Associate Delivery Manager

Job Purpose

The Associate Delivery Manager Data Architect plays a dual role combining technical leadership in data architecture with project delivery management. This role is responsible for designing and governing enterprise-wide data solutions while ensuring projects are delivered on time, within scope, and with high quality. The position bridges the gap between business goals, data management strategies, and technology solutions, working closely with technical teams, business stakeholders, and project managers.

Duties and Responsibilities

- Define, design, and maintain enterprise data architecture frameworks, standards, and principles.
- Develop scalable data models, integration patterns, and architecture blueprints to support business requirements.
- Manage end-to-end delivery of data projects, ensuring alignment with enterprise strategies, deadlines, and budget constraints.
- Collaborate with business analysts, data engineers, data scientists, and solution architects to translate business needs into technical data solutions.
- Ensure the security, quality, and compliance of all data assets with organizational governance policies.
- Lead architecture reviews and solution design sessions to ensure adherence to best practices.
- Monitor project progress, identify risks/issues, and implement mitigation plans.
- Manage project resources and ensure effective communication with stakeholders.
- Stay updated with emerging technologies and trends in data architecture and delivery methodologies (Agile, Scrum, Kanban).
- Drive innovation in data platforms, cloud adoption, and data-as-a-service initiatives.
- Stay up to date with the latest industry trends and technologies in data engineering and recommend innovative solutions.
- Create and maintain comprehensive documentation for all developed data pipelines and systems.
- Mentor junior data engineers and contribute to the development of best practices.

Key Decisions / Dimensions

- Define technical data architecture standards, tools, and technologies to be adopted.
- Prioritize project deliverables and allocate resources based on business impact and urgency.
- Approve technical designs and solution architectures for data platforms.
- Make trade-offs between technical debt and delivery speed to balance long-term architecture stability with project timelines.

Major Challenges

- Balancing delivery timelines with the need for robust and scalable data architecture.
- Managing stakeholder expectations from both business and technical domains.
- Dealing with legacy systems while introducing modern, scalable data technologies.
- Ensuring data security, privacy, and compliance in rapidly evolving regulatory landscapes.
- Handling complex integrations across diverse platforms and heterogeneous data sources.

Required Qualifications and Experience

a)Qualifications

- Bachelors Degree in Computer Engineering, Computer Science, Information Technology, or a related discipline.
- A Masters degree in a related field is an advantage.
- Professional certifications such as Azure Certified Solutions Architect, Google Professional Cloud Architect, TOGAF, or DAMA Certified Data Management Professional (CDMP) are desirable.

b)Work Experience
- 6+ years of experience in data architecture, solution design, and/or enterprise architecture.
- 2-3 years of experience managing technical project deliveries or acting in a delivery lead capacity.
- Strong expertise in data modeling (conceptual, logical, physical), data integration, and ETL design.
- Proficiency with cloud-based data services (AWS, Azure, GCP) and modern data architectures (data lake, lakehouse, data mesh).
- Deep understanding of relational databases, NoSQL, big data platforms (Hadoop, Spark), and real-time data processing.
- Experience with Agile methodologies and project management frameworks (Scrum, Kanban).
- Strong leadership, stakeholder management, and problem-solving skills.

c)Skills Keywords
- Data Architecture
- Delivery Management
- Project Management
- Cloud Data Platforms (e.g., Azure, AWS, GCP)
- Data Modeling
- Data Governance
- Stakeholder Management
- Quality Assurance
- Agile Methodology
- Team Leadership
- Budget Management
- Risk Management
- Data Integration

Scalable Data Solutions