Data Engineer/Big Data Engineer

Must have skills:
1. draw.io nd ER modeling tools like ER/Studio, Erwin
2. File Formats : XML, JSON, AVRO, Fixed width, Delimiter Files
3. NOSQL technologies like Amazon DynamoDB and MongoDB
4. Traditional DB's: Oracle, SQL Server, DB2
5. Search Platforms: Amazon OpenSearch, Elasticsearch or Solr
6. APIs, Streaming Platforms e.g. Kafka, RabbitMQ

I will be looking on resume for the required skills: draw.io , ER Studio (might be written like ER/Studio), ERWIN, and Kafka

Job Description:

Role and 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;

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