Senior Data Engineer
MECS Africa · Johannesburg, South Africa ·
- Seniority
- Senior
- Category
- Data engineering
A senior data engineer ensuring the accuracy and reliability of data transformation processes for complex, high-volume insurance and financial services datasets. Day to day involves ingesting and transforming data with Microsoft SQL, validating outputs, and analysing large datasets using Excel (Power Query, Power Pivot) and Power BI.
If youâre 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:
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.
- 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.
- Bachelorâs degree in Science, IT, Actuarial Science, Data Science, or a related discipline.
- Minimum of four yearsâ 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.