Principal Engineer -Data Engineering
Wells Fargo7 days ago
Bengaluru, IndiaStaff+
Responsibilities
- Advise senior leadership and influence enterprise architecture, technology strategy, and implementation decisions across complex business and technical initiatives.
- Define and execute the enterprise data engineering modernization roadmap for the HR organization.
- Architect, develop, optimize, and maintain scalable metadata-driven data platforms, frameworks, and pipelines.
- Lead migration from legacy data platforms and frameworks to cloud-native, lakehouse-based architectures across Azure and GCP.
- Design and implement modern data platforms using Azure Fabric and GCP services.
- Provide hands-on technical leadership through design, code contributions, reviews, automation, testing, performance optimization, and secure coding.
- Drive AI and GenAI strategy, governance, adoption, and production implementation for HR initiatives.
- Mentor senior engineers, architects, and data engineering teams while promoting engineering excellence and continuous learning.
- Partner with architecture, product, analytics, risk, security, and business stakeholders to deliver enterprise-wide outcomes.
- Evaluate emerging technologies and industry practices while balancing innovation, operational stability, risk, compliance, and long-term sustainability.
Requirements
- At least 7 years of engineering experience, or equivalent demonstrated through work experience, training, military experience, or education.
- At least 7 years of progressive engineering experience with sustained hands-on expertise in architecture, system design, and end-to-end solution development.
- At least 7 years of data engineering experience, including migration from legacy data platforms to cloud-native, lakehouse-based architectures.
- At least 3 years of hands-on experience transforming legacy data frameworks to modern stacks in private or public cloud environments.
- Expertise with Azure Fabric, including OneLake, Data Factory, Synapse, Real-Time Analytics, and Power BI integration.
- Experience designing and building GCP data platforms using BigQuery, Dataflow or Apache Beam, Pub/Sub, Dataproc or Spark, Cloud Storage, Cloud Composer or Airflow, Dataplex, and Data Catalog.
- Deep expertise in SQL, Python, and distributed data processing frameworks such as Spark and Beam.
- Experience developing large-scale enterprise applications, data models, ETL/ELT patterns, lakehouse architectures, and microservice-based applications.
- Cloud-native engineering experience with serverless systems, managed Spark, and event-driven architectures.
- Familiarity with Docker, Kubernetes, workflow operators, and data governance platforms such as Collibra, Alation, and Purview.
- Experience implementing data lineage, observability, and drift detection.
- Strong background in AI, machine learning, and GenAI, including retrieval systems, embeddings, chunking strategies, and agentic AI workflows.
- Ability to provide enterprise technical stewardship, mentor technical teams, communicate architecture clearly, and align technology investments with business outcomes.
Tech Stack
Apache AirflowApache BeamApache SparkAzureDockerGoogle BigQueryGoogle Cloud PlatformKubernetesPythonSQL
Categories
Data Engineering
About Wells Fargo
Wells Fargo & Company is a U.S.-based financial services firm providing consumer and commercial banking, mortgages, credit, and wealth/investment services to individuals, small businesses, and enterprises. It earns revenue from interest income and fees across retail banking, payments, lending, and capital markets. Founded in 1852 and headquartered in San Francisco, it is publicly traded on the NYSE (WFC) and operates nationally with offices in multiple countries.