication skills.
• Experience testing cloud-native data platforms on GCP.
• Knowledge of Apache Iceberg, Lakehouse architectures, and BigQuery external tables.
• Experience validating streaming pipelines and event-based architectures.
• Regulatory reporting, financial crimes, AML, Fraud, KYC, or compliance domain experience.
• Experience designing automated reconciliation frameworks across source-to-target data flows.
• Knowledge of metadata management, data lineage, and data governance concepts.
• Experience with performance and volume testing for large-scale data processing systems.
• Experience working with containerized workloads and Kubernetes.
• Experience supporting audit and regulatory validation activities.
• Strong leadership experience managing offshore/onshore QA teams.

Job Expectations:

• This position is not eligible for Visa sponsorship
• This position offers a hybrid work schedule
• Must be able to work on-site at any of the listed locations
• Relocation assistance is not available for this position
  Job Posting Locations:
  401 Las Colinas Blvd W Bldg A, Irving, Texas 75039

Posting End Date:

*Job posting may come down early due to volume of applicants.