Database Administrator

Responsibilities

• Evaluate DB features and related products.
• Expert knowledge in MS SQL, PostgreSQL and Oracle PL / SQL database (relational & NoSQL), Windows / UNIX scripting, and Java.
• Design, building and manage Database warehouse.
• Familiar with end-to-end supply chain and associated eco-systems and ability to architect and implement strategic recommendations
• Engage with the business and other IT teams to understand the strategies and requirements to conceptualize possible architectural alternatives
• Evaluate architectural alternatives with the business and IT and select the desirable alternatives for the business and platform
• Leverage best practices and solutions across regions, businesses and Logistics and Transportation platforms
• Incorporate organization and best practices in the architectural design
• Follow project management methodology and ensure the timely delivery of architectural designs
• Work without day-to-day supervision.
• Establish and maintain sound backup and recovery policies and procedures.
• Database design and implementation.
• Implement and maintain database security.
• Perform database tuning and performance monitoring.
• Setup and maintain documentation and standards.
• Work as part of a team and provide 24x7 support when required.
• Perform technical trouble shooting and give consultation to development teams.
• Interface with Oracle and Microsoft for technical support.
• Patch Management and Version Control.
• Installation, configuration and upgrading of Oracle server software and related products.
• Preparing datasets and building models for machine learning and other AI-driven processes.
• Experience in building ETL / ELT pipelines for data ingestion and transformation.
• Strong skills in SQL for data manipulation (DML), definition (DDL), and control (DCL) are essential for managing and querying data within the warehouse.
• The ability to analyze data and create reports or dashboards to provide actionable insights to business users.
• Ensuring the accuracy, consistency, and reliability of data within the warehouse through various cleansing processes.
• Discovering patterns and insights from large datasets within the data warehouse.
• Familiarity with big data technologies
• Proficiency in Python (Pandas, PySpark, Airflow).
• Knowledge of shell scripting for automation tasks.
• Understanding of APIs (REST, GraphQL) for data integration.
• Experience with data warehouses
• Understanding of data lakes and lakehouse architectures
• Hands-on experience with cloud platforms

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