You are a strategic thinker passionate about driving solutions in Data Domain Architect
.
You have found the right team. As a Vice President in Data Domain Architect, where youll play a strategic role in the rapidly evolving Payments Operations industry. This role offers the opportunity to provide data architecture leadership and strategy within the Strategy, Innovation & Digitization Data team. Youll collaborate closely with product, analytics, and technology teams, making this role perfect for a motivated team member with a passion for data and problem-solving.
As a Data Engineer Associate Payment Operations within the Payments Operations organization, you will be responsible for providing data architecture leadership and strategy, and solutions data engineering use cases focused on data analytics, metrics and insights across Payments Operations. This role is ideal for a highly motivated team member with a strong passion for data, problem solving, and domain knowledge as well as strong interpersonal and communication skills.
Job responsibilities
- Facilitate requirements definition, design, testing, and implementation of new data delivery and analytic capabilities that address specific business needs for Payments Operations.
- Define data (metadata), identify systems of record and authoritative sources, create data quality rules, create data flow diagrams, and apply firm-wide standards and controls.
- Create conceptual and logical models to describe a particular domain of data and use these models to inform the physical design of data-related projects; consult enterprise and industry models.
- Profile, wrangle, and prepare data from diverse sources to support analytical efforts; write data transformation logic in languages such as Python, SAS, or Scala.
- Conduct business process analysis and identify data needed to support the processes. Determine whether the requested data is fit for use within a given process.
- Conduct research and development with emerging technologies, determine their applicability to business use cases, document & communicate their recommended use in the firm.
- Work with Tech, Product, and CIB data partners to research, define, and implement use cases.
- Collaborate closely with data analytics and data product owner staff across our team to understand requirements and partner to optimize solutions and develop/foster new ideas.
Required qualifications, capabilities and skills
- Accumulate 3+ years of relevant work experience as a software developer, data/ML engineer, data scientist, or business intelligence engineer.
- Hold a minimum of a Bachelor s degree in Computer Science, Financial Engineering, MIS, Mathematics, Statistics, or another quantitative subject.
- Exhibit analytical thinking and problem-solving skills coupled with the ability to understand business requirements and communicate complex information effectively to broad audiences.
- Experience in at least one data technology, such as data warehousing, ETL, data quality concepts, Business Intelligence tools, analytical tools, unstructured data, or machine learning.
- Utilize common relational database systems, such as Teradata and Oracle, with strong SQL skills.
- Hands-on experience in cloud platform with Databricks or Snowflake.
You are a strategic thinker passionate about driving solutions in Data Domain Architect
.
You have found the right team. As a Vice President in Data Domain Architect, where youll play a strategic role in the rapidly evolving Payments Operations industry. This role offers the opportunity to provide data architecture leadership and strategy within the Strategy, Innovation & Digitization Data team. Youll collaborate closely with product, analytics, and technology teams, making this role perfect for a motivated team member with a passion for data and problem-solving.
As a Data Engineer Associate Payment Operations within the Payments Operations organization, you will be responsible for providing data architecture leadership and strategy, and solutions data engineering use cases focused on data analytics, metrics and insights across Payments Operations. This role is ideal for a highly motivated team member with a strong passion for data, problem solving, and domain knowledge as well as strong interpersonal and communication skills.
Job responsibilities
- Facilitate requirements definition, design, testing, and implementation of new data delivery and analytic capabilities that address specific business needs for Payments Operations.
- Define data (metadata), identify systems of record and authoritative sources, create data quality rules, create data flow diagrams, and apply firm-wide standards and controls.
- Create conceptual and logical models to describe a particular domain of data and use these models to inform the physical design of data-related projects; consult enterprise and industry models.
- Profile, wrangle, and prepare data from diverse sources to support analytical efforts; write data transformation logic in languages such as Python, SAS, or Scala.
- Conduct business process analysis and identify data needed to support the processes. Determine whether the requested data is fit for use within a given process.
- Conduct research and development with emerging technologies, determine their applicability to business use cases, document & communicate their recommended use in the firm.
- Work with Tech, Product, and CIB data partners to research, define, and implement use cases.
- Collaborate closely with data analytics and data product owner staff across our team to understand requirements and partner to optimize solutions and develop/foster new ideas.
Required qualifications, capabilities and skills
- Accumulate 3+ years of relevant work experience as a software developer, data/ML engineer, data scientist, or business intelligence engineer.
- Hold a minimum of a Bachelor s degree in Computer Science, Financial Engineering, MIS, Mathematics, Statistics, or another quantitative subject.
- Exhibit analytical thinking and problem-solving skills coupled with the ability to understand business requirements and communicate complex information effectively to broad audiences.
- Experience in at least one data technology, such as data warehousing, ETL, data quality concepts, Business Intelligence tools, analytical tools, unstructured data, or machine learning.
- Utilize common relational database systems, such as Teradata and Oracle, with strong SQL skills.
- Hands-on experience in cloud platform with Databricks or Snowflake.
