Director of Software Engineering
On-siteWilmington, Delaware, United States
Job Summary
Lead technology and process implementations to achieve functional objectives while directly managing multiple areas with a strategic transactional focus. Manage complex projects and large cross-product collaborations, setting direction and governance for agentic AI-enabled engineering and SDLC/TLM automation to drive measurable improvements in speed, quality, and operational outcomes. Establish guardrails for validation, security, resiliency, and traceability across teams, applying knowledge of the software development life cycle toolchain to improve value realized by automation. Make decisions influencing team resources, budget, and process execution, carrying governance accountability for coding decisions and portfolio operations. Deliver technical solutions leveraged across multiple businesses and domains while influencing peer leaders and senior stakeholders. Champion the firm's culture of diversity, opportunity, inclusion, and respect within Consumer & Community Banking.
Required Qualifications
- Formal training or certification on data management concepts
- 10+ years applied experience
- 5+ years of experience leading technologists to manage, anticipate and solve complex technical items within your domain of expertise
- Proven experience in designing and developing large scale data pipelines for batch & stream processing
- Strong understanding of Data Validation / Data Quality
- Strong understanding of Data Warehousing, Data Lake, ETL processes and experience in Big Data technologies (e.g Hadoop, Snowflake, Databricks, Apache Spark, PySpark, Airflow, Apache Kafka, Java, Open File & Table Formats, GIT, CI/CD pipelines etc.)
- Expertise with public cloud platforms (e.g., AWS, Azure, GCP) and modern data processing & engineering tools
- Excellent communication, presentation, and interpersonal skills
- Experience developing or leading large or cross-functional teams of technologists
- Strong understanding of responsible AI use and control expectations in engineering workflows, including data sensitivity, resiliency/security implications, and governance; ability to influence leaders on safe scaling patterns and reuse
- Experience leading adoption of agentic AI-enabled engineering practices (using enterprise-authorized tools within the work environment) across teams, including defining operating expectations (human-in-the-loop validation, quality gates), measuring outcomes, and ensuring secure handling of sensitive inputs/outputs
- Exhibit strong proficiency in Java or Python, with the ability to architect and build complex AI models from scratch. Ensure the delivery of secure, high-quality production code
- Extensive practical cloud native experience
- Experience working at code level and ability to be hands-on performing PoCs, code reviews
Desired Qualifications
- Experience in Data Modeling (ability to design Conceptual, Logical and Physical Models, ERDs and proficiency in data modeling software like ERwin)
- Experience with Data Governance, Data Privacy & Subject Rights, Data Quality & Data Security practices
- Experience in Data visualization & BI tools is a huge plus
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