Occupation intelligence

chief data officer

Role lens

Data is the lifeblood of modern organizations, and the chief data officer (CDO) is responsible for ensuring it’s managed strategically. If you’re passionate about leveraging data to drive business decisions and building robust information systems, a career as a chief data officer could be a rewarding path.

Summary

As a chief data officer, you’ll be a key executive leader focused on the entire data lifecycle within a company. Your days will involve collaborating with various departments, from IT and marketing to finance and operations, to define data strategy, governance policies, and analytical capabilities. You’ll be responsible for ensuring data quality, security, and compliance, while also identifying opportunities to use data to improve business performance and gain a competitive advantage. This role requires a blend of technical expertise, business acumen, and strong leadership skills.

Key responsibilities:
  • • Developing and implementing a comprehensive data strategy aligned with business goals.
  • • Establishing and enforcing data governance policies and standards.
  • • Overseeing data quality management and ensuring data accuracy and reliability.
40%
Resilience Score · 2026 (Higher is better)
Master's or equivalent level 51% AI exposure
Start Career DNA assessment
Labour market

Where this occupation is in demand

Reported labour shortages and surpluses, by year. Published for occupation groups, not for individual job titles.

Shortage reportedSurplus reportedReported in another yearNot covered by this source

Deeper colour: reported the same way in more consecutive years.

Figures cover Production and specialised services managers — 186 jobs including this one.

7 of 11 in shortage202514 of 26 growing2.5Mopenings to 2035

In shortage: Belgium, Bulgaria, Cyprus, Czechia and 3 more.

Longest-running shortage: Belgium, 4 years.

Select a place on the map to see its figures.

About this source

Source: ELA/EURES labour shortages and surpluses. Readings are published at occupation-group level, and cover Europe. Editions differ in annex layout and country coverage, so a change between years does not always mean the labour market changed. Countries in grey were not reported, which is not the same as being in balance.

Explore More

Find your career path and explore the science behind our recommendations.

Guiding others? See NexPath for schools and practices.
Quick fit check

Could chief data officer fit you?

Answer three quick questions. This is not a full assessment — it is a teaser to help you decide whether to compare your profile.

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Do you enjoy tasks that require Integrity?

Do you enjoy tasks that require Dependability?

Do you enjoy tasks that require Relationships?

NexFuture™

Future Outlook for chief data officer

The outlook for chief data officer reflects a balanced mix of automation exposure and durable, human-led work.

How are these scores calculated?

The Resilience Score (0–100) estimates how structurally protected this occupation is from automation and AI disruption, based on task-level analysis. Higher scores mean more human-judgment-intensive tasks. AI Exposure shows the estimated percentage of task hours that current AI capabilities could affect. These are model-derived structural indicators, not predictions about individual job security.

Play the future

How could chief data officer change as AI adoption grows?

Several task areas may shift toward AI-assisted workflows, so reskilling becomes more important.

Significant task-level transformation is estimated in 12 years (around 2038) under the selected Expected Pace scenario.
~35%
Resilience
Automation Risk
EXP~55%
Human advantage
MOAT~40%

Illustrative scenario based on task automatability — not a forecast. Values are rounded the further ahead you look.

2026
2033
2043
AI Adoption Speed:

How AI may change this role

Deterministic, model-based interpretation of current role signals — not a guarantee of replacement.

Human-owned 40% Human-owned
What still depends on people
  • apply information security policies
  • define technology strategy
  • define data quality criteria
The Human Edge To stay ahead in this role, focus on data mining and data storage. These human-centric skills are the hardest for AI to replicate in the next 20 years.
Assist 28% Assist
Where AI may become a co-pilot
  • make data-driven decisions
  • utilise decision support system
  • manage ICT data architecture
Automate 51% Automate
Tasks most exposed to automation
  • manage ICT data classification
  • manage data
Detailed Analysis

Vital Signs & AI Vectors

AI Exposure Vectors

0-100%
AI / Machine Learning 28%

Exposure to AI-assisted analysis, pattern recognition, and predictive modelling tasks

Generative AI 6%

Exposure to content generation, creative augmentation, and large language model tools

Cognitive Software 3%

Exposure to workflow automation, decision-support software, and process digitisation

Robotic & Physical Automation 0%

Exposure to physical automation, robotics, and sensor-driven task displacement

Technical Details
Methodology: NexFuture v3.0 Sources: O*NET® 30.3, ESCO v1.2.1 Updated: Aug 2026

NexFuture v3.0 estimates automation exposure natively from ESCO essential-skill groups, weighted by skill mass and calibrated against expert anchors. Scores are probabilistic estimates, not guarantees. See the NexFuture Methodology White Paper for full details.

Measures automation exposure. It does not measure pay, demand, or how many jobs exist near you.

Day in the life

What people in this role usually do

Digital Technology

Day in the life

A typical day as a chief data officer

09
09:00 · Morning
define technology strategy
Create an overall plan of objectives, practices, principles and tactics related to the use of technologies within an organisation and describe the means to reach the objectives, taking into account analyses and relevant regulations.
10
10:30 · Mid-morning
apply information security policies
Implement policies, methods and regulations for data and information security in order to respect confidentiality, integrity and availability principles.
12
12:00 · Midday
define data quality criteria
Specify the criteria by which data quality is measured for business purposes, such as inconsistencies, incompleteness, usability for purpose and accuracy.
14
14:00 · Afternoon
manage data
Administer all types of data resources through their lifecycle by performing data profiling, parsing, standardisation, identity resolution, cleansing, enhancement and auditing. Ensure the data is fit for purpose, using specialised ICT tools to fulfil the data quality criteria.
15
15:30 · Late afternoon
manage ICT data architecture
Oversee regulations and use ICT techniques to define the information systems architecture and to control data gathering, storing, consolidation, arrangement and usage in an organisation.
17
17:00 · Wrap-up
manage ICT data classification
Oversee the classification system an organisation uses to organise its data. Assign an owner to each data concept or bulk of concepts and determine the value of each item of data.

Task order is illustrative. Individual days vary.

Software & Technologies & Knowledge areas
Software & Technologies
Adaptive Metadata ManagerAdeptia ETL SuiteAdvanced business application programming ABAPAltova MapForceAmazon DynamoDBAmazon Elastic Compute Cloud EC2Amazon RedshiftAmazon Simple Storage Service S3Amazon Web Services AWS softwareApache AvroApache CassandraApache FlumeApache HadoopApache HBaseApache HiveApache HTTP ServerApache KafkaApache OozieApache PigApache Solr
Knowledge areas
  • data mining

    The methods of artificial intelligence, machine learning, statistics and databases used to extract content from a dataset.

  • data storage

    The physical and technical concepts of how digital data storage is organised in specific schemes both locally, such as hard-drives and random-access memories (RAM) and remotely, via network, internet or cloud.

  • decision support systems

    The ICT systems that can be used to support business or organisational decision making.

  • information structure

    The type of infrastructure which defines the format of data: semi-structured, unstructured and structured.

  • visual presentation techniques

    The visual representation and interaction techniques, such as histograms, scatter plots, surface plots, tree maps and parallel coordinate plots, that can be used to present abstract numerical and non-numerical data, in order to reinforce the human understanding of this information.

  • CA Datacom/DB

    The computer program CA Datacom/DB is a tool for creating, updating and managing databases, currently developed by the software company CA Technologies.

Cross-sector skills
  • business processes
  • data ethics
  • data science
Essential skills
managing, gathering and storing digital data
  • manage ICT data classification

    Oversee the classification system an organisation uses to organise its data. Assign an owner to each data concept or bulk of concepts and determine the value of each item of data.

developing financial, business or marketing plans
  • define technology strategy

    Create an overall plan of objectives, practices, principles and tactics related to the use of technologies within an organisation and describe the means to reach the objectives, taking into account analyses and relevant regulations.

designing ict systems or applications
  • manage ICT data architecture

    Oversee regulations and use ICT techniques to define the information systems architecture and to control data gathering, storing, consolidation, arrangement and usage in an organisation.

developing operational policies and procedures
  • define data quality criteria

    Specify the criteria by which data quality is measured for business purposes, such as inconsistencies, incompleteness, usability for purpose and accuracy.

protecting privacy and personal data
  • apply information security policies

    Implement policies, methods and regulations for data and information security in order to respect confidentiality, integrity and availability principles.

managing information
  • manage data

    Administer all types of data resources through their lifecycle by performing data profiling, parsing, standardisation, identity resolution, cleansing, enhancement and auditing. Ensure the data is fit for purpose, using specialised ICT tools to fulfil the data quality criteria.

analysing business operations
  • make data-driven decisions

    Collect data such as Key Performance Indicators (KPIs) for an organisation and use the information to formulate actions and strategies.

using digital tools for collaboration and productivity
  • utilise decision support system

    Use the available ICT systems that can be used to support business or organisational decision making.

Skill DNA

Skill DNA

Work personality traits and values that define this role

Key traits you need
Integrity Dependability Self-Control Stress Tolerance Attention to Detail Cooperation Initiative Adaptability/Flexibility Independence Analytical Thinking Concern for Others Persistence Achievement/Effort Leadership Innovation Social Orientation
Key rewards you can expect
AchievementWorking Condit…RecognitionRelationshipsSupportIndependence
Career progression

Growth Pathways & Similar Roles

Explore typical career progression paths, adjacent skills, and similar roles to plan your next transition.

Career landscape

Where does chief data officer fit?

This role
chief data officer This role
Growth paths

Similarity scores based on skill overlap from ESCO data.

Common questions

Frequently asked questions

What kind of background is typically needed to become a chief data officer?
While a formal degree in data science or a related field is beneficial, experience is often more crucial. Many CDOs come from backgrounds in data management, business intelligence, analytics, or IT leadership roles. A strong understanding of both technology and business principles is essential.
How does the role of a CDO differ from a Chief Information Officer (CIO)?
The CIO typically focuses on the overall IT infrastructure and technology operations of a company. The CDO, however, has a narrower, more data-centric focus, ensuring data is treated as a strategic asset and used effectively across the organization. While there can be overlap, the CDO’s primary responsibility is data, while the CIO’s is broader technology.
What are the most important skills for a chief data officer to possess?
Beyond technical skills in data management and analytics, CDOs need strong leadership, communication, and stakeholder management abilities. The ability to translate complex data insights into understandable business recommendations is also vital, as is a strategic mindset focused on driving business value through data.
Chief Data Officer — is there a shortage in Europe?
Yes. In the 2025 ELA/EURES edition, a shortage was reported in 7 of the 11 European countries that assessed this occupation group: Belgium, Bulgaria, Cyprus, Czechia and 3 more. Belgium has reported one for 4 consecutive years. These assessments are published per occupation group rather than per job title.
Chief Data Officer — what does it pay in the United States?
$135,980 a year at the median, as of 2025-05. State medians run from $95,620 to $170,160. Source: US Bureau of Labor Statistics. This is a United States figure and not a projection for Europe.