Senior Data Engineer

MECS Africa; South Africa; On-site; ZAR 700,000 - 1,000,000; Full time

Job summary

MECS Africa is seeking a detail-oriented Data Engineer to ensure accuracy and reliability of data transformations across large insurance and financial services datasets. You will ingest, transform, and validate data using SQL and BI tools.

You will collaborate with stakeholders, manage multiple input systems (e.g., DINO, local SQL databases), and apply rigorous checks to deliver validated outputs for business teams.

Qualifications

• Bachelor's degree in Science, IT, Actuarial Science, Data Science or related field.
• Minimum of four years’ relevant professional experience in data analysis, data management, or business intelligence.
• Ability to work independently with strong attention to detail.
• Excellent communication and interpersonal skills to work effectively with both technical and non-technical stakeholders.

Responsibilities

• Understand and work with existing team data processes, tools, and frameworks.
• Support data transformation from multiple input systems (e.g., DINO, local SQL databases) into concise, validated outputs for business teams.
• Perform thorough validation and verification checks to ensure data accuracy and completeness.
• Identify, document, and communicate data errors clearly and concisely.
• Collaborate with the data team to implement and track solutions for data issues.

Skills

Microsoft SQL

Power BI

Power Query

Power Pivot

Excel

Education

Bachelor’s degree in Science/IT

Job description

If you’re a detail-oriented data professional with strong SQL and Power BI skills who enjoys working with complex, high-volume datasets, this role is worth serious consideration and offers meaningful exposure to enterprise-level data within the insurance and financial services sector.

Role Overview:

As a Data Engineer, you will play a crucial role in ensuring the accuracy, completeness, and reliability of data transformation processes. You will work closely with colleagues to deliver validated, actionable outputs from complex datasets.

Key Responsibilities:

• Understand and work with existing team data processes, tools, and frameworks.
• Support data transformation from multiple input systems (e.g., DINO, local SQL databases) into concise, validated outputs for business teams.
• Perform thorough validation and verification checks to ensure data accuracy and completeness.
• Identify, document, and communicate data errors clearly and concisely.
• Collaborate with the data team to implement and track solutions for data issues.

Technical Requirements & Expertise:

• Strong proficiency in Microsoft SQL for data ingestion, transformation, and analysis.
• Advanced skills in Microsoft Excel, including Power Query, Power Pivot, and Power BI.
• Ability to organise, manipulate, and analyse large datasets.
• Knowledge of life insurance products is advantageous.

Qualifications & Background:

• Bachelor’s degree in Science, IT, Actuarial Science, Data Science, or a related discipline.
• Minimum of four years’ relevant professional experience in data analysis, data management, or business intelligence.
• Ability to work independently with strong attention to detail.
• Excellent communication and interpersonal skills to work effectively with both technical and non-technical stakeholders.
• Ability to work under pressure and meet deadlines in a fast-paced environment.