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MUFG · 2 days ago

Data Integration Lead (Snowflake, Databricks), Vice President

Tampa, FL

Full-time

Hybrid

Senior Level, Lead/Staff

$133K/yr - $164K/yr

8+ years exp

Mitsubishi UFJ Financial Group (MUFG) is one of the world’s leading financial groups, and they are seeking a Vice President, Data Integration Lead. The role involves supporting projects and BAU work efforts, managing project timelines and risks, and developing data-driven solutions while collaborating with various business lines and stakeholders.

Financial Services

Responsibilities

Develop and maintain strong, trust-based relationships with key stakeholders to understand their business challenges and identify data-driven solutions

Develop and maintain data infrastructure, pipelines, and solutions, leveraging data engineering expertise

Design and deploy automated solutions for building, testing, monitoring, and deploying ETL data pipelines in a continuous integration environment

Design, build, and launch advanced data models and visualizations to support multiple use cases across various products or domains

Conceive, design, and implement Cloud Data Lakes, Data Warehouses, Data Marts, and Data APIs

Complete the full lifecycle of ETL/ELT development, including design, mappings, data transformations, scheduling, and testing

Apply knowledge of data engineering concepts, including data APIs, data availability, data quality, data management, metadata management, reference data management, data governance, data catalog, data virtualization, and data optimization

Utilize data tools and platforms such as Starburst, Snowflake, Databricks, and programming languages like SQL, Python, and Shell Scripting

Manage batch job operations using Autosys, perform data modeling (physical and logical), and utilize data catalog tools (e.g., Collibra)

Implement data governance, quality standards, and best practices to ensure data accuracy and security

Troubleshoot and optimize data processing workflows, reduce latency and enhance the scalability of data systems

Collaborate on Data Strategy and Solutions

Ensure compliance with data privacy and security regulations, employing best practices for data handling and storage

Build and maintain data dictionaries and process documentation

Qualification

Data Lake InfrastructureData WarehousingSnowflakeDatabricksSQL optimizationPythonAWS servicesETL toolsData modelingAutosysData governanceAgile developmentGitJiraConfluencePower BITableau

Required

8+ years of hands-on experience in data science with a focus on developing and implementing data-driven solutions in the Banking & Financial Services sector

5+ years of experience with Data Lake Infrastructure, Data Warehousing, and Data Analytics tools

3+ years of experience in Implementation of cloud platforms like Snowflake, Databricks, S3, Redshift

3+ years of experience in SQL optimization and performance tuning, and development experience in programming languages like Python, PySpark, Scala etc.)

Experience in 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, RedShift, DB2, Oracle, SQL Server), ETL tools (Informatica IICS), and scripting languages (Python)

5+ years experience with job/workflow management tools (Autosys) and other pipeline orchestration tools

Experience with source control tools like Git and CI/CD practices

Experience architecting end-to-end data pipelines with both cloud and on-premises stacks

Experience building/operating highly available, distributed systems of data extraction, ingestion, and processing of large data sets

Understanding of metadata management, data lineage, and data glossaries is a plus

Working knowledge of agile development, including DevOps and DataOps concepts

Understanding of serverless architectures (eg. AWS Lambda)

Experience in Jira, Confluence, MS office