Data Architect

Responsibilities of the Role

• Subject matter expertise in technologies (TD, HD, BDA, R, Python) and Data Management
• Understand and deliver data modeling requirements – physical and logical data modeling
• Drive data quality enhancements at scale to solve business problems in a prioritized manner
• Build and support data flow integration between different products increasing the capabilities of our product and expanding its use across the firm
• Ability to understand and deliver client requirements end to end for reference data and data lake aligned use cases
• Ensure proper risk management process is adhered too, to mitigate risk exposure for the firm

Hard Skills / Requirements

Technology Infrastructure (HW, SW & Applications hosted) Expertise

• Ability to understand in depth how technology products are delivered as per requirement

Strong Data Architecture experience

• Advanced understanding of reference data, data lake, and other information system solutions
• Experience integrated multiple systems together to create an intelligent and resilient information system solution
• Ability to use industry standard tools to create logical and physical data models for technology infrastructure and reference data

Information System Design

• Experience delivering or supporting information systems using extract, translate, load (ETL) and publishing methods
• Understanding the right technical solution to represent the data appropriately to meet the client requirement
• Experience with performance tuning of information systems (e.g. streamlining ETLs to run faster)

Data Quality Experience

• Understanding the core concepts of data quality–how to measure improve
• Understanding what data quality issues pose the greatest risks to the Maybank operations and raising those to governance effectively

Functional Skills:

Must Have (Experience in any of the areas):

• Data Mining. Data modelling, Data Standards
• Data Lineage, Masking, Encrypt/Decrypt
• Data Quality Score Cards, Data Management, Data Governance
• Dashboards, Visualization Scorecards, Sharepoint

Good to have (Experience in any of the areas):

• Data Warehousing (5 years)
• Big Data (4 years)
• Master Data Management, Reference Data Management (4 years)
• Worked as SI/Sa in Financial domain (6 years)

Technical Skills:

Must Have (Certified in anyone of the below but should have multiple skillset):

• R, Python
• Teradata
• Hadoop-Cloudera
• ETL/ELT Tools - Trillium, informatica (Any data Modelling or data profiling tools)
• Data Visualization Tools (Oracle DV, Denodo, Clairvoyant, OEDQ, Paxata)
• Cloud (AWS, Azure, GCP)
• OS - Scripting (Any OS)

Good to have (Experience in any of the following):

• Pig, MapReduce, Hive, Hbase
• Big Data Integration, Ingestation Framework (4 yeras)
• Data Lab, Data Lake (4 years)
• ITIL, TOGAF (any one)