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Wells Fargo Logo Wells Fargo · IT - Software Development

Senior Software Engineer

India, Bengaluru · Job Posted May 29, 2026
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Job Responsibility

  • Lead moderately complex initiatives within Technology and contribute to large scale data processing framework initiatives related to enterprise strategy deliverables
  • Build and maintain optimized and highly available data pipelines that facilitate deeper analysis and reporting
  • Review and analyze moderately complex business, operational or technical challenges that require an in-depth evaluation of variable factors
  • Oversee the data integration work, including developing a data model, maintaining a data warehouse and analytics environment, and writing scripts for data integration and analysis
  • Resolve moderately complex issues and lead teams to meet data engineering deliverables while leveraging solid understanding of data information policies, procedures and compliance requirements
  • Collaborate and consult with colleagues and managers to resolve data engineering issues and achieve strategic goals

Requirements

  • 4+ years of Data Engineering experience, or equivalent demonstrated through one or a combination of the following: work experience, training, military experience, education
  • Strong experience in EDL pipelines using Spark and BigQuery on GCP
  • Hands-on expertise in GCP services (BigQuery, Dataflow, GCS, IAM) and cloud-native architecture
  • Solid understanding of SQL, enterprise data governance, data quality, and approved data sources (ADS)
  • Exposure to AI/ML or GenAI use cases, including integration with data platforms and awareness of AI governance standards
  • Design and build scalable, production-grade data pipelines on GCP supporting analytics and AI workloads
  • Develop and manage secure, compliant cloud data platforms aligned with enterprise policies and controls
  • Optimize data processing for performance, cost efficiency, and reliability (Spark + BigQuery workloads)
  • Collaborate with AI/analytics teams to enable feature engineering, model consumption, and AI-driven insights
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