- Wells Fargo hiring Lead Data Engineer jobs
- Post Name: Lead Data Engineer
- Company: Wells Fargo
- Degree: B.E/B.Tech/M.E/M.Tech/MCA (Computer Science/IT/Data Science or related field)
- Salary: ₹18 LPA – ₹32 LPA (depending on experience)
- Location: Bengaluru/Hyderabad/Chennai/Pune
- Experience: 6-10 years
Company Overview
Wells Fargo is one of the world’s leading financial services institutions, offering a wide range of banking, investment, mortgage, and consumer finance services. Headquartered in the United States, the company serves millions of clients globally and has built a strong reputation for financial expertise, technology innovation, and enterprise-level operations.
The company focuses on providing secure, reliable, and customer-centric financial solutions through digital transformation, advanced analytics, and modern technology platforms. Wells Fargo invests heavily in data, cloud technologies, cybersecurity, and platform modernization to improve customer experience and increase business efficiency.
Its technology and engineering teams work on large-scale systems that support data management, risk analysis, fraud detection, regulatory reporting, and customer insights. Wells Fargo professionals have the opportunity to work with enterprise platforms, modern engineering tools, and global teams across multiple business units.
Job Description: Wells Fargo Hiring Lead Data Engineer
Wells Fargo is hiring experienced professionals for the role of Lead Data Engineer. The selected candidate will be responsible for building, maintaining, and optimizing large-scale data pipelines and platforms that support analytics, reporting, and enterprise decision-making.
As a Lead Data Engineer, you will work closely with data architects, analysts, business stakeholders, and engineering teams to build reliable data solutions for complex business needs. The role requires strong expertise in data engineering, database systems, cloud technology and big data processing.
You will be responsible for developing scalable ETL and ELT pipelines, integrating data from multiple sources, and ensuring data accuracy, consistency, and security across enterprise platforms. The role also includes improving data architecture, supporting real-time and batch processing, and enabling advanced analytics initiatives.
Key Responsibilities
- Design and build scalable data pipelines and data integration solutions
- Develop ETL/ELT workflows for enterprise data platforms
- Integrate data from databases, APIs, cloud sources, and third-party systems
- Optimize data processing performance and storage efficiency
- Ensure data quality, integrity, and consistency across all systems
- Support batch and real-time data processing requirements
- Collaborate with analysts, architects, and business teams on data solutions
- Maintain data models, metadata and technical documentation
- Apply automation for deployment, monitoring, and workflow management
- Troubleshoot data pipeline failures and production issues
- Mentoring junior engineers and promoting engineering best practices.
Eligibility Criteria
| Requirement | Details |
|---|---|
| Education | B.E/B.Tech/M.E/M.Tech/MCA in Computer Science, IT, Data Science, or related field |
| Experience | 6–10 years of experience in data engineering or big data development |
| Programming Skills | Strong knowledge of Python, Java, Scala, or SQL |
| Data Engineering Skills | Experience with ETL/ELT development, data modeling, and pipeline design |
| Big Data Tools | Knowledge of Spark, Hadoop, Kafka, or similar technologies |
| Cloud Skills | Experience with AWS, Azure, or Google Cloud data services |
| Database Knowledge | Strong understanding of SQL, NoSQL, and relational databases |
| Tools | Experience with Airflow, Informatica, Talend, or similar tools |
| Communication | Good verbal and written communication skills |
| Analytical Skills | Strong problem-solving and performance optimization abilities |
essential skills
- Strong expertise in data pipeline design and engineering
- Experience with big data technologies and distributed systems
- Advanced SQL and database optimization knowledge
- Strong programming and scripting abilities
- Understanding of cloud-based data platforms and storage systems
- Knowledge of data governance, security and compliance practices
- Ability to troubleshoot complex production problems
- Experience with workflow orchestration and automation tools
- Leadership and Guidance Abilities
- Ability to work with cross-functional teams in an enterprise environment
salary and benefits
- Competitive salary package (₹18 LPA – ₹32 LPA)
- Performance-Based Bonuses and Incentives
- Health insurance and welfare benefits
- Provident Fund and Retirement Benefits
- Paid Holidays and Flexible Leave Options
- Learning and Development Program
- Technical Training and Certification Assistance
- Career Development Opportunities in Data Engineering and Analytics
- Exposure to global financial technology projects
interview process
- online application
- Resume Shortlisting
- technical evaluation
- Technical Interview (SQL, Data Engineering, Big Data Tools)
- managerial phase
- HR discussion and proposal letter
Required Documents
- updated resume
- educational certificate
- government ID proof
- experience certificate
- latest salary slips
- passport-size photo
How to apply
Interested candidates can apply through the official Wells Fargo careers website by searching “Lead Data Engineer” in the jobs section. Submit your updated resume and highlight your experience in ETL development, big data tools, SQL, cloud platforms, and enterprise data systems.
Candidates can also apply through professional networking platforms and job portals. Early application is recommended as vacancies may close after suitable candidates have been shortlisted.
FAQ
1. Is prior data engineering experience required?
Yes, this role typically requires strong practical experience in data engineering and enterprise data platforms.
2. Are new hires eligible for this role?
No, this is a leading level role that requires significant industry experience.
3. What tools are commonly used in this role?
Spark, SQL, Python, cloud platforms, ETL tools, and workflow orchestration tools are commonly used.
4. Is cloud knowledge mandatory?
Cloud platform experience is highly beneficial and is often preferred for modern data engineering roles.
5. Is this role a good fit for long-term career development?
Yes, it offers excellent career opportunities in enterprise data engineering, analytics, and financial technology.
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