Own and evolve Keyloop’s People Data Platform and HR analytics dashboard (Python/Streamlit)
Design and maintain data architecture (pipelines, schemas, models) across SAP SuccessFactors and other HR systems
Manage API integrations and data access with core platforms and third-party vendors
Deliver insights across People Metrics, TA, L&D, and Engagement, partnering with functional leads
Own BAU reporting, driving accuracy, automation, and self-service adoption
Ensure GDPR and data compliance, including access controls and auditability
Build and scale AI-driven HR solutions (LLMs, agentic workflows, document processing, large-scale pipelines)
Develop production-ready AI use cases (e.g., attrition insights, skills inference, policy Q&A, candidate processing) and evaluate emerging tools
Act as HR AI SME, enabling adoption through training, playbooks, and self-service frameworks across HR and G&A
Partner with senior leadership, IT (AWS), and governance forums to shape the People Technology roadmap and responsible AI practices

Strong Python expertise building production-grade data applications, dashboards, or tools.
Hands-on experience in data engineering (ETL pipelines, API integrations, data modelling).
Proven track record integrating LLM/AI APIs (e.g., Anthropic, OpenAI) into live applications.
Solid knowledge of AWS and modern data/visualisation frameworks (e.g., Streamlit, Plotly).
Experience with SSO/authentication (OAuth2, SAML, Azure AD / Entra ID).
Strong data literacy and storytelling, with the ability to communicate insights to non-technical audiences.
High autonomy with a rigorous approach to data privacy, security, and compliance.
Desirable: Experience with SAP SuccessFactors or similar HRIS, including API/OData integration.
Proficiency in Power BI (data modelling, DAX, dashboards).
Familiarity with agentic AI frameworks (e.g., LangChain, CrewAI).
Understanding of HR data domains (e.g., headcount, attrition, hiring, engagement).

HR Tech Data Engineer

Key skills