Data Engineer Associate Payment Operations

As a Data Domain Architect, you will play a crucial role in driving solutions and strategies related to data within the organization. Your responsibilities will include: - Defining data (metadata), identifying systems of record and authoritative sources, creating data quality rules, data flow diagrams, and applying firm-wide standards and controls. - Creating conceptual and logical models to describe specific data domains, informing the physical design of data-related projects, and consulting enterprise and industry models. - Profiling, wrangling, and preparing data from various sources to support analytical efforts, including writing data transformation logic in languages like Python, SAS, or Scala. - Conducting business process analysis, identifying necessary data to support processes, and evaluating the suitability of requested data for specific processes. - Engaging in research and development with emerging technologies, assessing their relevance to business use cases, and documenting their recommended applications within the organization. - Collaborating with Tech, Product, and CIB data partners to research, define, and implement use cases, working closely with data analytics and data product owner staff to optimize solutions and drive innovation. Qualifications and skills required for this role: - 3+ years of relevant work experience in software development, data/ML engineering, data science, or business intelligence. - Bachelor's degree in Computer Science, Financial Engineering, MIS, Mathematics, Statistics, or another quantitative field. - Strong analytical thinking, problem-solving abilities, and effective communication skills to convey complex information to diverse audiences. - Experience or knowledge in data technologies such as data warehousing, ETL, data quality concepts, Business Intelligence tools, analytical tools, unstructured data, or machine learning. - Proficiency in relational database systems like Teradata and Oracle, with advanced SQL skills. - Knowledge and hands-on experience with cloud platforms like Databricks or Snowflake. - Hands-on experience with data modeling, proficiency in SQL, SAS, or Scala, Python languages, and understanding of advanced statistics. - Development of domain expertise within the data architecture domain.,