Multiple roles and capabilities in data ecosystem
Understanding of the teams, its needs and purpose are crucial to achieve operational excellence. Based on the operating model, the responsibilities are also shifting.
Please see below what is the motivation, needs and most common misalignments between these teams within the Data ecosystem.
As centralised operating model is one of the most common, we will provide the observations based on it.
Roles and responsibilities in Data ecosystem
Business / end-users
This category of stakeholders includes a variety of roles such as sponsors, decision-makers, internal and external users. These are the stakeholders who drive business requirements, make strategic decisions, and ultimately use the data and insights provided by the data ecosystem to achieve business outcomes. They are essential for identifying the impact, tracking value, and ensuring that data solutions meet their needs..
Data & AI teams
It is at the core of the data and AI initiatives. It includes roles such as data engineers, data analysts, data scientists, and project managers. The Data & AI team is responsible for developing data solutions, maintaining data quality, performing data analysis, and building AI/ML models. They work to turn raw data into actionable insights and are instrumental in driving the intelligence layer of the data ecosystem. The team can split into: AI team, BI & Analytics team, data management team.
"Ops" team in data ecosystem
It ensures the data ecosystem runs smoothly. This includes solution architects, DevOps engineers, and change managers who are responsible for the deployment, monitoring, and maintenance of data solutions. They handle the ongoing operational aspects, ensuring the systems are up and running, performing optimally, and that any changes are managed effectively. They also ensure the growth of data and AI literacy through trainings.
Governance team
the team is tasked with overseeing data governance and ensuring compliance with policies and regulations. They manage the standards for data quality, security, privacy, and usage. This team usually consists of a data governance leader, data stewards, and business domain subject matter experts (SMEs). Their role is crucial in establishing the trust framework that allows data to be used confidently and responsibly within the organization.
Cloud platform team
they manage the cloud infrastructure that underpins the data ecosystem. Cloud engineers and architects design, implement, and maintain the cloud environment, ensuring it is secure, scalable, and cost-efficient. They work closely with the Data & AI team and the Operations team to provide the necessary platform services for data storage, processing, and analytics.
IT system owners
system owners are responsible for the source systems that generate and store data. They ensure that these systems are fit for purpose, meet performance requirements, and are aligned with business needs. They are key players in managing the lifecycle of the systems and the data within them, from creation to retirement..
How to Start Building Capabilities for Your Data Ecosystem?
Begin by mapping the existing competencies within your organization and identifying key business priorities (e.g., reporting automation, data integration, AI implementation). Based on these needs, define the minimum viable team compositions - such as a data analyst + business owner + technical expert—who can jointly initiate the development of the data platform and simple use cases.
In the next stages, grow your teams around specific capability areas:
- Data & AI – hire a data engineer or upskill internal talent.
- Operations & DevOps – ensure solutions are scalable and stable.
- Governance & Security – appoint someone responsible for data quality and compliance.
- usiness – identify leaders who will own the use cases and source systems.
tart small (e.g., with one department or one key report), but with a clear vision for scaling the data ecosystem based on real needs and insights gained during the initial months.
People are the heart of data ecosystem
Would you like to build capabilities for data ecosystem? Contact us!