Principal Engineer -Data Engineering
Wells Fargo (company site, opens in a new tab)7+ yrsBengaluruOn-siteDirect career pageEst. 35–55 LPA
Posted 21h ago
Your match
Against your primary resume
Log in to see your match score
Create a free account or log in to unlock your CV match score across:
- Role fit
- Experience
- Industry relevance
Reach people at Wells Fargo
People at this company you can reach
Log in to see who works here
Create a free account or log in to see the people at Wells Fargo you could write to:
- Recruiters & HR
- People in this function
- Work addresses
Protocol Intelligence
How competitive this role is
Competition
Background fit
Strictness
Log in to see why each signal reads the way it does.
Job description
Structured overview of role & requirements
About This Role
- Lead design, architecture, and delivery of scalable, secure data engineering and Generative AI solutions for HR IT, influencing enterprise HR data strategy.
- Provide technical leadership and advisory to senior leadership on complex technical challenges and data modernization initiatives impacting multiple business lines.
- Drive innovation by integrating AI technologies and maintaining operational excellence in data platforms and engineering frameworks.
Minimum Requirements
- 7+ years of engineering experience including architecture, system design, and data engineering.
- Strong hands-on experience migrating legacy data platforms to cloud-native lakehouse architectures, specifically on Azure Fabric and GCP.
- Proficiency in SQL, Python, distributed data processing frameworks (Spark, Beam), and cloud-native engineering tools (e.g., Docker, Kubernetes).
- Work Experience Required: 7+ years of progressive engineering experience (explicitly stated).
Ideal Candidate Profile
- Experienced in leading enterprise-scale data modernization projects with strategic influence across business and technology stakeholders.
- Demonstrates a strong blend of hands-on technical expertise and thought leadership in data engineering, AI/GenAI, and cloud architectures.
- Skilled in mentoring senior engineers, shaping data engineering roadmaps, and balancing innovation with operational risk and sustainability.