Senior Software Engineer - Data Engineer (Python, SQL)

About this role: Wells Fargo is seeking a Senior Software Engineer. This is for Data Engineering to join the CALM (Corporate Asset and Liability Management) Data Engineering team within the Enterprise Functions Technology (EFT) organization. In this role, you will be responsible for designing, developing, optimizing, and maintaining metadata‑driven, scalable, high‑performance data engineering frameworks that power critical financial risk processes across Corporate Treasury. You will work independently to build resilient data pipelines, APIs, wrappers, and supporting components to enable reliable data ingestion, transformation, validation, and delivery across cloud and on‑prem ecosystems. This position plays a key role in Data Center exit migrations , DPC onboarding , and enterprise-wide modernization initiatives. The role requires deep technical expertise, hands‑on problem‑solving, and technical leadership in distributed data engineering, cloud platforms, data quality, and performance engineering. In this role, you will: Lead moderately complex initiatives and deliverables within technical domain environments Contribute to large scale planning of strategies Design, code, test, debug, and document for projects and programs associated with technology domain, including upgrades and deployments Review moderately complex technical challenges that require an in-depth evaluation of technologies and procedures Resolve moderately complex issues and lead a team to meet existing client needs or potential new clients needs while leveraging solid understanding of the function, policies, procedures, or compliance requirements Collaborate and consult with peers, colleagues, and mid-level managers to resolve technical challenges and achieve goals Lead projects and act as an escalation point, provide guidance and direction to less experienced staff Required Qualifications: 4+ years of Software Engineering experience, or equivalent demonstrated through one or a combination of the following: work experience, training, military experience, education Desired Qualifications: Strong years of Software Engineering experience OR equivalent (industry, training, military, education). Hands-on experience with Python , SQL , and bash scripting for automation. Strong experience building big data pipelines using Apache Spark, Hive, Hadoop. Experience with Autosys/Airflow or similar orchestration tools. Working knowledge of REST APIs , Object Storage , Dremio , and CI/CD pipelines. Strong troubleshooting and problem‑solving capabilities. Solid foundation in data modeling (conceptual/logical/physical) and database design. Platform & DevOps Cloud-native engineering experience — serverless, managed Spark, event-driven architectures. Familiarity with containerization (Docker, K8s) and workflow operators. Strong experience implementing test automation for data pipelines (unit, contract, integration tests). Data Lakehouse & Storage Hands‑on with optimization techniques: clustering, Z‑ordering, vectorized IO (Parquet/ORC), compaction. Experience implementing Medallion architectures and governed ingestion zones. Advanced Data Engineering Experience architecting pipelines using distributed systems patterns (shuffle optimization, spill, broadcast, storage layouts). Experience with streaming frameworks like Spark Structured Streaming or Apache Flink . Data Quality & Governance Knowledge of data governance platforms (Collibra, Alation, Purview). Understanding of financial data controls, validation rules, reconciliation checks, and compliance (SOX/PCI). Experience implementing lineage, observability, drift detection. GenAI for Data Engineering Applying GenAI for metadata extraction, data anomaly detection, automated documentation, or pipeline optimization. Domain Expertise Exposure to financial risk, treasury functions, or Asset & Liability Management (ALM) processes. Job Expectations: Deliver high-quality engineering outcomes during Data Center