Bangkok, Thailand
123 days ago
Data Engineer (DT)

Educational

Background in programming, databases and/or big data technologies OR​ BS/MS in software engineering, computer science, economics or other engineering fields


Responsibility

Partner with Data Architect and Data Integration Engineer to enhance/maintain optimal data pipeline architecture aligned to published standards​ Assemble medium, complex data sets that meet functional /non-functional business requirements​ Design and implement internal process improvements: automating manual processes, optimizing data delivery, re-designing infrastructure for greater scalability, etc.​ Build the infrastructure required for optimal extraction transformation, and loading of data from a wide variety of data sources ‘big data’ technologies Build analytics tools that utilize the data pipeline to provide actionable insights into customer acquisition, operational efficiency and other key business performance metrics​ Work with stakeholders including Domain leads, and Teams to assist with data-related technical issues and support their data infrastructure needs​ Ensure technology footprint adheres to data security policies and procedures related to encryption, obfuscation and role based access​ Create data tools for analytics and data scientist team members ​


Functional Competency 

Knowledge of data and analytics framework supporting data lakes, warehouses, marts, reporting, etc​ Defining data retention policies, monitoring performance and advising any necessary infrastructure changes based on functional and non-functional requirements​ In depth knowledge of data engineering discipline​ Extensive experience working with Big Data tools and building data solutions for advanced analytics Minimum of 5+ years' hands-on experience with a strong data background​ Solid programming skills in Java, Python and SQL​ Clear hands-on experience with  database systems - Hadoop ecosystem, Cloud technologies (e.g. AWS, Azure, Google), in-memory database systems (e.g. HANA, Hazel cast, etc) and other database systems - traditional RDBMS (e.g. Teradata, SQL Server, Oracle), and NoSQL databases (e.g. Cassandra, MongoDB, DynamoDB)​ Practical knowledge across data extraction and transformation tools - traditional ETL tools (e.g. Informatica, Ab Initio, Altryx) as well as more recent big data tools

Educational

Background in programming, databases and/or big data technologies OR​ BS/MS in software engineering, computer science, economics or other engineering fields


Responsibility

Partner with Data Architect and Data Integration Engineer to enhance/maintain optimal data pipeline architecture aligned to published standards​ Assemble medium, complex data sets that meet functional /non-functional business requirements​ Design and implement internal process improvements: automating manual processes, optimizing data delivery, re-designing infrastructure for greater scalability, etc.​ Build the infrastructure required for optimal extraction transformation, and loading of data from a wide variety of data sources ‘big data’ technologies Build analytics tools that utilize the data pipeline to provide actionable insights into customer acquisition, operational efficiency and other key business performance metrics​ Work with stakeholders including Domain leads, and Teams to assist with data-related technical issues and support their data infrastructure needs​ Ensure technology footprint adheres to data security policies and procedures related to encryption, obfuscation and role based access​ Create data tools for analytics and data scientist team members ​


Functional Competency 

Knowledge of data and analytics framework supporting data lakes, warehouses, marts, reporting, etc​ Defining data retention policies, monitoring performance and advising any necessary infrastructure changes based on functional and non-functional requirements​ In depth knowledge of data engineering discipline​ Extensive experience working with Big Data tools and building data solutions for advanced analytics Minimum of 5+ years' hands-on experience with a strong data background​ Solid programming skills in Java, Python and SQL​ Clear hands-on experience with  database systems - Hadoop ecosystem, Cloud technologies (e.g. AWS, Azure, Google), in-memory database systems (e.g. HANA, Hazel cast, etc) and other database systems - traditional RDBMS (e.g. Teradata, SQL Server, Oracle), and NoSQL databases (e.g. Cassandra, MongoDB, DynamoDB)​ Practical knowledge across data extraction and transformation tools - traditional ETL tools (e.g. Informatica, Ab Initio, Altryx) as well as more recent big data tools
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