HR Analytics Lead

HR Analytics Lead

Warsaw |  Hybrid: 3 days in office, 2 days remote

About Consid

Consid is an award-winning IT and consulting company founded in Sweden, with a strong presence across Scandinavia and Europe, including Poland. We partner with leading enterprises to build modern, scalable digital solutions, combining a strong engineering culture with long-term, trust-based collaboration. At Consid, we value ownership, quality, and continuous development.

About the Role

We are hiring an HR Analytics Lead for one of our clients. In this role, you will play a central part in transforming how workforce data supports business decisions. Working at Associate Director level, you will be responsible for the full HR data products portfolio, drive capability development across the analytics function, and bridge the gap between people strategy and technical data infrastructure.

You will join a team embedded within Central Functions, working closely with HR, IT, and data engineering colleagues. The team is known for its collaborative approach and high standards around data quality. If you enjoy finding clarity in complexity and turning raw data into decisions that matter, this role is for you.
 

Responsibilities

• Take end-to-end ownership of HR data products, continuously improving them to serve the analytical and operational needs of stakeholders across HR and the wider business.

• Develop and maintain workforce planning models that inform decisions on headcount growth, talent allocation, and organisational design.

• Build and govern the HR data quality framework, setting clear standards, keeping pipelines healthy, and fixing integrity issues at the root.

• Serve as the go-to person for all matters related to HR data architecture and lead data initiatives across the function.

• Work hand in hand with the Technology team to keep HR data infrastructure aligned with the broader platform roadmap and current best practices.

• Grow the analytics capability of the HR team through coaching, knowledge sharing, and embedding a data-first mindset into how the team operates day to day.

• Present complex workforce insights in ways that are visually compelling and easy for senior leaders to act on.

Requirements

• Extensive, senior-level experience in HR analytics or people data, with a strong portfolio of owned data products and a proven record of delivering strategic workforce insights in large, complex organisations.

• Practical knowledge of data modelling and pipeline development, with experience using tools such as Fivetran, dbt, or Snowflake.

• Strong skills in Power BI or comparable BI platforms, including the ability to design dashboards that communicate data clearly to non-technical users.

• Familiarity with HR data architecture, including governance practices, data quality processes, and system integrations.

• A track record of growing analytics capabilities in others, whether through direct management, mentoring, or process change.

• Proven ability to manage relationships with a wide range of stakeholders, from data engineers to HR business partners and senior leaders.

• Confidence working across the HR and technology boundary, with experience navigating shared data agendas in cross-functional settings.
  

Nice to Have

• Exposure to machine learning or AI, including tools like model context protocol (MCP) or experience contributing to agentic AI workflows.

• Awareness of how AI is being applied to HR analytics use cases such as attrition prediction, skills mapping, or workforce forecasting.

• Prior experience in a global or matrix organisation where HR data comes from multiple sources and systems.

• Knowledge of data mesh concepts or product-thinking approaches to data architecture.
  

Recruitment Process

1.  Screening Call (30 min): A short introductory conversation with our recruitment team to discuss your background, motivation, and role expectations.

2. Cultural Fit Interview: A meeting focused on collaboration style, communication approach, and how you operate in an international environment.

3.  Technical Interview: A deeper technical discussion covering data architecture, analytics engineering, and HR data topics, including a hands-on deep dive relevant to day-to-day responsibilities.

4.  Final Interview (45 min): A concluding conversation focused on behavioural aspects, leadership and ownership mindset, and managerial alignment.