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Job Description
- Gather requirements from business users, communicate status updates, and coordinate user acceptance testing and issue management
- Perform early stage analysis of Data integration and modeling requests to formulate high level approach and estimates
- Analyze user requirements to design data integration specifications and production reports
- Contribute to the ongoing development and improvement of ETL processes and standards
- Design, implement and support a system that can provide ad-hoc access to large datasets
- Model data and metadata to support ad-hoc
- Own the design, development, and maintenance of ongoing data integration processes, Data warehouse jobs, etc. to drive key business decisions
- Recognize and adopt best practices in developing and analysis: data integrity, test design, analysis, validation, and documentation
- Learning and understanding a broad range of Different customer data resources and know how, when, and which to use
- Deadlines and service levels Autonomous thinking and proactive approach to investigating and discovering solutions Excellent communicator and very transparent
- providing timely updates to supervisor for project tasks and deadlines Work Environment Requirements:
- Willing and able to travel to customer projects Ability to work in multicultural environment is a plus.
- Ability to multi-task with a variety of customers and projects Education.
- Analyze ETL Logic SQL and implement changes to optimize job performance
- Analytical thinking and problem-solving abilities Cooperative attitude towards team collaborations Ability to commit to customer milestones
- Drive reporting improvement and automation and create new innovative and insightful reports in a timely manner
- Extracting data using PL.SQL, SQL, Redshift, Teradata, Bigdata ecosystem, GreenPlum, Unix and other technologies. Analysing data using suitable tools (e.g., Excel, Tableau, Power BI, R, Python, SAP BI…etc.)
- Dealing with UNIX/Linux (Redhat, Solaris, HP-UX) scripting and environment.
Job Requirements
- Bachelor’s degree in a quantitative and analytical discipline
- Advanced SQL and experience in optimizing SQL queries
- Experience in data mining (SQL, ETL, data warehouse, etc.) and using databases in a business environment with large-scale, and complex datasets
- Knowledge of development methodologies (Agile, Kanban, Waterfall, SCRUM etc)
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