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Mitsubishi UFG

Global banking, trust, asset management, securities.

Data Services Delivery - Assistant Vice President

Data Engineering +1Confirmed live in the last 24 hours
Full-timeBengaluru, Karnataka, IndiaNo salary listedIn-person

About the Job

Requirements

  • A bachelor's degree or foreign equivalent in Information Technology, Information Systems, Computer Science, Software Engineering, or a related field.
  • At least 8 years of experience leading the design, development, and optimization of dashboards and reports using Power BI, Tableau, and other reporting platforms.
  • At least 5 years of experience integrating BI tools with data warehouses or data lakes, such as Snowflake, and strong knowledge of data modelling and user experience/user interface for dashboards.
  • At least 3 years of experience migrating reports from legacy platforms.
  • At least 5 years of proficiency in AWS services, including AWS Glue, Redshift, EMR, RDS, Kinesis, S3, Athena, DynamoDB, Step Functions, and Lambda.
  • At least 2 years of expertise in data pipelines associated with modern data platforms such as Snowflake.
  • At least 4 years of hands-on experience with AI-assisted engineering tools such as GitHub Copilot or similar platforms, including practical understanding of how they improve development, documentation, testing, and automation workflows.
  • At least 2 years of experience with Agentic AI concepts, prompt engineering, large language models, retrieval-augmented generation, AI governance, and responsible AI adoption in enterprise technology environments.
  • Excellent communication and collaboration skills, with the ability to work effectively in a team environment.
  • Knowledge of banking and financial services products such as loans, deposits, and foreign exchange.
  • Proficiency in data warehousing, data lake and data mesh concepts, data modelling, databases, data governance, data security/protection, and data access.
  • Experience with Power BI Desktop and Service; Tableau Desktop, Server, Online, and Prep; data modelling including star and snowflake schemas, composite models, row-level security, and data blending; AWS cloud technology including Redshift, S3, Athena, EMR, HiveQL, Glue, and RDS; and databases including SQL Server and Oracle.

Responsibilities

  • Manage data analysis and data integration across disparate systems.
  • Create a semantic layer for data virtualization connecting heterogeneous data repositories.
  • Develop reports and dashboards using Tableau, Power BI, or similar business intelligence tools as assigned.
  • Assist the Data Management Engineering Team in data pipelines engineering or data service and data access engineering, including extract, transform, and load or business intelligence design and related framework work.
  • Work with business users to translate functional specifications into technical designs for implementation and deployment.
  • Extract, transform, and load large volumes of structured and unstructured data from various sources into AWS data lakes or modern data platforms such as Snowflake.
  • Use GitHub Copilot and AI-assisted development tools to improve productivity, code quality, documentation, and testing efficiency.
  • Design and implement AI-enabled automation solutions, including Agentic AI frameworks, to improve data engineering, reporting, and operational processes.
  • Assist with data quality controls as assigned.
  • Work with cross-functional team members to develop prototypes, produce design artifacts, develop components, perform and support system integration testing and user acceptance testing, and triage and fix bugs.
  • Resolve issues and defects in a timely manner and ensure quality deliverables.
  • Optimize the data integration platform for performance as data volumes increase.
  • Develop data integration standards according to organizational information services policies and best practices.
  • Review other integration developers’ work to ensure consistent methodologies and recommend improvements where necessary.
  • Work with Agile teams and JIRA.
  • Ensure data integration systems deliver high quality and optimum performance to meet business solutions.

Desired Qualifications

  • Experience in the financial services industry.
  • Exposure to data virtualization tools such as Starburst, Dremio, or Denodo.
  • Familiarity with data mesh and data fabric.
  • Familiarity with data governance, data security, and compliance practices in cloud environments.
  • AWS, Snowflake, Power BI, or Tableau certifications.
  • Knowledge of operational/MIS reports, risk reporting, and regulatory reporting for a U.S. bank.
  • Knowledge of DAX.

About the Company

Mitsubishi UFG

Global banking, trust, asset management, securities.

MUFG is a large financial services group formed in 2005 by merging Mitsubishi Tokyo Financial Group and UFJ Holdings. It provides a wide range of services, including commercial banking, trust banking, securities, credit cards, and asset management, through a global network of banks, trust banks, securities firms, and asset management subsidiaries. Its products work by offering loans and deposits, investment products, payment services, and financial advisory to individuals, businesses, and institutions via branches, digital platforms, and partnerships. The company differentiates itself with its size and global reach, a diversified mix of financial offerings, and strategic international investments (notably the 2008 stake in Morgan Stanley) that expand its US and global presence. MUFG’s goal is to support economic growth worldwide by providing comprehensive financial solutions and pursuing sustainable finance and innovation.

Company size
10,001+
Company stage
IPO
Headquarters
Tokyo, Japan
Founded
2006

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