The Data Engineer will develop, test and maintain data architecture, including databases and processing systems, to support a robust analytical pipeline that facilitates priority analytics use cases. The Data Engineer will ensure these data processing capabilities meet business requirements, use case and user needs while providing reliable, efficient and quality data.
- Adhere to processes to ensure data pulled from various sources meets quality standards, is curated and enhanced for analytical use and there is a “single source of truth”
- Work with counterparts from Tech to build frameworks that integrate data pipelines and machine learning models that facilitate use by data scientists for priority use cases; Enterprise Data and Analytics team focused on “last mile” transformations on select data required for use cases
- Implement the data models, standards and quality rules
- Maintain database structure and standard definitions for business users across Macy’s
- Work with Legal and Privacy teams to adhere to data privacy and security standards
- Work with data architects & senior data engineers to build the foundational extract / load / transform process
- Collaborate with Technology to future-proof data & analytics software, tools and code to reduce risk and support pipeline owners
- Collaborate with the Data Science team to understand data formatting and sourcing needs to enable them to build out use cases as efficiently as possible
- Ability to effectively share technical information, communicate technical issues and solutions to all levels of business.
- At least 1 year of experience in relational or dimensional data modeling.
- At least 2 years of experience with one of the following: Python, Scala, Java.
- Passionate about designing and developing elegant ETL/ELT pipelines and Frameworks.
- At least 2 years of overall experience in building ETL/ELT, data warehousing and big data solutions.
- Bachelor’s degree in Computer Science (or related technical field) or equivalent experience.
- Able to confidently express the benefits and constraints of technology solutions to technology partners, stakeholders and team members.
- Ability to work a flexible schedule based on department and Company needs.
- At least 1 years of experience in building data models and data pipelines to process different types of large datasets.
- Ability to think creatively, strategically and technically.
- Ability and desire to take product/project ownership.
- Experience in maintaining a data warehouse using Cloud Technologies such as AWS or GCP Services, and Cloud Data Warehouse preferably Google BigQuery.
- Experience implementing and supporting operational data stores, data warehouses, data marts, and data integration applications.
Vacancy Type: Full Time
Job Location: New York City Metropolitan Area, US
Application Deadline: N/A