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senior data engineer.

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    job details
    Accountabilities • Data Pipeline - Develop and maintain scalable data pipelines and builds out new API integrations to support continuing increases in data volume and complexity • Data Integration - Connect offline and online data to continuously improve overall understanding of customer behavior and journeys for personalization. Data pre-processing including collecting, parsing, managing, analyzing and visualizing large sets of data • Data Quality Management - Cleanse the data and improve data quality and readiness for analysis. Drive standards, define and implement/improve data governance strategies and enforce best practices to scale data analysis across platforms • Data Transformation - Processes data by cleansing data and transforming them to proper storage structure for the purpose of querying and analysis using ETL and ELT process • Data Enablement - Ensure data is accessible and useable to wider enterprise to enable a deeper and more timely understanding of operation  Qualifications & Specifications • Masters /Bachelor’s degree in Engineering /Computer Science/ Math/ Statistics or equivalent. • Strong programming skills in Python/R/SAS • Proven experience with large data sets and related technologies – SQL, NoSQL, Google / AWS Cloud, Hadoop, Hive, Spark • Excellent understanding of computer science fundamentals, data structures, and algorithms • Data pipeline software - Airflow, RJ Metrics, Segment, Amazon Data Pipeline, Apache Pig • ETL software’s - Amazon RedShift, CA Erwin Data Modeler, Oracle Warehouse Builder, SAS Data Integration Server, Pentaho Kettle, Apatar • Hands-on experience and knowledge of the Data Lake technology
    Accountabilities • Data Pipeline - Develop and maintain scalable data pipelines and builds out new API integrations to support continuing increases in data volume and complexity • Data Integration - Connect offline and online data to continuously improve overall understanding of customer behavior and journeys for personalization. Data pre-processing including collecting, parsing, managing, analyzing and visualizing large sets of data • Data Quality Management - Cleanse the data and improve data quality and readiness for analysis. Drive standards, define and implement/improve data governance strategies and enforce best practices to scale data analysis across platforms • Data Transformation - Processes data by cleansing data and transforming them to proper storage structure for the purpose of querying and analysis using ETL and ELT process • Data Enablement - Ensure data is accessible and useable to wider enterprise to enable a deeper and more timely understanding of operation  Qualifications & Specifications • Masters /Bachelor’s degree in Engineering /Computer Science/ Math/ Statistics or equivalent. • Strong programming skills in Python/R/SAS • Proven experience with large data sets and related technologies – SQL, NoSQL, Google / AWS Cloud, Hadoop, Hive, Spark • Excellent understanding of computer science fundamentals, data structures, and algorithms • Data pipeline software - Airflow, RJ Metrics, Segment, Amazon Data Pipeline, Apache Pig • ETL software’s - Amazon RedShift, CA Erwin Data Modeler, Oracle Warehouse Builder, SAS Data Integration Server, Pentaho Kettle, Apatar • Hands-on experience and knowledge of the Data Lake technology