Top tier investment bank is seeking VP Software Engineers to join their Dallas, TX teams. The experienced Engineer will contribute to designing common data-stores in the firm's enterprise data platform "Data Lake" and "Legend," given the nature of finance's complex and high volume data continuously needing to be scaled.
* Work in a dynamic, fast-paced environment that provides exposure to all areas of Finance
* Build strong relationships with business partners
* Understand business needs, facilitating and developing process workflow, data requirements, and specifications required to support implementation
* Develop technical specifications, high level/detailed design, testing strategies, and implementation plans from business requirements
* Manage end-to-end systems development cycle from requirements analysis, coding, testing, UAT and maintenance
* 6+ years of software development experience
* Bachelor's degree in Computer Science, Mathematics, Electrical Engineering or related technical discipline
* Independent thinker, willing to engage, challenge and learn
* Comfortable multi-tasking, managing multiple stakeholders and working as part of a team
* Excellent communication skills including experience speaking to technical and business audiences and working globally
* Expertise in Object Oriented (preferably Java) development & Relational databases
* Working knowledge of ORM (Object Relational Mapping) tools to create executable domain models
* In-depth knowledge of database technologies and design e.g. relational, columnar, hierarchal and document databases.
* Experience with financial products and workflows and the systems that support them.
* Knowledge of data analytics and visualization tools, e.g. Kibana, Tableau, Qlikview, etc.
* Experience with continuous delivery and deployment
* Proficient at working with large and complex code bases
* Comfortable working in highly dynamic and rapid development environment (Agile development experience)
* Technologies: Linux, TDD, build tools (Maven/Gradle/Ant), Hadoop/HDFS, Spark