Analytics Lead

X, bigly labs

. Define, publish and maintain craft standards for BI development, data analysis and analytics engineering, covering modelling, coding, visualisation, documentation and version control.

Posted 10/21/2026full-timeJohannesburg • South AfricaSeniorWebsite

Core Competencies

Role fit

Core Competencies

Use this summary to align your resume positioning with the role.

Demonstrates expertise in Business Intelligence, Data Analysis, and Analytics Engineering, with a strong focus on establishing standards, frameworks, and quality assurance processes. Proven leadership in recruitment, onboarding, and career development of analytics professionals across diverse teams.

Highest-signal resume keywords

Business IntelligenceData AnalysisAnalytics EngineeringSQL ProficiencyPeople Leadership

ATS Keywords

Tailor your resume

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills

Data ModellingDimensional ModellingAnalytics StandardsPerformance ManagementRecruitmentOnboardingCareer DevelopmentVersion Control PracticesData GovernanceData Quality

Soft Skills

CollaborationCommunicationLeadershipMentoringStakeholder Engagement

Tools & Technologies

Power BITableauQlikSAP BusinessObjects BI SuiteSAP BW/4HANADbtAzureAWSGCP

Certifications & Qualifications

Postgraduate QualificationAgile Certification

Industry Keywords

Retail ExperiencePharmacy ExperienceHealthcare ExperienceAI ExposureML ExposureGenAI Exposure

Tech Stack

Tools & technologies

AWSAzureGoogle Cloud PlatformSQLTableau

About the role

Key responsibilities & impact

Define, publish and maintain craft standards for BI development, data analysis and analytics engineering, covering modelling, coding, visualisation, documentation and version control.
Establish quality gates across the analytics lifecycle, including design reviews, peer code reviews, and dashboard and dataset certification.
Establish and run Centres of Excellence for BI, Data Analysis and Analytics Engineering, each with a charter, ownership and roadmap.
Own recruitment for analytics roles, including role definition, assessment design, interview panels and hiring recommendations.
Design and run structured onboarding for analytics staff, contractors and consultants, covering access, tooling, data landscape, standards and ways of working.
Partner with the Data Analytics Chapter Lead on chapter strategy and report regularly on analytics craft health.
Act as custodian of the analytics craft across X, bigly labs, covering Business Intelligence, Data Analysis and Analytics Engineering.
Ensure analytics practitioners in tribes and domains deliver consistently high-quality work addressing underlying business problems.
Own the analytics talent lifecycle, including recruitment, onboarding, career development, training and coordination of performance matters, in partnership with tribe and domain leadership and the Data Analytics Chapter Lead.

Requirements

What you’ll need

Bachelor’s degree in Information Systems, Computer Science, Statistics, Data Analytics, or a related field.
10+ years of experience across business intelligence, data analytics and/or analytics engineering.
5+ years in a people leadership role leading analytics professionals, ideally across multiple teams in a matrix (tribe, squad and chapter) environment.
Demonstrated experience in establishing analytics standards, frameworks, communities of practice or Centres of Excellence.
Hands-on depth in at least one of data analysis or analytics engineering, with sound working knowledge of the other two.
Strong proficiency in SQL and data modelling (dimensional modelling, semantic layers) and experience with BI tools (e.g., Power BI, Tableau, Qlik, SAP BusinessObjects BI Suite).
Experience with modern data platforms and tooling (e.g., SAP BW/4HANA, dbt, Azure, AWS or GCP) and version control practices for analytics code.
Proven experience in recruitment, onboarding, performance management and career development of technical staff.
Experience in engaging and managing contractors, consultants and third-party vendors against agreed standards and statements of work.
Relevant certifications, postgraduate qualification, retail/pharmacy/healthcare experience, Agile, data governance/data quality, and AI/ML/GenAI exposure are advantageous, not required.