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How to Hire First-Party Data Management and Analytics Talent

How to Hire First-Party Data Talent

In the rapidly evolving digital landscape, where data privacy concerns and regulatory changes are reshaping how businesses collect and utilize customer information, the significance of first-party data has skyrocketed. This transformation has catalyzed a burgeoning demand for specialized talent capable of harnessing the power of first-party data to drive strategic decisions and create personalized customer experiences.

Here, we explore the critical aspects of how to hire first-party data talent, with a specific focus on Chief Data Officer, delving into the growing demand for such expertise, the emergence of specialized roles dedicated to first-party data management, effective strategies for sourcing and attracting the right talent, and a strategic playbook to streamline your hiring process. 

First-party vs second-party vs third-party data 

In today’s data-centric business environment, first-party data stands as the cornerstone of customer-centric strategies and sustainable growth. With the advent of stringent privacy legislations such as GDPR in Europe and CCPA in California, combined with the decline of third-party cookies, companies are compelled to pivot towards more ethical and transparent data collection practices, positioning first-party data at the heart of this shift.  

Unlike third-party data, which is often procured from external sources, first-party data is gathered directly from customer interactions, offering unparalleled insights into consumer behavior, preferences, and needs. This direct relationship not only ensures compliance with privacy laws but also enhances the accuracy and relevance of data, enabling businesses to make more informed decisions, tailor personalized experiences, and ultimately, foster deeper customer loyalty. 

The increasing demand for first-party data talent 

As the digital landscape continues to evolve with the decline of third-party cookies and a heightened focus on privacy regulations, the demand for skilled first-party data professionals has surged. This shift necessitates a new breed of professionals adept in harnessing first-party data to sculpt personalized customer experiences and inform strategic decision-making. The imperative for these skills is underscored by significant industry transformations which compel businesses to integrate advanced technology to maintain a competitive edge.  

Moreover, organizations looking to broaden their service portfolios, refine their business models, and foster innovation are finding digital capabilities to be indispensable. Within this context, the expansion of first-party data roles is not merely a response to changing market dynamics but a strategic move to capitalize on digital transformation. It signifies a strategic pivot towards leveraging data as a cornerstone of business strategy. As such, the growth of first-party data roles is emblematic of a broader shift towards more agile, responsive, and personalized business strategies, underpinned by robust digital infrastructure. 

This has been reflected in job growth numbers for critical first-party data roles. Take data scientists for example. By 2019, postings for data scientists on Indeed had risen by 256%, and the U.S. Bureau of Labor Statistics, predicts data science will see more growth than almost any other field between now and 2029. Meanwhile, job openings for Data Engineers have grown by 30% over the past five years, while AI engineers have increased by 74% in the past four years.   

Other critical first-party data roles experiencing growth include:  

But demand for first-party data talent isn’t just happening on the frontlines of tech teams. Instead, competition is heating as organizations emphasize the strategic importance of digital and data competencies in driving organizational change and innovation. They are looking for leaders who possess a broad skill set that transcends traditional digital boundaries, underscoring the interdisciplinary nature of managing first-party data effectively. This has led to a significant growth in the number of Chief Data Officer roles, for example.  

A decade ago, only 12% of large firms had a Chief Data Officer (CDO), but by 2021, this number soared to nearly 70%. But it’s evident that the path to success is a challenging and uncertain one. Both statistical data and real-world experience paint a rather precarious picture. According to research conducted by Gartner and HBR, the average tenure of a CDO hovers around a mere two to two-and-a-half years. It’s a rare sight to find CDOs who have held their positions for more than three years. This points to disconnects between business strategy, data, and a candidate’s ability to sell their achievements to across the C-suite. That begs a critical question, do you need a CDO and are you ready to hire first-party data talent?  

How to Hire First-Party Data Talent

Critical questions to ask prior to hiring

Before embarking on the journey of building a first-party data team and making strategic hires, business leaders should prioritize asking critical questions that align with their overall business strategy and goals.

This includes:  

1. Business Alignment: Begin by understanding how first-party data aligns with your organization’s strategic objectives. Ask: “How can leveraging first-party data directly contribute to achieving our business goals, whether it’s boosting revenue, reducing costs, optimizing cash flow, or enhancing data stewardship?” 

2. Championing Change: Identify forward-thinking business partners who can champion the adoption of data-driven practices across the organization. Ask: “Who within our organization can serve as a catalyst for change and showcase the transformative potential of data analytics?” 

3. Strategic Integration: Embrace Chief Digital and Information Officer at Procter and Gamble, Guy Peri’s philosophy of aligning data strategies with business unit goals. Ask: “Are our data initiatives directly supporting the strategic goals of our business units, and how can we ensure alignment throughout the process?” 

4. Data Platform Readiness: Assess the readiness of your data infrastructure and capabilities. Ask: “Is our current data platform equipped to handle the data sources, collection methods, and data security measures necessary to support our strategic objectives?” 

5. Ethical Data Practices: Prioritize ethical data practices and compliance with relevant regulations. Ask: “Are we adhering to the highest ethical standards in data collection, management, and usage, while ensuring compliance with privacy laws?” 

6. Digital Acceleration Stage: Determine where your organization stands on the digital acceleration continuum. Ask: “Are we in the early stages of digital adoption, and do we need a Chief Data Officer to drive digital maturity?” 

7. Tech Responsibilities: Consider the restructuring of tech roles, such as the CIO, CTO, Chief Data Officer, and Chief Innovation Officer, to align with your business strategy. Ask: “How can we reshape tech responsibilities to optimize our digital capabilities?”

  8. Digital Integration: Emphasize the integration of digital throughout your organization, transcending the development of a standalone digital strategy. Ask: “How can we seamlessly integrate digital initiatives into all aspects of our business, from channels and processes to data, operating models, incentives, and culture?” 

Common first-party data roles to hire for 

Building a first-party data team involves establishing roles that cover various aspects of data management, analysis, strategy, and governance. Beside the Chief Data Officer (CDO), who provides leadership and strategic direction, several other roles are crucial for a comprehensive first-party data team: 

  • Data Scientists and Analysts: These professionals are essential for extracting insights from data. They apply statistical analysis, machine learning, and predictive modeling to understand trends, patterns, and predictions that inform business strategies.
  • Data Engineers: They build and maintain the data infrastructure necessary for collecting, storing, and processing large sets of data efficiently. This includes setting up data pipelines, databases, and data warehousing solutions.
  • Data Architects: Responsible for designing the data framework and ensuring that the data structures support the company’s needs. They define how data is stored, consumed, integrated, and managed by different data entities and IT systems.
  • Data Governance Specialists: These individuals develop and implement policies and procedures that ensure data across the organization is accurate, available, and secure. They also ensure compliance with data protection regulations (like GDPR or CCPA).
  • Data Stewards: They are responsible for the management and quality of data elements, both content and metadata. Data stewards work closely with business units to ensure that the data meets the organizational standards and user needs.
  • Business Analysts: They bridge the gap between IT and the business by using data analytics to assess processes, determine requirements, and deliver data-driven recommendations and reports to executives and stakeholders.
  • Privacy Officers or Legal Counsel: With the increasing importance of data privacy and security, having individuals who understand the legal implications and can ensure compliance with relevant laws and regulations is critical.
  • Data Product Managers: These roles focus on the commercialization and productization of data assets. They work to turn data capabilities into data products or services that can provide value to customers or generate new revenue streams.
  • Data Visualization Specialists: They are responsible for designing and developing visual representations of data to make the insights accessible and understandable to non-technical stakeholders.
  • Change Management and Training Professionals: These roles facilitate the organizational adoption of data-driven culture and practices. They are responsible for training employees on data tools, policies, and best practices.

Each of these roles plays a crucial part in ensuring that a first-party data team can effectively collect, manage, analyze, and leverage data to drive business decisions and strategies. The team’s exact composition might vary depending on the organization’s specific needs, size, and industry. 

Attracting executive first-party data talent 

So, how can organizations attract these data leaders? It requires a nuanced and multi-pronged approach that mixes a strong employer brand and value proposition, access to active and passive-talent pools, talent development programs, and highly competitive compensation packages. But that’s not all.

Organizations need to be able to win over prospective candidates by showcasing critical aspects of the job itself. This means highlighting the ability for candidates to work on projects that are addressing big, high-impact organizational challenges; Providing candidates access to industry-leading tools, technology, and support mechanisms; And describing how a candidate’s contributions are recognized and what it’s like to be part of a “pro-data and analytics” culture. Like any employee, employers must demonstrate a clear path of career progression and related milestones through which a candidate can quantifiably gauge their ability to rise through the ranks.  

Assessing first-party data talent 

The skills, experiences, and traits the enable candidates to effectively collect, analyze, and leverage data generated internally from the organization’s own platforms and customer interactions vary by the first-party data role being hired for. Here’s a list of common skills, experiences, and traits that businesses often look for: 


  • Data Analysis and Interpretation: Ability to analyze and interpret complex data sets to drive business insights and decisions. 
  • Statistical and Mathematical Modelling: Proficiency in statistical methods and mathematical models to understand trends and patterns within data. 
  • Data Management and Governance: Knowledge of data management practices, including data storage, data quality, and governance policies. 
  • Programming and Database Management: Proficiency in programming languages such as SQL, Python, or R for data manipulation and analysis. Experience with database management systems is also crucial. 
  • Data Visualization: Skill in presenting data in a clear and understandable manner using tools like Tableau, Power BI, or similar visualization software. 
  • Machine Learning and Predictive Analytics: Familiarity with machine learning algorithms and predictive analytics to forecast future trends and behaviors. 
  • Privacy and Compliance: Understanding of data privacy laws and regulations such as GDPR, CCPA, and others, ensuring data is handled ethically and legally. 


  • Data-Driven Project Management: Experience in managing projects where decision-making is driven by data insights. 
  • Customer Relationship Management (CRM) Systems: Hands-on experience with CRM systems and integrating first-party data for personalized marketing and sales strategies. 
  • Data Integration and Warehousing: Experience with integrating disparate data sources and managing data warehouses to centralize and streamline data analysis. 
  • Cross-Functional Collaboration: History of working across different departments (e.g., marketing, sales, IT) to leverage data insights for organizational benefit. 
  • Industry-Specific Experience: Depending on the sector (e.g., retail, finance, healthcare), experience with industry-specific data and challenges can be vital. 


  • Analytical Thinking: Ability to think critically and analytically to solve complex problems and make data-driven decisions.
  • Attention to Detail: Precision and attention to detail in handling data, ensuring accuracy and reliability of insights.
  • Curiosity and Continuous Learning: A keen interest in staying updated with the latest data trends, tools, and technologies.
  • Communication Skills: Strong ability to communicate technical information to non-technical stakeholders effectively. 
  • Problem-Solving: Aptitude for identifying problems and using data to propose viable solutions. 
  • Ethical Judgment: Commitment to ethical standards in data handling, respecting privacy, and maintaining confidentiality. 
  • Collaboration and Teamwork: Ability to work collaboratively within teams and across departments to achieve data-driven goals. 

For organizations looking to hire a Chief Data Officer, candidate assessment must go beyond pure technical skills, and instead prioritize and scrutinize aspects like:  

  • Agile mindset and the ability to drive significant transformation: Building a ‘spirit of digital’ within the organization and increasing its ‘metabolic rate’ are crucial. This involves embedding agility and speed into processes, fostering a culture of rapid experimentation and learning, and effectively managing data to inform decisions and innovations.
  • Cross-functional collaboration and networking: Extending networks both internally and externally is vital for a CDO. They should build relationships with a wide range of stakeholders, including external partners, start-ups, and technology providers, to bring innovative ideas and technologies into the organization. Internally, building strong relationships with IT, marketing, and other departments is key to ensuring that digital initiatives are integrated and supported across the business. 
  • The ability to identify, attract, and assess experts to increase department capacity: A CDO should have a keen eye for identifying emerging skills and roles critical to digital transformation, such as data scientists, digital product managers, UX/UI designers, and cybersecurity experts. They should stay informed about the latest digital trends and technologies to understand the evolving skills landscape. Utilizing professional networks, industry conferences, and digital platforms like LinkedIn can help in scouting for talent. Additionally, partnering with academic institutions and participating in hackathons and tech meetups can be effective ways to connect with potential candidates. 
  • Whether a candidate has the business acumen to translate strategy into action, and action into wins that stakeholders understand and value: A CDO should possess the ability to translate complex digital initiatives into strategic business outcomes that resonate with the wider organization, including the executive team, board members, and non-technical staff. This involves framing digital achievements not just in terms of technology milestones, but in how they contribute to key business metrics such as revenue growth, customer satisfaction, operational efficiency, and competitive advantage. 
  • Knowledge of relevant data-privacy regulations, policies, trends, and governmental bodies: A CDO must possess an in-depth understanding of diverse data-privacy regulations and policies, including global frameworks like the GDPR, CCPA, CPRA, and the Virginia CDPA, which encompass explicit consent for data processing, data accuracy, individuals’ rights to their data, and stringent security measures. Awareness of emerging trends and legislation, such as the EU’s ePrivacy Regulation and AI Act, is also crucial, highlighting the importance of user control and ethical AI development. Additionally, the CDO should stay informed about enforcement actions by bodies like the FTC, which underscore the significance of robust data security practices and compliance with evolving standards. 
  • Visibility and Advocacy: The CDO should act as a digital evangelist within the organization, raising the visibility of digital initiatives and their business impact. This could involve speaking at company-wide meetings, contributing articles to the company newsletter, or participating in industry panels and forums. The goal is to continually highlight the work of the digital team and its contribution to the organization’s success. 
  • Customer Obsession: A successful CDO must have a deep understanding of customer behavior across all channels and make customer-centricity a core competency of the organization. They should use detailed analyses of customer journeys and big data to challenge the status quo and drive changes that enhance customer experiences.

Common mistakes when hiring first-party data talent:  

When hiring first-party data talent, organizations should take a detailed and specific approach at each stage of the hiring lifecycle to ensure they attract, assess, and retain the right candidates. However, the following mistakes are commonly made during this process: 

Job Description Mistakes: 

  • Lack of Specific Technical Requirements: Failing to specify the data analysis tools, programming languages (like Python or R), and database technologies (such as SQL or NoSQL databases) relevant to your first-party data ecosystem. This can attract candidates who may not have the necessary technical expertise for your specific data environment.
  • Underemphasizing Data Privacy Knowledge: Not highlighting the importance of knowledge in data privacy laws and regulations (like GDPR, CCPA) in the job description. First-party data roles often require navigating complex privacy landscapes, and overlooking this can lead to hiring talent unprepared for these crucial aspects. 

Interview Process Mistakes: 

  • Insufficient Evaluation of Data-Driven Decision-Making Skills: Not thoroughly assessing a candidate’s ability to derive actionable insights from first-party data and influence strategic decisions. This oversight can result in hires who are technically competent but unable to effectively drive business outcomes with data.
  • Overlooking Experience with First-Party Data Sources: Not specifically evaluating candidates’ experience with managing and analyzing data from direct customer interactions, CRM systems, or subscription platforms. Experience with these sources is crucial for roles focused on first-party data.
  • Lengthy Interview Processes: Overextended hiring timelines can significantly disadvantage organizations seeking first-party data talent. Top candidates, often in high demand, may lose interest or accept other offers if the interview process drags on, reflecting poorly on the company’s agility and decision-making culture. Streamlining interviews to focus on essential assessments and maintaining clear, timely communication can help keep candidates engaged and prevent losing out on high-quality talent. We recommend no more than three interviews.  

Offer and Negotiation Mistakes: 

  • Not Addressing Data-Specific Career Growth: Failing to articulate clear career paths for first-party data roles, including opportunities for advancing in data strategy, data governance, or leadership positions within the data domain. This can deter candidates looking for long-term growth in data-centric careers. 

Onboarding and Retention Mistakes: 

  • Overlooking First-Party Data Integration Training: Neglecting to include comprehensive training on integrating and leveraging first-party data from various internal systems and platforms during onboarding. Proper integration is key to maximizing the value of first-party data.
  • Inadequate Support for Ongoing Data Education: Not providing or emphasizing continuous learning opportunities in emerging first-party data management practices, advanced analytics techniques, and evolving data privacy regulations. Continuous education is crucial for keeping first-party data talent at the cutting edge. 

Culture Fit and Engagement Mistakes: 

  • Not Promoting a Data-Centric Culture: Failing to demonstrate during the hiring process how data, especially first-party data, is valued and utilized for decision-making across the organization. Candidates should see a clear link between their role and the company’s broader data-driven objectives.
  • Underestimating the Importance of Data Ethics: Not discussing the ethical considerations and the organization’s commitment to ethical data use during the hiring process. Ethical use of first-party data is increasingly becoming a deciding factor for data professionals when choosing employers. 

Finding the right candidate 

In today’s digital era, the value of first-party data is paramount, driving the need for adept professionals in data management and analytics. As businesses strive to adapt to privacy regulations and harness customer data for strategic insights, the demand for specialized talent has surged. Building a team equipped with the skills to navigate these challenges is crucial for leveraging data effectively and fostering personalized customer experiences. For organizations looking to strengthen their data and analytics capabilities, our technology practice at Talentfoot offers comprehensive support. We are dedicated to helping you assemble a team that can unlock the full potential of your first-party data.

Discover more about how Talentfoot can empower your organization’s data journey by visiting our technology practice.