SCOPE & AUTHORITY
Data Architecture:
- Execute Enterprise data initiatives / programs to establish a governed, curated, and agile data ecosystem that enables business to make data-driven decisions.
- Translate strategic requirements into a usable Enterprise information architecture (e.g. enterprise data model, associated metamodel, common business vocabulary, and naming taxonomy, etc.).
- Develop and maintain architecture artifacts, frameworks, and patterns as references for the development teams across the Group.
- Deliver tangible Data & AI solutions, Choosing the right technology, evaluating architecture evolution as well as being capable of creating and maintaining architecture using leading Data & AI technology frameworks
- Participate in key transformational project design reviews as part of the methodology process to ensure application designs adhere to enterprise information architecture guidelines.
- Monitor regulatory guidelines such as consumer privacy laws, data retention policies, outsourced data, and specific industry guidelines to determine impact on the enterprise information architecture.
- Provide capability assessment tool on Data Management & Governance in all Dimensions of Data Management adhering to DMBOK V2.
- Establish and monitor the operations of the data governance organization across the Group.
- Drive the implementation of corrective measures to ensure data governance policies and procedures are followed.
- Publish data reference architecture, data architecture principles, best practices, and design patterns to enable data engineering teams to build scalable and resilient platforms.
- Exploring new technology trends and leveraging on it in order to simplify our data eco-system (e.g. development of architectures, strategies, and policies around data governance, including master data management, metadata management, data quality and data profiling).
Data Management (Regulatory & Compliance):
Requirements
Academic Qualification:
• Bachelor's degree in computer science, computer engineering, electrical engineering, systems analysis or a related field of study
• Min 8 years of experience architecting, designing and developing large scale data solutions utilizing a mixture of Big Data and Relational database platforms. Data/information modeling expertise at the enterprise level Space, NLTK
Skills Required:
• Requires advance knowledge of Big Data analysis and data management tools to be able to recommend and provide industry best practices.
• You will drive end to end data solutions and data management strategy across data and analytics platforms.
• Enterprise scale expertise in data analysis, modelling, data security, data warehousing, metadata management and data quality.
• Extensive knowledge and experience in architecting modern data ingestion frameworks, highly scalable distributed systems using open source and emerging data architecture patterns.
• Data/information modelling expertise at the enterprise level
• Experience with Master Data Management, Metadata Management, and Data Quality tools, Data Security and Privacy methods and frameworks
- Hands on experience in Data Management Lifecycle, Data Modelling and Data Governance
- Experience with Hadoop clusters, in memory processing, GPGPU processing and parallel distributed computing systems
- Experience building data pipelines using Kafka, Flume, and accelerated Stream processing - Deep understanding of Apache Hadoop 1/2 and the Hadoop ecosystem. Experience with one or more relevant tools (Sqoop, Flume, Kafka, Oozie, Hue, Zookeeper, HCatalog, Solr, Avro).
- Good knowledge of Elastic search and Solr
- Experience in designing NoSql, HDFS, Hive, HBASE datamarts and creating data lakes - Familiarity with one or more SQL-on-Hadoop technology (Hive, Pig, Impala, Spark SQL, Presto)
- At least 10 years of experience with data warehouse design for RDBMS such as for Oracle, MS SQL, PostgreSQL and MySQL – Can incorporate with above
- Experience with Service Oriented Architecture (SOA), web services, enterprise data management, information security, applications development, and cloud-based architectures
- Experience with enterprise data management technologies, including database platforms, ETL tools such as Talend/Pentaho (developing Spark ETL jobs), and SQL.
- Experience in languages like Java, PHP, Python and/or R on Linux OS. – JavaScript, Scala and Windows OS
- Experience in implementing machine-learning solutions, development in multiple languages and statistical analysis. He/she will also need to be familiar with a whole host of other approaches used in practical applications of machine learning.
- Experience in AI Integration, Natural Language Processing and AI Application Programming
- Experience with Telecommunications, IoT, Data visualization and GIS projects - Current hands-on implementation experience required
- Database Administrator with big data project and TOGAF certification will be an advantage
- Customer facing skills to represent Big Data Architectures well within the opco environments and drive discussions with senior personnel regarding trade-offs, best practices, project management and risk mitigation.
• Collaborate with Opco’s Analytics, data science and full stack team to ensure structured and unstructured data capturing and ingestion as per design requirements
• Work with Axiata’s IT and security architects to ensure compliance with data security and privacy policy
• Manage and lead end-to end data lifecycle management activities and ensure consistency/quality/availability between data management – More of Data Engineers role
• Excellent communication skills and ability to convey complex topics through effective documentation as well as presentation.
