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 Seniority level

Mid-Senior level Employment type

Full-time Job function

Information Technology Industries

Higher Education

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