Lead Data Architect

LEAD DATA ARCHITECT

WOOLWORTHS FINANCIAL SERVICES

OBSERVATORY

MAIN PURPOSE:

The primary role of the Lead Data Architect is to translate business requirements into usable cloud hosted information architecture which may include an enterprise data model, associated metadata, common business vocabulary, and taxonomies that are used to guide enterprise solution development and achieve consistency of information assets across the application portfolio. The Lead Data Architect must take business requirements, knowledge of current and future state BI technology platform design and business capabilities, knowledge of enterprise data standards, and deep data expertise into account to design data architecture solutions that can be implemented in a cost-effective manner. The specific tasks performed will include analysing business requirements and defining information systems data solutions to address complex business needs (projects are technically difficult, requiring innovative and creative solutions and frequently involve multiple platforms, software, hardware, technologies and tools).

KEY RESPONSIBILITIES:

Strategy & Planning

• Develop and deliver long-term strategic goals for cloud hosted data architecture vision and standards in conjunction with data users, department managers, clients, and other key stakeholders.
• Create short-term tactical solutions to achieve long-term objectives and an overall data management roadmap.
• Create end-to-end vision on how logical design translates into data lake and databases, and how the data will flow through the successive stages. 
• Establish methods and procedures for tracking data quality, completeness, redundancy, compliance and improvement.
• Assess and determine governance, stewardship, and frameworks for managing data across the enterprise.
• Create strategies and plans for data capacity planning, data security, life cycle data management, scalability, backup, disaster recovery, business continuity, and archiving.
• Ensure that data strategies and architectures are in regulatory compliance. Recognize and identify potential areas where existing policies and procedures require change, or where new ones are needed

Project Related Deliverables and Tasks

• Select and implement the appropriate tools, software, applications, and systems to support cloud data technology goals.
• Oversee the mapping of data sources, data movement, interfaces, and analytics, with the goal of ensuring data quality.
• Collaborate with project leads and consultants and business unit leaders for all projects involving enterprise data and analytics.
• Create and maintain data model and metadata policies and procedures for functional design
• Provide technical recommendations and engage with ETL/BI Architects, Business SMEs and other stakeholders throughout the Solution/Data Architecture and implementation lifecycle and recommend effective solutions to develop high performance and highly scalable data solutions (data marts/warehouse and data mining and advanced analytics)
• Address data-related problems in regards to systems integration, compatibility, and multiple-platform integration.
• Develop and implement key components as needed to create testing criteria in order to guarantee the fidelity and performance of data architecture.
• Document the project and programs data architecture and environment in order to maintain a current and accurate view of the larger data picture, an environment that supports a single version of the truth and is scalable to support future analytical needs
• Identify and develop opportunities for data reuse, migration, or retirement and platform upgrades.
• Communicate with customer, project team in a timely manner and escalates issues & risks appropriately.

Staff and Talent Management

• Develop a high performing team by embedding formal performance development, recognition and informal coaching. Encourage frequent knowledge sharing between team members;
• Leading and managing a team of Data Engineers.
• Coach team on how to plan for and perform successful BI analysis and documentation through various techniques;
• Evaluate and implement training and development needs for team;
• Provide authoritative advice and guidance to colleagues on any aspect of BI work as well as other development where appropriate;
• Maintain and improves BI roles and responsibilities within the BI portfolio; and
• Facilitate the creation of an environment whereby staff can motivate themselves and feel proud of the work

KEY COMPETENCIES

• Solid written and verbal communication skills and presentation skills
• Demonstrated ability to work in a fast paced and changing environment with short deadlines, interruptions, and multiple tasks/projects occurring simultaneously
• Must be able to work independently and have skills in planning, strategy, estimation, scheduling,
• Strong problem solving, influencing, communication, and presentation skills, self-starter
• Good interpersonal skills and ability to work both independently as well as in a team with a strong sense of responsibility, initiative and anticipation
• Customer and service oriented approach (ability to deal with demanding users)
• Analytical capability with attention to detail and a concern for accuracy 

MINIMUM QUALIFICATION

• Relevant formal B-degree qualification
• 8-10 years’ experience in IT systems and analysis

EXPERIENCE REQUIRED

• 10 years+ experience with analytical tools and Business Intelligence tools and visualization as well as prior experience with enterprise integration applications or techniques
• 5 years+ Experience in cloud computing infrastructure (e.g. Amazon Web Services EC2, Elastic MapReduce, S3, Redshift, Glue, Lamda etc) and considerations for scalable, distributed systems
• Experience in Data Lake and relational databases (RDB) and RDB design with the ability to create and read Entity Relationship diagrams
• 8 – 10 years’ experience delivering business capabilities for Financial Services including hands on experience in the development and design of functional and non-functional technical specifications for complex systems
• Deep knowledge of contemporary architectural principles across the data architectural domain
• Understanding of the enterprise architecture to ensure on-going alignment, driving the technical roadmap for key applications and platforms
• Knowledge of different SDLC Methodologies (Waterfall, Agile, etc)