Lead Software Engineer

Wells Fargo · Hyderabad · 5+ yrs experience · Posted 2026-07-28

Tech stack: FastAPI, Flask, Kubernetes, Python, SQL

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About the role

About this role: Wells Fargo is seeking a Lead Software Engineer. In this role, you will: Lead complex technology initiatives including those that are companywide with broad impact. Act as a key participant in developing standards and companywide best practices for engineering complex and large scale technology solutions for technology engineering disciplines. Design, code, test, debug, and document for projects and programs. Review and analyze complex, large-scale technology solutions for tactical and strategic business objectives, enterprise technological environment, and technical challenges that require in-depth evaluation of multiple factors, including intangibles or unprecedented technical factors. Make decisions in developing standard and companywide best practices for engineering and technology solutions requiring understanding of industry best practices and new technologies, influencing and leading technology team to meet deliverables and drive new initiatives. Collaborate and consult with key technical experts, senior technology team, and external industry groups to resolve complex technical issues and achieve goals. Lead projects, teams, or serve as a peer mentor. Required Qualifications: 5+ years of Software Engineering experience, or equivalent demonstrated through one or a combination of the following: work experience, training, military experience, education. Desired Qualifications: Lead lakehouse engineering efforts by utilizing open table formats such as Iceberg, Delta, or Hudi. This includes implementing Medallion architectures to govern data ingestion, transformation, and consumption processes. Establish comprehensive frameworks for data quality, observability, lineage, and service-level agreements (SLA), guaranteeing reliability and auditability of data at scale. Design secure REST and metadata APIs to facilitate governed data access and seamless integration with downstream applications. Collaborate closely with cross-functional product, architecture, and business teams, providing technical leadership through design reviews, mentoring, and contributions to the platform roadmap. Expertise in designing and implementing metadata-driven ETL/ELT pipelines and robust data ingestion and validation frameworks. Skilled in optimizing distributed Spark workloads, storage layouts, and schema evolution within lakehouse environments. Proficient with enterprise orchestration tools such as Autosys or Airflow; able to operate production-grade data pipelines meeting SLAs with effective alerting. Strong knowledge of data modeling, API development, and CI/CD or infrastructure automation processes. Familiarity with major cloud platforms, data governance tools, and secure engineering best practices. Preferred: Experience with financial data, risk or treasury systems, and large-scale migration programs. Applying GenAI for metadata extraction, data anomaly detection, automated documentation, or pipeline optimization. Job Expectations: Deliver high-quality engineering outcomes during Data Center exit migrations and DPC onboarding, ensuring validations, automation, and production readiness. Collaborate with cross-functional teams to build scalable, high‑performance data solutions using Python, SQL, Spark, Iceberg. Drive framework modernization initiatives and migration to metadata-driven DPC architectures, ensuring reusability, scalability, and governance. Build and maintain robust RESTful services (FastAPI/Flask) to support data frameworks and workflows, ensuring maintainability and performance. Mentor junior engineers and enforce engineering best practices across both development and deployment lifecycles. Good to have: Experience deploying applications and data platforms into Kubernetes/OpenShift (OCP) environments, including containerization and orchestration best practices.

Qualifications

- 5+ years of Software Engineering experience, or equivalent demonstrated through one or a combination of the following: work experience, training, military experience, education.
- Lead lakehouse engineering efforts by utilizing open table formats such as Iceberg, Delta, or Hudi.
- This includes implementing Medallion architectures to govern data ingestion, transformation, and consumption processes.
- Establish comprehensive frameworks for data quality, observability, lineage, and service-level agreements (SLA), guaranteeing reliability and auditability of data at scale.
- Design secure REST and metadata APIs to facilitate governed data access and seamless integration with downstream applications.
- Collaborate closely with cross-functional product, architecture, and business teams, providing technical leadership through design reviews, mentoring, and contributions to the platform roadmap.
- Expertise in designing and implementing metadata-driven ETL/ELT pipelines and robust data ingestion and validation frameworks.
- Skilled in optimizing distributed Spark workloads, storage layouts, and schema evolution within lakehouse environments.
- Proficient with enterprise orchestration tools such as Autosys or Airflow; able to operate production-grade data pipelines meeting SLAs with effective alerting.
- Strong knowledge of data modeling, API development, and CI/CD or infrastructure automation processes.
- Familiarity with major cloud platforms, data governance tools, and secure engineering best practices.
- Preferred: Experience with financial data, risk or treasury systems, and large-scale migration programs.
- Applying GenAI for metadata extraction, data anomaly detection, automated documentation, or pipeline optimization.
- Job Expectations: Deliver high-quality engineering outcomes during Data Center exit migrations and DPC onboarding, ensuring validations, automation, and production readiness.
- Collaborate with cross-functional teams to build scalable, high‑performance data solutions using Python, SQL, Spark, Iceberg.
- Drive framework modernization initiatives and migration to metadata-driven DPC architectures, ensuring reusability, scalability, and governance.
- Build and maintain robust RESTful services (FastAPI/Flask) to support data frameworks and workflows, ensuring maintainability and performance.
- Mentor junior engineers and enforce engineering best practices across both development and deployment lifecycles.
- Good to have:
- Experience deploying applications and data platforms into Kubernetes/OpenShift (OCP) environments, including containerization and orchestration best practices.

Responsibilities

- Lead complex technology initiatives including those that are companywide with broad impact.
- Act as a key participant in developing standards and companywide best practices for engineering complex and large scale technology solutions for technology engineering disciplines.
- Design, code, test, debug, and document for projects and programs.
- Review and analyze complex, large-scale technology solutions for tactical and strategic business objectives, enterprise technological environment, and technical challenges that require in-depth evaluation of multiple factors, including intangibles or unprecedented technical factors.
- Make decisions in developing standard and companywide best practices for engineering and technology solutions requiring understanding of industry best practices and new technologies, influencing and leading technology team to meet deliverables and drive new initiatives.
- Collaborate and consult with key technical experts, senior technology team, and external industry groups to resolve complex technical issues and achieve goals.
- Lead projects, teams, or serve as a peer mentor.

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