Lead Software Engineer

• 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

• 5+ years of Software Engineering experience, or equivalent demonstrated through one or a combination of the following: work experience, training, military experience, education
• 4+ years of 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
• Experience architecting pipelines using distributed systems patterns (shuffle optimization, spill, broadcast, storage layouts)
• Experience with streaming frameworks like Spark Structured Streaming or Apache Flink
• Hands‑on with optimization techniques: clustering, Z‑ordering, vectorized IO (Parquet/ORC), compaction
• Experience implementing Medallion architectures and governed ingestion zones
• 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
• 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)
• Applying GenAI for metadata extraction, data anomaly detection, automated documentation, or pipeline optimization
• Exposure to financial risk, treasury functions, or Collateral Management processes

Exposure to financial risk, treasury functions, or Collateral Management processes