Our client, a reputable MNC Conglomerate, is looking for a Data Engineering Lead (AM Grade). The selected talent will be tasked designing the end-to-end real time data pipeline. Plan, design and implement the migration of the existing on-prem data warehouse to cloud infrastructure. TB-PB scale data sets. Perm opportunity.  

About the Role

• Design Customer Intelligence Platform architecture and implement the best practices of Data Analytic platform to enable customer data analytic and data-driven marketing automation with emerging technologies
• Collaborate with internal IT, Digital Team, various upstream & downstream system teams and external data management vendors to establish end-to-end data pipeline (real-time and batches) from data ingestion, transformation, data modelling to data visualization and utilization including but not limited to requirement gathering, data mapping, testing and trouble shooting
• Ensure the data and information are delivered on-time with high quality, good performance, reconciled and integrity assured Manage and maintain the existing on-premises data warehouse to support the BAU activities as well as ad-hoc data extraction and report generation to business users Implement the customer data single source of truth and automate the direct marketing subscription preference management between loyalty systems and marketing tools on BU and brand level
• Plan and implement source system data migration from legacy systems to new systems and/or data warehouse Plan, design and implement the migration of the existing on-premises data warehouse to Cloud infrastructure;
• Establish data lake to enable a flexible and effective analytic platform to fulfil tagging data analytics, extended customer insights, real time behaviour analytics, personalization and data feeding among different digital touchpoints
• Document the data architecture and pipeline including but not limit to data dictionary, pipeline design and mapping, transformation logic, real-time/batch control and monitoring and data flow between systems

Requirements

• University graduate in Information Technology, Computer Science, Information System, Information Management or related discipline
• Minimum 5 years’ working experience in data infrastructure and architecture with demonstrated experience and capability in Data warehousing, data modelling and design, data integration, data migration, ETL, BI and Big data solutions skill sets
• Experience in leading a small team of data engineers/ETL developers and vendor management Strong in SQL, Python/R
• Experience with traditional DWH such as Teradata, Oracle, DB2, Sybase, MS SQL Server
• Experience with batch and real-time streaming technologies such as DataStage, Informatica, Spark, EMR, HDInsight, Kinesis, Kafka Experience with or knowledge of cloud platforms such as Azure, AWS and Google Cloud Platform
• Experience with or knowledge of cloud Data Lake, DWH and query engine such as Azure (Data Lake Store & BLOB, SQL DW), AWS (S3, Redshift, Athena), Databricks and Presto Experience with or knowledge of data catalog, data lineage, BI and Data Preparation (Tableau, Qlik, Power BI, Tableau Prep, Alteryx, Looker) is highly desirable
• Excellence presentation and communication skills; strong analytical, problem-solving and interpersonal skill
• Good command of both written and spoken English, Cantonese and Mandarin

ST Partnership

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