Senior AI Governance & Enablement Analyst

HeadHR; Wrocław; Hybrid; PLN 160,000 - 230,000; Full time

Job summary

HeadHR poszukuje doświadczonego analityka z silnym zapleczem w obszarze analityki biznesowej i inżynierii danych, aby prowadzić warstwę AI wspierającą analitykę biznesową. Oczekujemy 5+ lat doświadczenia, biegłej znajomości SQL i pracy z dużymi zestawami danych w chmurze.

Rolę charakteryzuje tworzenie i testowanie komponentów analitycznych Talk2Data, doskonalenie systemu oceny jakości odpowiedzi AI oraz współpraca z inżynierami danych i interesariuszami w zakresie własności danych i standardów

Qualifications

• Minimum 5 years of experience in an analytical role.
• Strong background in business analytics, data engineering or a related discipline.
• Advanced proficiency in SQL and experience with large datasets in cloud data platforms.
• Knowledge of data governance and data cataloguing practices (Atlan).

Responsibilities

• Owning development and maintenance of the AI layer supporting business analytics, including Talk2Data and agent-ready data.
• Defining, implementing and testing analytical components of Talk2Data - from specification and business validation to release.
• Building and improving the evaluation framework for AI response quality: metrics, representative Q&A pairs, ground truth and quality monitoring over time.
• Translating business needs, use cases and rules into requirements, acceptance criteria and analytical specifications.
• Collaborating with Data Engineers on dimensional data models (star schema), data quality checks, merge request reviews and deployments.
• Working with large datasets and cloud data platforms to validate data quality, structure and suitability for AI-powered analytics.
• Collaborating with Product Leads, Business Owners and stakeholders on data ownership and governance standards.
• Preparing presentations, guidelines and materials for technical and non-technical audiences.
• Facilitating enablement initiatives such as AI Office Hours and sessions with Product Leads.
• Improving Talk2Data quality and performance by analysing user feedback, product analytics and evaluation results.
• Driving adoption of Talk2Data and AI-assisted analytics across the organization.

Skills

SQL

Git

Databricks

Star schema

Claude/LLM tools

Tools

Claude

Databricks

Job description

• Owning development and maintenance of the AI layer supporting business analytics, including Talk2Data and agent-ready data
• Defining, implementing and testing analytical components of Talk2Data - from specification and business validation to release
• Building and improving the evaluation framework for AI response quality: metrics, representative Q&A pairs, ground truth and quality monitoring over time
• Translating business needs, use cases and rules into requirements, acceptance criteria and analytical specifications
• Collaborating with Data Engineers on dimensional data models (star schema), data quality checks, merge request reviews and deployments
• Working with large datasets and cloud data platforms to validate data quality, structure and suitability for AI-powered analytics
• Collaborating with Product Leads, Business Owners and stakeholders on data ownership and governance standards
• Preparing presentations, guidelines and materials for technical and non-technical audiences
• Facilitating enablement initiatives such as AI Office Hours and sessions with Product Leads
• Improving Talk2Data quality and performance by analysing user feedback, product analytics and evaluation results
• Driving adoption of Talk2Data and AI-assisted analytics across the organization

Kogo poszukujemy?

• At least 5 years of experience in an analytical role
• Strong background in business analytics, data engineering or a related discipline
• Advanced proficiency in SQL and experience with large datasets in cloud data platforms
• Comprehensive understanding of data warehousing concepts, including dimensional data modelling and ETL/ELT processes
• Hands-on experience with LLM-based AI tools, such as Claude or similar
• Practical understanding of how AI assistants are built and evaluated (quality metrics, Q&A datasets, ground truth, performance monitoring)
• Experience translating business needs into requirements, analytical specifications and acceptance criteria
• Ability to tailor communication and documentation to technical and non-technical audiences
• Basic familiarity with Git, code review and version control processes
• Knowledge of data governance and data cataloguing practices, including tools such as Atlan
• Strong stakeholder management and collaboration skills
• Analytical and critical mindset for assessing AI-generated outputs
• Experience with Databricks would be an asset
• Work from the European Union region and a work permit are required