Data Management Engineer - Full Stack

Salary: $30,000 - 55,000 per year Requirements: Proven experience designing, developing, and implementing large-scale projects in the financial industry using data warehousing ETL tools, including Spark. Bachelors degree in computer science, engineering, or a related discipline, or equivalent work experience; 2–6 years of software development experience required. Securities or financial services experience is a plus. Proficiency creating ETL transformations and jobs with Spark and automating workflows using orchestration tools such as Airflow and Control-M. Hands-on knowledge of SQL, Python, Java, Spark, and reporting tools such as Power BI. Experience with Oracle, Snowflake, SQL Server, or another relational database. Familiarity with big data and distributed frameworks, including Spark, Kubernetes, Hadoop, and Hive. Experience working with APIs for inter-process communication, including creating, testing, and managing APIs. Ability to adopt AI-first software development practices and use AI coding assistants to support code generation, debugging, reviews, unit tests, and documentation. Ability to design ETL/ELT solutions for user reporting and archival needs. Commitment to excellent customer service and addressing client requirements effectively. Self-motivated and able to work independently with minimal supervision. Comprehensive experience building and managing CI/CD pipelines. Basic understanding of Azure Cloud components. Strong problem-solving skills and an interest in designing scalable solutions. Experience applying best practices in design, development, testing, and release management. Understanding of monitoring tools such as AppDynamics, Splunk, and Moogsoft. Responsibilities: Translate business requirements into scalable, flexible ETL/ELT logical models that support evolving solutions. Develop robust data pipelines using Spark; design and code programs, create test transactions, and document installation and operating procedures. Define and deliver reusable components for the ETL/ELT framework. Establish effective data flows for system integration and data migration. Incorporate emerging data management technologies and software engineering tools into existing architectures while applying security and privacy principles. Design, build, and maintain CI/CD pipelines across integration and test environments. Install, configure, and manage automated testing tools. Use AI-based development tools and techniques, including tools such as Windsurf and Codex, to develop solutions. Build agents and agentic solutions. Participate in deployments in accordance with change controls; maintain, support, and enhance existing systems and platforms, and recommend improvements. Work with fellow engineers to advance technology and consistently apply best practices. Share responsibility with the team for delivering committed work. Collaborate with full-stack engineers, business users, project managers, and other engineers to develop effective solutions. Technologies: AI Airflow Azure Big Data CI/CD Cloud ETL Hadoop Hive Support Java Kubernetes Oracle Power BI Python SQL Security Snowflake Spark Splunk Windsurf Copilot Cursor GitHub LLM Fullstack More: We are partnering with hackajob to connect professionals with BNY for a Vice President, Data Management Engineer role on our Finance Platforms Client Profitability Engineering team in Pittsburgh, Pennsylvania. BNY is a global financial services company whose teams use AI and advanced technologies to work with clients and develop solutions across industries. We offer competitive compensation, benefits, and wellbeing programs, flexible global resources, generous paid leave, and paid volunteer time. BNY has been recognized among Fortunes Most Innovative Companies and Worlds Most Admired Companies, and by Just Capital and CNBC as one of the Most Just Companies in 2025. last updated 41 week of 2026