Lead I - Data Engineering- Azure

Responsibilities

• Maintain foundational knowledge of upstream data, including knowledge provided through data profiling, data quality reporting, and via the production of metadata.
• Supports the acquisition and ingestion of data.
• Articulates technical design and development details to non-technical business partners.
• Elicits, analyzes, and understands business and data requirements to develop complete business solutions under the guidance of senior peers and managers, including data models (entity relationship diagrams, dimensional data models), ETL and business rules, data life-cycle management, governance, lineage, and metadata.
• Ensures data is maintained in compliance with enterprise data standards, policies, and guidelines.
• Develops and maintains data models using industry standard modeling tools.
• Develops and maintains ETL jobs using the Banks standard tools.
• Provides support to the development and testing teams to resolve data issues.
• Supports partners and stakeholders in interpreting and analyzing data.
• Builds effective working relationships to collaborate with peers and partners on personal deliverables.
• Provides data governance and availability support.
• Supports the QA team with any data loads and data analysis/investigations as part of SIT/UAT/PAT testing.
• Provides post implementation support to the production support team during the warranty period.
• Executes code check-in/ check-out into source code repository as part of source code management.
• Works closely with ITS/ ARE teams to support code packaging deployment (CI CD) into higher environments.
• Is an active participant in the design architecture reviews of the application.
• Raises service-now requests and works with the change management team to support release management activities.
• Understands data engineering initiatives and capabilities, data governance principles and how they apply across the organization.
• Ensures metadata and data lineage is captured and compatible with enterprise metadata and data management tools and processes.

Technology Stack

• Azure - Azure Databricks, Unity Catalog, Delta Live Tables, Azure Data Factory, Azure Data
• ASP Connectors - TIBCO, OnPrem SQL, SharePoint, SharedFolders
• DevOps - Strong Infrastructure and Azure Release Engineer skills
• Language - Python, PySpark
• Banking domain experience strongly desired

Experience

• Azure Devops - 5+ Years
• Unity Catalog - 2 Years
• Azure Data Bricks - 5+ Years
• Azure Data Factory - 5+ Years

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