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iLink DigitalPosted 6 months ago

Data Engineer (ETL ODI) - AMS

On-siteBengaluru, Karnataka, India

Full TimeSenior LevelMedium

Job Summary

Design, develop, and maintain functions and stored procedures using Oracle Data Integrator (ODI). Create and document data warehouse schemas, including fact and dimension tables, based on business requirements. Develop and execute SQL scripts for table creation and collaborate with Database Administrators (DBAs) for deployment. Analyze various data sources to identify relationships and align them with Business Requirements Documentation (BRD). Design and implement Extract, Load, Transform (ELT) processes to load data from source systems into staging and target environments. Validate and profile data using Structured Query Language (SQL) and other analytical tools to ensure data accuracy and completeness. Apply best practices in data governance, including query optimization, metadata management, and data quality monitoring. Utilize Python to automate data collection from APIs, enhancing integration workflows and enabling real-time data ingestion. Investigate and resolve data quality issues through detailed analysis and root cause identification. Communicate effectively with stakeholders through strong written, verbal, and analytical skills.

Required Qualifications

  • over 5 years of experience in designing and developing data solutions
  • strong expertise in data modeling
  • ETL/ELT processes
  • SQL
  • exposure to Python scripting for API-based data ingestion
  • Oracle Data Integrator (ODI)
  • Design, develop, and maintain functions and stored procedures using Oracle Data Integrator (ODI)
  • Create and document data warehouse schemas, including fact and dimension tables
  • Develop and execute SQL scripts for table creation
  • collaborate with Database Administrators (DBAs) for deployment
  • Analyze various data sources to identify relationships and align them with Business Requirements Documentation (BRD)
  • Design and implement Extract, Load, Transform (ELT) processes to load data from source systems into staging and target environments
  • Validate and profile data using Structured Query Language (SQL) and other analytical tools
  • Apply best practices in data governance, including query optimization, metadata management, and data quality monitoring
  • Demonstrate strong data modeling skills to support scalable and efficient data architecture
  • Utilize Python to automate data collection from APIs
  • Investigate and resolve data quality issues through detailed analysis and root cause identification
  • Communicate effectively with stakeholders through strong written, verbal, and analytical skills
  • Exhibit excellent problem-solving and research capabilities in a fast-paced, data-driven environment

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