Data Pipeline Developer, Assistant Vice President

Do you want your voice heard and your actions to count? Discover your opportunity with Mitsubishi UFJ Financial Group (MUFG), one of the world’s leading financial groups. Across the globe, we’re 150,000 colleagues, striving to make a difference for every client, organization, and community we serve. We stand for our values, building long‑term relationships, serving society, and fostering shared and sustainable growth for a better world.

With a vision to be the world’s most trusted financial group, it’s part of our culture to put people first, listen to new and diverse ideas and collaborate toward greater innovation, speed and agility. ThisMAG means investing in talent, technologies, and tools that empower you to own your career.

Join MUFG, where being inspired is expected and making a meaningful impact is rewarded.

The selected colleague will work at an MUFG office or client sites four days per week and work remotely one day. A member of our recruitment team will provide more details.

Base pay range: $110,000 – $134,000 per year.

The Enterprise Data Pipeline team in Technology is focused on a transformative journey that will support our data strategy, on how we develop and deliver critical business outcomes. Our team is seeking an experienced and dynamic individual to join as Assistant Vice President, Data Pipeline Developer, to support projects and BAU work efforts. The successful candidate must be able to deliver while adopting an agile methodology and managing project timelines and risks.

The role involves significant interaction with colleagues outside

RK the immediate Data services team, including all lines of business (Global Corporate & Investment Banking, Finance, Risk, Compliance, Chief Data Office, Information Technology), Product Owners, and Data owners. Role involves global stakeholder base with interaction across time zones.

• Work with data architects, data/systems analysts, and business users to understand business requirements, business rules, and outcomes.
• Function as data and integration SME, supplying business and technical knowledge on required subject areas and systems.
• Conduct impact analysis.
• Document, develop, test, implement, monitor, maintain, and support enterprise data solutions.
• Document, develop, test, implement, and maintain complex ETL/ELT mappings, workflows, and scripts based on architecture, requirements, mappings, technical specifications, and otherيجة documentation.
• Investigate, troubleshoot, and resolve failures, data and other issues proactively and preemptively where possible.
• Ensure security, scalability, maintainability, and supportability of solutions.
• Meet or exceed data quality and integrity standards.
• Perform and support DUT/SIT/UAT/DR/regression testing activities.
• Handle user inquiries and production support.
• Create and maintain project Wied, design, data flow, technical, how‑to, and other required documentation.
• Recommend and follow best practices, standards, processes, and procedures.

• Degree in Computer Science, Software Engineering, Data Science, Information Technology, Information Systems, or a related field.
• 5+ years of hands‑on experience with complex, large‑scale dataorgot warehouse and data Pipeline projects.
• 3+ years of experience with Data Lake Infrastructure, Data Warehousing, and Data Analytics tools.
• 3+ years of experience implementing cloud platformstimeout (like AWS, Snowflake).
• 3+ years of experience in SQL optimization and performance tuning, and development experience in programming languages like Python, PySpark, Scala.
• Experience implementing cloud‑based data solutions using AWS services (EC2, S3, EKS, Lambda, API Gateway, Glue) and big data tools (Spark, EMR, Hadoop).
• Hands‑on experience in data profiling, data modeling, and data engineering using databases (Snowflake, Red Shift, DB2, Oracle, SQL Server), ETL tools (Informaticaлижית IICS), and scripting languages (Python).
• 2+ years’ experience with job/workflow management tools (Autosys) and other pipeline orchestration tools.
• Hands‑on experience with data domains such as loans, deposits, trade finance, markets, investment banking, transaction…