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Wells Fargo
Wells Fargo

Leading company in the financial services industry

Senior Software Engineer at Wells Fargo

RoleData Engineering
LevelSenior
LocationBengaluru, India
WorkOn-site
TypeFull-time
Posted1 day ago
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About the role

About this role:

Wells Fargo is seeking Senior Software Engineer – Credit Risk Technology (Data & GenAI)

In this role, you will:

  • Lead moderately complex initiatives and deliverables within technical domain environments

  • Contribute to large scale planning of strategies

  • Design, code, test, debug, and document for projects and programs associated with technology domain, including upgrades and deployments

  • Review moderately complex technical challenges that require an in-depth evaluation of technologies and procedures

  • Resolve moderately complex issues and lead a team to meet existing client needs or potential new clients needs while leveraging solid understanding of the function, policies, procedures, or compliance requirements

  • Collaborate and consult with peers, colleagues, and mid-level managers to resolve technical challenges and achieve goals

  • Lead projects and act as an escalation point, provide guidance and direction to less experienced staff.

Required Qualification :

  • 4+ years of Software Engineering experience, or equivalent demonstrated through one or a combination of the following: work experience, training, military experience, education

Desired Qualifications:

  • Design, develop, and maintain large‑scale data engineering solutions for credit risk data using modern big‑data and distributed computing frameworks

  • Lead data platform modernization initiatives, including performance optimization, scalability, reliability, and security

  • Build and optimize ETL/ELT pipelines for structured and semi‑structured data using Spark, Hadoop, and cloud‑based technologies

  • Develop robust data models, analytics layers, and reporting datasets to support credit risk analysis and regulatory reporting

  • Apply Generative AI and AI/ML techniques (e.g., LLMs, embeddings, intelligent data enrichment, automated insights, anomaly detection) to enhance risk analytics, data quality, and operational efficiency

  • Collaborate closely with Credit Risk, Analytics, and Business stakeholders to translate business requirements into technical architectures and solutions

  • Review code, enforce best practices, and provide technical guidance and mentorship to junior team members

  • Contribute to architectural decisions, technology selection, and long‑term platform roadmaps

  • Ensure solutions meet enterprise standards for governance, security, auditability, and regulatory compliance.

  • Experience with batch processing and scheduling tools such as Autosys

  • Hands‑on experience with Dremio or similar data virtualization/query acceleration platforms

  • Experience building data solutions on cloud platforms (AWS, Azure, or GCP), including cloud storage, compute, and orchestration services

  • Exposure to ML/AI platforms, MLOps concepts, or AI governance frameworks in regulated environments

  • Experience working in financial services, risk, or regulated data domains Job Expectations:

  • 4+ years of professional Software Engineering experience, or equivalent demonstrated through work experience, training, military experience, or education

  • 4+ years of hands‑on experience building ETL/ELT pipelines on big‑data platforms such as Apache Spark, Hadoop, and Hive

  • 4+ years of data engineering experience using Py Spark/Python, Hadoop ecosystem tools, Hive, and/or Scala

  • Strong experience (4+ years) with RDBMS and SQL‑based data modeling

  • 3+ years of experience with UNIX/Linux environments and Shell scripting

  • 2+ years of experience leading technical initiatives, mentoring engineers, and providing solution‑level guidance

  • Solid understanding of data engineering best practices, including performance tuning, data quality, testing, and observability

  • Experience or strong interest in Generative AI / AI‑driven data solutions, including working with LLMs, AI pipelines, or intelligent analytics use cases.

Posting End Date:

13 May 2026

Job posting may come down early due to volume of applicants.We Value Equal Opportunity

Wells Fargo is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, status as a protected veteran, or any other legally protected characteristic.

Employees support our focus on building strong customer relationships balanced with a strong risk mitigating and compliance-driven culture which firmly establishes those disciplines as critical to the success of our customers and company. They are accountable for execution of all applicable risk programs (Credit, Market, Financial Crimes, Operational, Regulatory Compliance), which includes effectively following and adhering to applicable Wells Fargo policies and procedures, appropriately fulfilling risk and compliance obligations, timely and effective escalation and remediation of issues, and making sound risk decisions. There is emphasis on proactive monitoring, governance, risk identification and escalation, as well as making sound risk decisions commensurate with the business unit’s risk appetite and all risk and compliance program requirements.

Candidates applying to job openings posted in Canada: Applications for employment are encouraged from all qualified candidates, including women, persons with disabilities, aboriginal peoples and visible minorities. Accommodation for applicants with disabilities is available upon request in connection with the recruitment process.

Applicants with Disabilities

To request a medical accommodation during the application or interview process, visit Disability Inclusion at Wells Fargo.

Drug and Alcohol Policy

Wells Fargo maintains a drug free workplace. Please see our Drug and Alcohol Policy to learn more.

Wells Fargo Recruitment and Hiring Requirements:

a. Third-Party recordings are prohibited unless authorized by Wells Fargo.

b. Wells Fargo requires you to directly represent your own experiences during the recruiting and hiring process.

Required skills

Data engineering

ETL/ELT

Distributed computing

Performance optimization

Scalability

Reliability

Technical leadership

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About Wells Fargo

Wells Fargo

Wells Fargo & Company is an American multinational financial services company. The company operates in 35 countries and serves more than 70 million customers worldwide.

10,001+

Employees

San Francisco

Headquarters

$163B

Valuation

Reviews

10 reviews

3.7

10 reviews

Work-life balance

3.8

Compensation

3.2

Culture

3.9

Career

3.1

Management

3.4

72%

Recommend to a friend

Pros

Good benefits and health coverage

Flexible schedules and work arrangements

Supportive team environment

Cons

Limited career advancement opportunities

High stress and overwhelming workload

Poor management and lack of direction

Salary Ranges

16 data points

Mid/L4

Senior/L5

Mid/L4 · Lead Analytics Consultant

1 reports

$151,878

total per year

Base

$116,064

Stock

-

Bonus

-

$151,878

$151,878

Interview experience

4 interviews

Difficulty

3.0

/ 5

Duration

21-35 weeks

Offer rate

25%

Interview process

1

Application Review

2

Recruiter Screen

3

Online Assessment

4

Technical Interview

5

Behavioral Interview

6

Offer

Common questions

Coding/Algorithm

Technical Knowledge

Behavioral/STAR

Past Experience