AVP-Data Visualization Specialist T500-16412
2 weeks ago
About Us: MUFG Bank, Ltd. is Japan's premier bank, with a global network spanning in more than 40 markets. Outside of Japan, the bank offers an extensive scope of commercial and investment banking products and services to businesses, governments, and individuals worldwide. MUFG Bank's parent, Mitsubishi UFJ Financial Group, Inc. (MUFG) is one of the world's leading financial groups. Headquartered in Tokyo and with over 360 years of history, the Group has about 120,000 employees and offers services including commercial banking, trust banking, securities, credit cards, consumer finance, asset management, and leasing. The Group aims to be the world's most trusted financial group through close collaboration among our operating companies and flexibly respond to all the financial needs of our customers, serving society, and fostering shared and sustainable growth for a better world. MUFG's shares trade on the Tokyo, Nagoya, and New York stock exchanges. MUFG Global Service Private Limited: Established in 2020, MUFG Global Service Private Limited (MGS) is 100% subsidiary of MUFG having offices in Bengaluru and Mumbai. MGS India has been set up as a Global Capability Centre / Centre of Excellence to provide support services across various functions such as IT, KYC/ AML, Credit, Operations etc. to MUFG Bank offices globally. MGS India has plans to significantly ramp-up its growth over the next 18-24 months while servicing MUFG's global network across Americas, EMEA and Asia Pacific About the Role: Position Title: Data Engineer or Data Visualization Analyst Corporate Title: AVP Reporting to: Vice President Job Profile Position details: Cloud Data Engineer with a strong technology background and hands-on experience working in an enterprise environment, designing, and implementing data warehouses, data lakes, and data marts for large financial institutions. Alternatively, Data Visualization Analyst with BI & Analytics experience with exposure to or experience in Data Engineering or Data Pipelines can be considered. In this role you will work with technology and business leads to build or enhance critical enterprise applications both on-prem and in the cloud (AWS) along with Modern Data Platform such as Snowflake and Data Virtualization tool such as Starburst. Successful candidates will possess in-depth knowledge of current and emerging technologies and demonstrate a passion for designing and building elegant solutions and for continuous self-improvement. Roles and Responsibilities: Manage data analysis and data integration of disparate systems Create a semantic layer for data virtualization that connects to heterogenous data repositories Develop reports and dashboards using Tableau, Power BI, or similar BI tools as assigned Assist Data Management Engineering team (either for Data Pipelines Engineering or Data Service & Data Access Engineering) for ETL or BI design and other framework related items 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. Assist with Data Quality Controls as assigned Work with cross functional team members to develop prototypes, produce design artifacts, develop components, perform, and support SIT and UAT testing, triaging and bug fixing. Optimize and fine-tune data pipelines jobs for performance and scalability. Implement data quality and data validation processes to ensure data accuracy and integrity. Provide problem-solving expertise and complex analysis of data to develop business intelligence integration designs. Convert physical data integration models and other design specifications to source code. Ensure high quality and optimum performance of data integration systems to meet business solutions. Job Requirements: Bachelors' Degree (or foreign equivalent degree) in Information Technology, Information Systems, Computer Science, Software Engineering, or a related field. Experience in the financial services or banking industry is preferred. 5+ Years of experience working as a Data Engineer, with a focus on building data pipelines and processing large datasets. AWS certifications on Data related specialties are a plus. Business Acumen – 15%: Knowledge of Banking & Financial Services Products (such as Loans, Deposits, Forex, etc.). Knowledge of Operational/MIS Reports, Risk and Regulatory Reporting for a US Bank is a plus. Data Skills – 25%: Must have proficiency in Data Warehousing concepts, Data Lake & Data Mesh concepts, Data Modeling, Databases, Data Governance, Data Security/Protection, and Data Access. Solid understanding of data modeling, database design, and ETL principles Familiarity with data governance, data security, and compliance practices in cloud environments. Tech Skills – 50%: 5+ Years of Expertise in Hive QL, Python programming, experience with Spark, Python, Scala and Spark for big data processing and analysis. 2+ Years of Strong proficiency in AWS services, including AWS Glue, Redshift, EMR, RDS, Kinesis, S3, Athena, DynamoDB, Step Functions and Lambda. 3+ years of experience with Data Visualization Tools such as Tableau or Power BI 2+ years of experience with ETL technologies such as Informatica Powercenter or SSIS coupled with most recent 2-3 years of cloud ETL technologies 2+ years of experience in dealing with data pipelines associated with modern data platforms such as Snowflake or Databricks Exposure to Data Virtualization tools such as Starburst or Denodo is a plus Strong problem-solving skills and the ability to optimize and fine-tune data pipelines and Spark jobs for performance. Experience working with data lakes, data warehouses, and distributed computing systems. Experience with Modern Data Stack and Cloud Technologies is a must. Human Skills – 10%: Excellent communication and collaboration skills, with the ability to work effectively in a team environment.
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