Data Engineering
ripplehire
Job Description
- Maintain foundational knowledge of upstream data, including knowledge provided through data profiling, data quality reporting, and production of metadata.
- Support the acquisition and ingestion of data.
- Articulate technical design and development details to non-technical business partners.
- Elicit, analyze, and understand business and data requirements to develop complete business solutions under the guidance of senior peers and managers.
- Develop and maintain data models, including Entity Relationship Diagrams (ERDs) and Dimensional Data Models.
- Develop and maintain ETL jobs using the Bank's standard tools.
- Define and implement business rules, data life-cycle management, governance, lineage, and metadata requirements.
- Ensure data is maintained in compliance with enterprise data standards, policies, and guidelines.
- Develop and maintain data models using industry-standard modeling tools.
- Provide support to development and testing teams to resolve data issues.
- Support partners and stakeholders in interpreting and analyzing data.
- Build effective working relationships and collaborate with peers and partners on deliverables.
- Provide data governance and data availability support.
- Support the QA team with data loads and data analysis/investigations as part of SIT/UAT/PAT testing.
- Provide post-implementation support to the production support team during the warranty period.
- Execute code check-in/check-out into the source code repository as part of source code management.
- Work closely with ITS/ARE teams to support code packaging and deployment (CI/CD) into higher environments.
- Actively participate in design and architecture reviews of the application.
- Raise ServiceNow requests and work with the change management team to support release management activities.
- Understand data engineering initiatives and capabilities, data governance principles, and how they apply across the organization.
- Ensure metadata and data lineage are captured and compatible with enterprise metadata and data management tools and processes.