Data Quality Engineer - Available Immediately

Embelo; Cape Town; Hybrid; ZAR 420,000 - 660,000; Full time

Job summary

Embelo in Cape Town is expanding its data capability and seeks a hands-on Data Quality Engineer to help clients build trusted data. You will focus on data quality, validation, profiling and reconciliation using SQL and modern quality frameworks.

Work with Data Engineering, MDM and Integration teams to ensure data is accurate, complete and ready for downstream reporting and AI initiatives. Hybrid work in Cape Town with some in-office days.

Qualifications

• 3–5 years in Data Quality/Data Engineering/Data Governance/Data Analytics
• Strong SQL skills with data profiling and validation
• Experience designing or implementing data quality rules and automated checks
• Experience with data reconciliation and root-cause analysis
• Familiarity with data quality dimensions (completeness, accuracy, consistency, validity, uniqueness, timeliness)
• Ability to collaborate with data stewards and explain issues to technical and non-technical stakeholders

Responsibilities

• Profile source and target data to identify quality issues and anomalies
• Design and implement automated data validation and quality checks using SQL and data quality frameworks
• Define and maintain data quality rules across ingestion, transformation and publishing pipelines
• Investigate data issues to root cause and coordinate with engineering and business teams
• Triage and prioritize data quality issues with data stewards
• Build monitoring and reporting around data quality metrics and trends
• Support Master Data Management activities including match/merge and survivorship
• Embed data quality controls into pipelines with Data Engineers and Integration teams
• Document data quality rules, findings, exceptions and remediation actions clearly
• Support data governance and stewardship across client data domains
• Establish repeatable data quality standards and engineering practices

Skills

SQL

Data profiling

Data validation

Root cause analysis

Stakeholder communication

Education

Bachelor's degree (Computer Science/Info Systems/Data Science)

Tools

Elementary

Great Expectations

Informatica Data Quality

Databricks

dbt

Job description

At Embelo, we’re dedicated to helping founders of consulting businesses start and scale efficiently. Backed by our UK-based investors and clients, we deliver exceptional client services to a growing group of UK businesses, combining technical expertise, South African spirit, and the latest in AI-powered services. One of those is Inference Group, a fast-growing data and AI consultancy on a mission to help businesses unlock their true potential and drive sustainable growth.

Role Overview

We’re expanding our Data capability in Cape Town and are looking for a hands‑on Data Quality Engineer to help our clients build data they can genuinely trust.

The immediate focus of this role will be data quality, validation, monitoring and reconciliation – profiling data, building automated quality checks, investigating anomalies and working with business and technical teams to resolve issues at source.

You’ll work primarily with SQL, data profiling and validation techniques, and modern data quality frameworks such as Elementary, helping embed quality controls across data ingestion, transformation and master data processes.

This is a consulting role, so alongside strong technical data quality skills, we’re looking for someone who can understand the business meaning behind the data, work effectively with data stewards and explain issues and findings clearly to both technical and non‑technical stakeholders.

You’ll work closely with our Data Engineering, MDM and Integration teams, helping ensure data is accurate, complete, consistent and ready for downstream systems, reporting and AI.

Location: Hybrid – Cape Town, with a minimum of three days per week in our Woodstock office. Candidates looking to relocate to Cape Town are welcome to apply, although relocation would need to be arranged personally.

What You’ll Do

• Profile source and target data to identify quality issues, gaps, inconsistencies and anomalies.
• Design and implement automated data validation, reconciliation and quality checks using SQL and data quality frameworks such as Elementary.
• Define and maintain data quality rules across ingestion, transformation and publishing pipelines.
• Investigate data issues through to root cause and work with engineering and business teams to resolve them.
• Triage and prioritise data quality issues alongside business data stewards.
• Build monitoring and reporting around data quality metrics, trends and recurring issues.
• Support match/merge, survivorship and golden-record processes within Master Data Management initiatives.
• Work with Data Engineers and Integration teams to embed data quality controls into pipelines from the outset.
• Document data quality rules, findings, exceptions and remediation actions clearly.
• Support data governance and stewardship processes across client data domains.
• Help establish repeatable data quality standards and engineering practices across client platforms.

What We’re Looking For

You’ll have strong hands‑on experience working with data quality and be comfortable investigating problems directly in the data rather than simply reporting them.

• Around 3–5 years’ experience across Data Quality, Data Engineering, Data Governance, Data Analytics or a similar data‑focused role.
• Strong SQL skills, including hands‑on data profiling, querying, validation and investigation.
• Practical experience designing or implementing data quality rules, controls or automated checks.
• Experience with data reconciliation and root‑cause analysis.
• Understanding of common data quality dimensions such as completeness, accuracy, consistency, validity, uniqueness and timeliness.
• Experience working with data quality frameworks or tooling such as Elementary, Great Expectations, Informatica Data Quality or similar.
• Comfortable working with business stakeholders and data stewards to understand and resolve data issues.
• Able to document rules, findings and technical issues clearly.
• Comfortable working across both technical and business teams.

It Would Be Great If You Also Have

• Experience with Elementary or Great Expectations.
• Exposure to Databricks, dbt or modern cloud data platforms.
• Experience with Informatica Data Quality.
• Understanding of Master Data Management (MDM) concepts such as matching, merging, survivorship and golden records.
• Exposure to MDM platforms such as Profisee.
• Experience working within consulting or client‑facing environments.
• Exposure to data lineage, governance or metadata management.
• Enjoys getting into the detail and finding the reason behind a data problem.
• Takes ownership of issues through to resolution.
• Works in a structured and methodical way.
• Can explain complex data issues simply and clearly.
• Is comfortable working in a fast‑paced consulting environment.
• Works well across Data Engineering, business and governance teams.
• Is curious about modern data platforms, tools and approaches.

Education & Experience

A degree in Computer Science, Data Science, Information Systems or a related field is useful but not essential.

More important is practical experience working hands‑on with data quality, SQL and real‑world data problems.

Working With Us:

At Inference Group, we’re a young and fast‑growing consultancy built by people who are naturally curious and passionate about lifelong learning. If you’re driven and want to help shape the early stages of a dynamic business, we’d love to have you on board. You’ll be part of a team exploring the limitless opportunities of data and AI, driving excellence, growing together, and we’ll be having plenty of fun along the way.

We’re committed to hiring future leaders who will help shape our next chapter, and we’ll invest in your growth through access to the latest technology, hands‑on experience, mentorship and ongoing training and certifications. As AI continues to evolve, we promise our clients a team of people who stay ahead of the curve, equipped with the most up‑to‑date knowledge and skills to deliver truly innovative solutions. Our Values are:

We Geek Out Loud:

we excel in our data and AI domain, using our expertise to deliver solutions that realise value. We share our wisdom and experience proudly, no egos, just pure tech passion.

We Act Boldly, and Collaborate Openly:

we explore uncharted territories, working on the new to deliver operational solutions at scale. We don’t tread over old ground. We collaborate openly with full transparency, learning from each other as a community.

We are the Connectors:

we bridge the gaps between business value, data engineering, data science and deployment. Working seamlessly as one unified team internally and externally to deliver working solutions for our clients.

We Empower our Customers:

we equip our clients with the skills and knowledge to fully leverage, scale and deploy data and AI solutions. We prioritise delivering operational success over prototypes and proof of concepts to provide long term value. We build trust.

We Love our Work:

we are proud of the work we do and take ownership of it. We work on the things we love and care about, we work with passion with people we respect.

We are Data Jedis:

we work on hard problems and aim to deliver working solutions at scale. We don’t have time for politics, backbiting, gossiping, game playing or selfish behaviour. We work as one team with a mission to deliver and we will only achieve that together.