Data Quality Lead

X, bigly labs; Johannesburg; On-site; ZAR 900,000 - 1,300,000; Full time

Job summary

X, bigly labs in Johannesburg is seeking a Data Quality Lead to build and scale the organisation's data quality capability, partnering with data engineers and analytics teams to raise confidence across critical domains. You will define standards, implement checks, and drive governance aligned with POPIA/GDPR, enabling data-driven decisions and AI readiness.

You will lead a small team, work with business stakeholders, and champion a culture of data stewardship, quality, and accountability across

Qualifications

• Bachelor’s degree in CS, information systems, or a related field.
• 5+ years in data quality, data management, or data engineering, with at least 2 years in a lead/supervisory capacity.
• Proven experience improving data quality in organisations not already well-governed.
• Strong SQL and Python; ability to profile data, build validation logic, and write checks.
• Experience with data quality tooling and modern data platforms.
• Experience with Power BI dashboards and data quality reporting.
• Familiar with DAMA-DMBOK, POPIA, GDPR regulatory standards.
• Demonstrated cross-functional leadership and stakeholder management.

Responsibilities

• Assess data quality landscape and identify high-impact issues across domains.
• Map end-to-end data flows to identify root causes of quality failures.
• Design and implement data quality checks, validation rules, and monitoring.
• Represent data quality in Data/AI governance forums and risk reviews.
• Own and evolve an enterprise data quality framework, standards, and measures.
• Oversee profiling and cleansing of structured and unstructured datasets.
• Align with regulatory frameworks to minimise risk and enhance data stewardship.

Skills

SQL

Python

Data profiling

Data cleansing

Data validation

Stakeholder management

Leadership

Data governance

Power BI

Education

Bachelor’s degree in Computer Science or related field

Tools

Great Expectations

dbt tests

Monte Carlo

Soda

Snowflake

BigQuery

Databricks

Airflow

dbt

Job description

We are X, bigly labs, Dis-Chem’s high-performance innovation hub; a place where bold ideas meet data, design, and radical customer focus to reimagine what healthcare can be.

Our mission is to power the future of healthcare by lowering costs, unlocking new possibilities, and improving access to healthcare for all South Africans. We do this through cutting-edge digital solutions that deliver smarter, more human, and truly patient-focused experiences. Here, your work is not limited to a whiteboard; it becomes real. It drives decisions, shapes experiences, and moves healthcare forward. We are driven by one big question: How do we use data and today’s technology to build breakthroughs to better health?

There’s only one question left: are you ready to make healthcare smarter, and actually mean it?

Data Quality Lead will build the organisation's data quality capability from a low base by establishing the practices, tooling, and culture needed to make data trustworthy and usable. Working as a core member of the Data, Analytics & AI chapter, the Data Quality Lead will be the driving force behind lifting data confidence across the organisation, one data domain at a time. The Data Quality Lead will work directly with business teams, data engineers, and analytics practitioners to understand where poor data quality is causing real pain, prioritise ruthlessly, and fix things in ways that stick. The Data Quality Lead will balance tactical quick wins with the structural foundations that prevent problems from recurring. The Data Quality Lead is responsible for setting the strategic direction for enterprise data quality, leading a team of Data Quality Analysts, and embedding robust data quality standards across platforms and domains. This role serves as a centre of excellence for data quality practice, directly enabling strategic decision-making, regulatory compliance, and AI readiness. The Lead will champion a data quality culture, own the enterprise data quality framework, manage stakeholder relationships at a senior level, and ensure the team delivers scalable, automated quality solutions aligned to modern data science and AI practices.

WHAT WE'RE LOOKING FOR?

Minimum

• Bachelor’s degree in, Computer Science, Information Systems, or a related field.
• 5+ years of experience in data quality, data management, or data engineering roles, with at least 2 years in a lead, senior, or supervisory capacity.
• Demonstrated experience improving data quality in a real organisation, ideally one that was not already well-governed.
• Strong proficiency in SQL and Python; ability to interrogate data, profile datasets, and write validation logic.
• Practical experience with data quality tooling (Great Expectations, dbt tests, Monte Carlo, Soda, or similar).
• Familiar with modern data platforms (Snowflake, BigQuery, Databricks, or similar) and pipeline tooling (dbt, Airflow, or similar).
• Comfortable working with data at source: understanding APIs, databases, flat files, and the ingestion layer well enough to identify where quality breaks down.
• Experience with BI and reporting tools (e.g., Power BI), including building and maintaining data quality dashboards and scorecards.
• Familiarity with data governance frameworks (e.g., DAMA-DMBOK), metadata management, and data privacy regulations (POPIA, GDPR).
• Demonstrated experience leading cross-functional teams, managing stakeholder relationships, and driving organisational data quality culture.
• Experience working directly with business stakeholders to diagnose data problems and co-design solutions.
• Exposure to both the technical and organisational dimensions of data quality

Advantageous

• Certifications in Data Governance (CDMP), AI Ethics, or Machine Learning.
• Experience in healthcare, retail, or insurance
• Postgraduate qualification with a data or technology focus.

WHAT YOU WILL BE DOING?

• Conduct a rapid, pragmatic assessment of the organisation's data quality landscape by identifying the most painful, highest-impact quality issues across key data domains.
• Map data flows end-to-end across critical domains to identify root causes, not just symptoms, of recurring data quality failures.
• Design and implement practical data quality checks, validation rules, and monitoring across pipelines, with a clear escalation and remediation path for failures.
• Represent data quality in Data and AI governance forums and model risk review processes.
• Own and evolve a pragmatic enterprise data quality framework, for the organisation's current maturity, including standards, policies, and measurement approaches.
• Oversee profiling and cleansing of structured and unstructured critical datasets across business domains.
• Align with frameworks like DAMA-DMBOK, POPIA, GDPR, and internal governance policies to minimise regulatory risk and enhances organisational data stewardship.

WHO YOU ARE?

• Expert-level proficiency in data profiling, cleansing, and validation methodologies.
• Experience driving cultural change and embedding data quality practices organisation-wide.
• Ability to trace data anomalies across complex systems and recommend sustainable solutions.
• Builds strong relationships with data owners, engineers, analysts, and business users.
• Familiarity with data governance frameworks (e.g., DAMA-DMBOK) and regulatory standards (e.g., POPIA)

Our values show up in how we think, build, and make choices that make an impact. We are building a culture that drives progress; one that fixes friction, chases what changes, and owns the outcome. We design with tomorrow in mind, ask sharper questions, and answer them with care, urgency, and systems that scale.

Think you’ve got energy, curiosity, and guts? Come hold the space, make it matter, and own a breakthrough.