About the Role
Our client is seeking a highly experienced Senior AI Data Engineer to join their expanding data science team in Sandton. You will play a critical role in designing, building, and maintaining the data infrastructure required for advanced AI and machine learning applications. This position involves working with large, complex datasets, ensuring data quality, and optimizing data pipelines to support data scientists and ML engineers. Become a key contributor to data-driven innovation within a leading organization in Gauteng.
Key Responsibilities
- Design, develop, and optimize scalable data pipelines for AI and machine learning projects.
- Implement and manage data warehousing solutions and data lakes, ensuring data integrity and accessibility.
- Collaborate with data scientists and ML engineers to understand data requirements and deliver robust data solutions.
- Develop and maintain data governance policies and ensure compliance with data privacy regulations.
- Monitor data infrastructure performance, troubleshoot issues, and implement improvements for efficiency and reliability.
Requirements
- Bachelor's or Master's degree in Computer Science, Engineering, or a related quantitative field.
- 5+ years of experience in data engineering, with a focus on supporting AI/ML workloads.
- Strong proficiency in SQL, Python, and data processing frameworks (e.g., Spark, Hadoop).
- Experience with cloud data services (AWS Redshift, Azure Data Lake, Google BigQuery).
- Solid understanding of ETL/ELT processes and data modeling techniques.
Benefits
- Competitive salary and comprehensive benefits package.
- Opportunity to work on impactful AI and data initiatives.
- Professional development and continuous learning opportunities.
- Hybrid work model providing flexibility and work‑life balance.
- Dynamic team environment in the heart of Sandton.
About the Role
This role is ideal for someone who sits between Data Engineering and Analytics, with a solid understanding of data engineering principles, and an equal comfort with exploring datasets, investigating data quality, performing analysis, and translating business questions into meaningful data outputs.
What You’ll Be Doing
- Perform exploratory data analysis (EDA) and validate datasets.
- Use Python extensively for data analysis, investigation and problem‑solving.
- Work with real‑world and imperfect datasets to identify patterns, issues and insights.
- Support analytics, reporting and insight‑driven initiatives.
- Translate client and business questions into clear data outputs and findings.
- Apply data engineering best practices to ensure data is reliable and fit for analytical use.
- Investigate data and communicate findings clearly to both technical and business stakeholders.
- Engage with stakeholders to understand analytical requirements and provide data‑driven solutions.
What We’re Looking For
- 2+ years’ experience in a Data Engineering, Analytics Engineering or similar data‑focused role.
- A solid foundation in data engineering concepts.
- Strong hands‑on experience working with data for analysis and insight generation.
- Strong Python skills, particularly pandas and NumPy.
- Experience performing data exploration, investigation and validation.
- Comfortable working with complex, imperfect or inconsistent datasets.
- Strong problem‑solving abilities and an analytical mindset.
- The ability to interpret data within a business and client context.
- Strong communication skills, with the ability to explain data findings clearly.
About the Company
LexisNexis Legal & Professional® provides legal, regulatory, and business information and analytics that help customers increase their productivity, improve decision‑making, achieve better outcomes, and advance the rule of law around the world. As a digital pioneer, the company was the first to bring legal and business information online with its Lexis® and Nexis® services.
About the Role
This role supports Global Operations by designing, building, and maintaining reliable data pipelines and platforms. You will enable high‑quality analytics and AI‑ready data while improving automation, performance, and scalability. The role involves close collaboration with technical and business partners and encourages the responsible use of AI‑assisted engineering practices.
Key Responsibilities
- Design, build, and maintain scalable data pipelines and integrations that support analytics and AI use cases.
- Develop high‑quality, well‑tested code that follows best practices for readability, security, and maintainability.
- Use SQL as a primary tool to query, transform, validate, and optimize data across systems.
- Collaborate with technical and business partners to understand data needs and translate them into practical data solutions.
- Document data requirements and contribute to specifications for analytics and AI‑enabled workflows.
- Troubleshoot and resolve data issues through root cause analysis and appropriate automation or tooling.
- Identify opportunities to improve efficiency through automation, orchestration, or AI‑assisted processes.
- Participate in code reviews and development processes that promote reproducibility, transparency, and data quality.
- Support database and data flow management to ensure systems meet organizational standards for reliability and AI readiness.
- Stay current with evolving data engineering, automation, and AI practices and apply relevant learnings to your work.
Required Skills and Experience
- Professional experience in data engineering, data management, or a related technical role.
- Strong, hands‑on SQL expertise required, including writing complex queries, performance tuning, and data validation.
- Experience with data modeling, file management, and data transformation workflows.
- Working knowledge of at least one additional programming or scripting language (such as Python, Java, or similar).
- Experience with databases, data platforms, or cloud services (for example, AWS, Azure, GCP, Redshift, or Teradata).
- Familiarity with version control, testing, and core software development practices.
- Strong problem‑solving skills and clear, collaborative communication.
- Experience with ETL/ELT processes or general workflow orchestration concepts.
- Exposure to AI, machine learning, or data automation tools and practices.
- Experience with data visualization tools (such as Tableau or similar).
- A bachelor’s degree in a related field or equivalent practical experience. We welcome candidates from non‑traditional educational and career paths.
Benefits
- Competitive salary and performance-based bonuses.
- Hybrid work model providing a balance of in‑office and remote work.
- Comprehensive health, dental, and retirement benefits.
- Opportunities for professional development, certifications, and attending conferences.
- A collaborative and innovative workplace culture.
Work Culture
We promote a healthy work/life balance across the organisation. We offer an appealing working prospect for our people. With numerous wellbeing initiatives, shared parental leave, study assistance and sabbaticals, we will help you meet your immediate responsibilities and your long-term goals.
Working Pattern
Working flexible hours – flexing the times when you work in the day to help you fit everything in and work when you are the most productive.
Accessibility
We are committed to providing a fair and accessible hiring process. If you have a disability or other need that requires accommodation or adjustment, please let us know by completing our Applicant Request Support Form or please contact us.
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Equal Opportunity
We are an equal opportunity employer: qualified applicants are considered for and treated during employment without regard to race, color, creed, religion, sex, national origin, citizenship status, disability status, protected veteran status, age, marital status, sexual orientation, gender identity, genetic information, or any other characteristic protected by law.