Data Integration Lead, VP

MUFG•Jersey City, NJ

4d•$158,000 - $205,000•Hybrid

About The Position

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 Vice President, Data Integration Lead, 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 of 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 a global stakeholder base with interaction across time zones.

Requirements

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.
Working knowledge of agile development, including DevOps and DataOps concepts.
Understanding of serverless architectures (e.g. AWS Lambda)
Experience in Jira, Confluence, MS office.
Demonstrates leadership
Communicate effectively
Identifies multiple paths to success using analytical and critical thinking as well as decision-making skills
Operates strategically to support a culture of continuous improvement and systems thinking
Makes sound business decisions in a complex work environment
Collaborate with other business functions and divisions to advance business objectives
Is flexible, decisive, and able to establish support from leadership
Monitors industry trends and best practices and applies insights to advance the business
Exhibits and fosters optimism, resilience, flexibility, and openness to others' ideas
Inspires innovation and values learning as a lifelong professional objective
Leads by example, engaging inclusively and with intent
Always act with integrity
Serving as a trusted advisor
Degree in Computer Science, Software Engineering, Data Science, Information Technology, Information Systems, or a related field.
Bachelor's degree in Computer Science or a closely-related discipline, or an equivalent combination of formal education and experience

Nice To Haves

Understanding of metadata management, data lineage, and data glossaries is a plus.
AWS Certification as Cloud Practitioner, Solutions Architect, Developer/Data Engineer.

Responsibilities

Develop and maintain strong, trust-based relationships with key stakeholders to understand their business challenges and identify data-driven solutions.
Build extensible data acquisition and integration solutions to meet the functional and non-functional requirements of the business.
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.
Conduct review of other integration developers’ development efforts to ensure consistent methodologies are followed and to make recommendations where necessary.
Work with business and technology users for code promotions, test data set up, test scenario set up, and proactive detection of problems through pre-built sanity checks
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.
Ensure compliance with data privacy and security regulations, employing the best practices for data handling and storage.
Build and maintain data dictionaries and process documentation.