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Job Description
Leads the Data Architects for the overall design and approach to designing both the logical and the physical data architecture of the data warehouse and data lake.
A Data Architecture Manager is a technical leadership role responsible for overseeing the creation and management of data architecture artifacts, including the delivery of data models and data mapping. This role also involves managing data design reviews and ensuring the successful completion of critical data-related projects. They excel in project management, stakeholder engagement, ensuring that data solutions align with business objectives. They prioritize the creation of design artifacts based on industry best practice, promotes talent development in data covering cross-functional teams, fostering a culture of data-centricity while optimizing workflows for efficiency.
The Data Architect is responsible for the overall design and the approach to designing both the logical and the physical data architecture of the data warehouse and data lake. The data architect should have a broad understanding of data warehousing, ETL, big data, cloud architecture and is responsible for providing technical leadership to the implementation teams
The responsibilities of this position will include but will not be limited to the following:
- Data modeling: The ability to design and create a conceptual, logical, and physical representation of data. These skills are crucial for organizing data effectively within a database. a data warehouse or a data lake, ensuring it's accurate, consistent, and easily accessible.
- Data mapping: A core part of data management that involve the ability to define relationships between data fields from different sources. This is crucial for ensuring that data remains accurate, consistent, and usable during processes like data migration, data integration, and data warehousing.
- Stakeholder Engagement: Collaborate with business stakeholders to understand their data requirements and ensure data solutions meet their needs.
- Process Improvement: Continuously improve data architecture experience and processes, implement sound practices, and optimize workflows for efficiency.
- Documentation Oversight: Ensure the maintenance of documentation, data dictionaries, metadata and data lineage within the team.
- Talent Development: Foster the professional growth of team members through mentoring, training, and skill development.
KPIs:
- Data Model Completeness: Measure the completeness of a design against the requirements.
- Design Review Success Rate: Assess efficient resource allocation
- Stakeholder Satisfaction: Evaluate stakeholder feedback on data solutions.
- Process Efficiency: Track improvements in data architecture processes.
- Budget Adherence: Ensure data-related projects stay within budget.
- Data Mapping accuracy rate: Measure the correctness of the logic implemented in the data design.
- Adherence to Data Governance Policies: The degree to which data models and processes comply with data governance policies, which can be measured by the number of policy exceptions or compliance violations.
TOP 3-5 DELIVERABLES:
- Design Accuracy, Efficiency, and Compliance: Correct and optimized design that supports business objectives and adheres to project budget while ensuring compliance with governance policies.
- Project Execution: Successful completion of data architecture projects within timelines and budgets.
- Stakeholder Alignment: Data solutions that meet business requirements.
- Process Optimization: Streamlined data architecture processes and workflows.
- Budget Oversight: Effective budget management for data-related initiatives.
SKILLS:
Soft Skills
- Excellent communication
- Excellent leadership
- Collaboration
Hard SKills
- Data Modeling
- Database Technologies
- Data Warehousing
- Data Integration
- Cloud Technologies
COMPETENCIES
- Data Design: Ability to create and review data models and mappings
- Stakeholder Engagement: Collaborative skills to engage with business stakeholders.
- Process Improvement: Expertise in optimizing data architecture processes and workflows.
HIRING REQUIREMENTS
Work Experience
- 5 to 10 years of experience in data architecture related work.
- Must have experience in designing and/or developing a mid - large scale data warehouse or data lake.
- Must have solid 3 years of experience in SQL and ETL / Reports development
- Experienced in implementing various Relational database, NoSQL, or Distributed Computing technologies
Level of Knowledge
- Should be knowledgeable on data warehousing implementation
- Should be proficient in data modeling for both operational systems and analytical systems
- Must be able to communicate effectively
- Should possess the ability to work independently with minimal supervision or with a team depending on the scenario.
- Knowledge on SDLC with emphasis on design phase or any other Agile methodologies
Education
- Bachelor's Degree preferably Information Technology or Computer Science.
Preferred
- Telecommunications industry knowledge and experience
- Should be knowledgeable on various Hadoop implementation strategies
- Related Technical Certification
Equal Opportunity Employer
Globe's hiring process promotes equal opportunity to applicants, Any form of discrimination is not tolerated throughout the entire employee lifecycle, including the hiring process such as in posting vacancies, selecting, and interviewing applicants.
Globe's Diversity, Equity and Inclusion Policy Commitment can be accessed
Make Your Passion Part of Your Profession. Attracting the best and brightest Talents is pivotal to our success. If you are ready to share our purpose of Creating a Globe of Good, explore opportunities with us.
