HR Business Intelligence (BI) Senior Manager (Data Modelling, Data Analytics, Workday,Python, Power BI)

Job Description

Welcome to AtkinsRéalis, a global leader in Design, Engineering, and Project Management. Established from an integration of long-standing organizations dating back to 1911, we are dedicated to engineering a better future for our planet and its people. We specialize in sustainable solutions that connect people, data, and technology to transform infrastructure and energy systems worldwide. Leveraging global capabilities locally, we offer end-to-end services throughout the life cycle of an asset, including consulting, advisory & environmental services, intelligent networks & cybersecurity, design & engineering, procurement, project & construction management, operations & maintenance, decommissioning, and capital.

Stay updated with the latest news and information on our website or follow us on LinkedIn. Our talented team is the backbone of our success, and their diverse thinking, expertise, and knowledge are key to delivering some of the most prestigious projects across the world.

Benefits of Working with AtkinsRéalis

At AtkinsRéalis, we believe in a balanced work-life approach, supported by our flexible and remote working policies. Our commitment to equality includes pledges to Women's Equality and being a 'Disability Confident' and 'Inclusive Employer'. Join us in a genuinely collaborative environment where everyone is empowered to achieve their best.

Our HR team, consisting of 270+ members, operates under one Hub, segmented into Recruitment, Lifecycle, Offboarding, Service Excellence, and Contact Management. With a strong focus on diversity and inclusion, we strive to build a workplace reflective of society's diversity. Bring your authentic self and help us create a better tomorrow.

Job Overview: HR BI Senior Manager

The HR BI Senior Manager will be a pivotal member of the Global HR Excellence & Analytics team, overseeing day-to-day deliverables while driving innovation in HR Reporting. This role requires a combination of HR analytics knowledge and advanced technical skills in Python, data modeling, AI, and predictive analytics. The ideal candidate will lead the innovation of HR processes, leveraging cutting-edge technologies to optimize decision-making and operational efficiency.

Key Responsibilities

Team Management:

• Manage the workload of the HR Excellence & Analytics team, effectively assigning projects and tasks.
• Provide guidance and mentorship to foster continuous learning and development.

Stakeholder Engagement:

• Understand external and internal business contexts, supporting stakeholders in formulating workforce information, KPIs, reports, dashboards, and ad hoc analyses.
• Define project scopes, formulate detailed requirements for analysts, and ensure timely delivery of requests.

Quality Control and Automation:

• Apply logic to raw data sets, validate automated calculations, and establish QC protocols for periodic KPI production.
• Identify opportunities to automate existing insights production and reporting tasks within HR teams.

Collaboration and Training:

• Collaborate with the IT Business Intelligence team, acting as an interlock between stakeholders and analysts.
• Build strong working relationships with HR teams, Business Leaders, and key stakeholders.
• Develop training material for the HR community on using HR Analytics tools.

Data and Analytics Inputs:

• Provide data and analytics inputs for monitoring HR service delivery efficiency.
• Focus on data quality, assurance activities, data audit requirements, and data governance.

Special Projects and Troubleshooting:

• Support special projects with HR data and analytics expertise.
• Troubleshoot data and reports as needed.

Technical Leadership in HR Analytics:

• Utilize advanced technical skills, including proficiency in Python, to lead the development and implementation of HR analytics strategies.
• Drive the exploration and application of AI and predictive analytics to enhance talent acquisition, workforce planning, and employee engagement.

Data Modelling and Analysis:

• Design and implement robust data models to extract meaningful insights from HR data sets.
• Conduct in-depth data analysis to identify trends, patterns, and opportunities for process improvements.

Automation Solutions:

• Lead the identification and implementation of automation solutions within HR processes