Data Management Lead

Purpose

The Data Management Lead will be responsible for driving and embedding best-in-class data management practices within our engineering teams to ensure our data is accessible, reliable, secure, and fit for purpose. Acting as a subject matter expert and strategic advisor, the Data Management Lead will influence the technical patterns and engineering approaches to enable a consistent, comprehensive and trusted data ecosystem across all ShopriteX analytics data products. The role will ensure that data governance principles, data modelling standards, DataOps methodologies, and robust data quality frameworks are foundational elements of the engineering lifecycle. This role offers the opportunity to shape and influence advanced data engineering methodologies and standards within a collaborative and innovative environment, working alongside cross-functional teams dedicated to achieving data excellence.

Role Description

• Analyse and adopt DataOps best practices to produce shorter development cycles, optimise insightdelivery, and ensure a stable production environment.
• Advise on and implement DataOps principles within existing and new engineering patterns and pipelines.
• Liaise with stakeholders to structure and oversee CI/CD integration for data flows, ensuring automated testing and deployment processes are effectively deployed.
• By researching and charting best practices, the teams will focus on refining and streamlining data maturity and observability frameworks alongside DevOps and Analytics engineers.
• Develop high-quality, scalable data models that identify and support advanced analytics, machine learning, and optimised data consumption.
• Map and define patterns for building ShopriteX data models, data domains, and canonical data structures.
• Work with solution architects and engineers to benchmark schema design, evaluate data storage formats, and determine effective data organisation patterns.
• Ensure data lineage, semantic consistency, and integration patterns are upheld across all ShopriteX domains to improve data quality.
• The goal is to establish a well-defined governance model that produces increased data trust, reduces risk, and enhances compliance and auditability.
• Implement and maintain data governance policies, standards, and procedures aligned with industry best practices and regulatory requirements.
• Partner with cross-functional teams to ensure adherence to enterprise data governance and protection standards.
• Lead the adoption of metadata management, data cataloguing, and master data management (MDM) tools and practices to solve existing challenges in data governance.
• Analyse and measure improvements in data accuracy, completeness, visibility, and consistency across ShopriteX Analytics data products and domains.
• Establish and oversee data quality frameworks, metrics, and continuous improvement initiatives that focus on optimising data reliability.
• Deploy automated data quality checks, alerts, and remediation workflows that are integrated into the data pipeline.
• Mentor team members within business and engineering teams to foster accountability for data quality and ensure data management principles are embedded within the engineering mindset and toolset.
• Serve as the technical authority for data management patterns and contribute to the architectural roadmap by evaluating technology selection to ensure that tools and platforms support robust data management practices.
• Provide training, mentorship, and thought leadership on data management best practices to engineering and analytics communities, continuously working to improve the data management culture.

Qualifications & Experience

• Degree in Computer Science, Information Systems, Data Management, or related fields - (essential).
• +6 years of experience in data management, data engineering, or related roles with a strong technical background - (essential).
• Demonstrated success in leading data management initiatives, implementing governance frameworks, and improving data quality in complex, multi-domain environments - (essential).
• Certifications in cloud platforms, data management (e.g., DAMA), or other relevant professional accreditations - (advantageous).
• Proficient in CI/CD pipelines (Asure DevOps, Terraform).
• Experience with cloud platforms (AWS) and containerisation (Docker, Kubernetes).
• Expertise in data modelling techniques (3NF, Dimensional Modelling).
• Knowledge of modern data architectures (data mesh, data Lakehouse).
• Familiarity with SQL, NoSQL databases, and big data formats (e.g., S3, Snowflake, Iceberg).
• Familiar with governance frameworks (DAMA-DMBOK, DCAM) and compliance (GDPR, CCPA).
• Hands-on experience with data cataloguing and metadata management.
• Ability to manage data classification and lineage processes.
• Skilled in data quality rules, anomaly detection, and validation frameworks (e.g., Great Expectations,).
• Experience with observability tools for monitoring and lineage tracking.
• Proficient in programming languages (Python, Scala, Java).
• Understanding of distributed processing frameworks (Spark, Flink) and workflow orchestration (Airflow).

Our Group and all its operating companies is committed to creating, embracing, and preserving a diverse workplace that values the unique talents, perspectives, backgrounds, and abilities that enrich our organisation. A place where everyone matters and feels included.

We are committed to Employment Equity when recruiting internally and externally.

Please take note that by responding to this application and providing your personal information, you confirm your express and informed consent for Shoprite Checkers (Pty) Ltd and all its subsidiaries and affiliates companies to process your personal information for the Company to consider your application for this position. All Personal Information which you provide to the Company will be used and/or retained only for the purposes for which it is collected, whereafter it will be permanently destroyed. Your information is only retained if it is required by law or where you have given consent to us to retain such information for an extended period.

If you don’t hear from us within 14 days, please consider your application unsuccessful. Any personal information collected as part of your application will be destroyed, securely, in accordance with South African legislation.