Data Architect/Modeler

Responsibilities: 
Contribute to the strategy and architecture for managing the enterprise’s data:
Ensure technology solutions are in alignment with data architecture principles and target state;
Evaluate and recommend emerging technologies for data management, storage and analytics;
Manage data governance and data quality best practices:
Create and maintain current- and target-state data architectures;
Define and manage standards, guidelines and processes to ensure data quality; 
Collaborate with business and IT stakeholders to ensure data architectures address business and IT objectives:
Work with IT teams, business analysts and data teams to understand data consumers’ needs and develop solutions;
Define and manage data needs and data movement between systems;
Collaborate with domain architects to develop the data model;
Provide technical leadership and strategic direction for the technologies, standards, processes and architectures for data across the enterprise:
Direct the design, development, implementation and maintenance of complex data systems and solutions;
Drive end-to-end data life cycle management activities;
Develop conceptual, logical and physical data models to support data analysis and operational data store:
Create data model for the data domains for the enterprise;
Define logical and physical schema for the operational data store;
Define query by pattern concepts to design the containers in the operational data store;
Develop the patterns for data synchronization from the source system to operational data store;
Establish mechanism for reconciliation and recovery of the data.
Required Skills:
draw.io and ER modeling tools like ER/Studio, Erwin.
File Formats : XML, JSON, AVRO, Fixed width, Delimiter Files.
NOSQL technologies like Amazon DynamoDB and MongoDB.
Traditional DB's: Oracle, SQL Server, DB2.
Search Platforms: Amazon OpenSearch, Elasticsearch or Solr.
Nice to Have:
APIs, Streaming Platforms e.g. Kafka, RabbitMQ.