DATA MANAGEMENT ENGINEER – Full Stack

DATA MANAGEMENT ENGINEER – Full Stack At BNY, our culture allows us to run our company better and enables employees’ growth and success. As a leading global financial services company at the heart of the global financial system, we influence nearly 20% of the world’s investible assets. Every day, our teams harness cutting-edge AI and breakthrough technologies to collaborate with clients, driving transformative solutions that redefine industries and uplift communities worldwide. Recognized as a top destination for innovators and champions of inclusion, BNY is where bold ideas meet advanced technology and exceptional talent. Together, we power the future of finance – and this is what #LifeAtBNY is all about. Join us and be part of something extraordinary. We’re seeking a future team member for the role of Vice President, Data Management Engineer to join our Finance Platform’s Client Profitability Engineering   team. This role is in Pittsburgh, PA. In this role, you’ll make an impact in the following ways:  Translate business requirements into ETL/ELT logical models, ensuring data structures are designed for scalability and flexibility to support evolving business solutions. Develop and implement robust data pipelines using Spark. Design and code programs, create test transactions and write documentation that describes installation and operating procedures. Define and deliver reusable components within the ETL/ELT framework. Establish optimal data flows for system integration and data migration. Integrate emerging data management technologies and software engineering tools into existing architectures. Apply security and privacy principles. Design, construct, and maintain CI/CD pipelines across multiple integration and test environments. Install, configure, and manage automated testing tools within the environment. Utilize AI based development / vibe coding (e.g. Windsurf, Codex) and techniques to develop solutions Knowledge and experience building agents and agentic solutions. Participate in deployment process following all change controls. Provide ongoing maintenance, support and enhancements in existing systems and platforms. Provide recommendations for continuous improvement. Work alongside other engineers on the team to elevate technology and consistently apply best practices. Collaborate closely with all the other members of the team to take shared responsibility for the overall efforts that the team commits to. Collaborate cross-functionally with full-stack engineers, business users, project managers and other engineers to achieve elegant solutions.   To be successful in this role, we’re seeking the following:  Proven experience in the design, development, and implementation of large-scale projects within financial industries, utilizing Data Warehousing ETL tools (including Spark). Bachelor's degree in computer science engineering or a related discipline, or equivalent work experience required2-6 years of experience in software development required; experience in the securities or financial services industry is a plus Proficient in creating ETL transformations and jobs with Spark and automating workflows through orchestration tools such as Airflow and Control-M. In-depth knowledge and hands-on experience with SQL, Python, Java, Spark and reporting tools like Power Bi.  Oracle, Snowflake, SQL Server or any other relational database experience necessary.  Familiarity with Big Data and distributed frameworks including Spark, Kubernetes, Hadoop, and Hive. Experience working with APIs to create, test and manage APIs for inter-process communication. Adopt AI-first software development practices. Experience leveraging AI tools (e.g., GitHub Copilot, Cursor, Windsurf, or similar LLM-based assistants) to accelerate daily development tasks such as code generation, debugging, code review, building unit tests and documentation. Ability to design ETL/ELT solutions tailored to user reporting and archival needs.