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.