Data Architect

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.