Data/Systems Analyst
Absa
n/a - n/a
R700–750 per hour
Auckland Park, City of Johannesburg Metropolitan Municipality, 2092
Contract
Data Engineer
Role
This role operates at an intermediate level, supporting the understanding of source systems and independently preparing data so that it is structured, consistent, and fit for analytical use. The role applies established data principles and works with big‑data and low‑code platforms to ingest, standardize, and transform data for downstream consumption.
Key Responsibilities
- Independently analyse and understand source systems, including data structures, semantics, and business meaning
- Translate raw source data into well‑structured and consistent datasets aligned to defined analytical and reporting requirements
- Apply and enforce core data concepts and standards, including:
- Consistent and meaningful column naming conventions
- Use and management of reference and lookup data
- Correct application of joins and relationships across datasets
- Design, build, and maintain data pipelines using an in‑house low‑code development environment
- Perform data analysis using SQL and related query tools
- Use guided or low‑code big data tools to support data ingestion, transformation, and standardisation at scale to build data pipelines
- Ensure datasets comply with agreed standards for quality, consistency, reusability, and reliability
- Produce and maintain data documentation, including definitions, assumptions, and lineage
- Collaborate with data engineers, analysts, and platform teams to resolve data issues and improve data structures
Required Knowledge and Skills
- Practical, hands‑on experience with foundational data concepts, including:
- Relational data models and schemas
- Keys, joins, and data relationships
- SQL for complex queries and transformations
- Experience working with large or complex datasets on modern data platforms (platform‑agnostic)
- Applied knowledge of reference data and data standardisation practices
- Working understanding of cloud and technical concepts, including AWS storage, compute, and data access patterns
- Experience using low‑code or guided data tooling alongside traditional query‑based approaches
Nice to Have
- Experience working within a data lake, data warehouse, or similar analytical environment
- Exposure to regulated or enterprise data environments
- Familiarity with data quality controls, validation techniques, and issue resolution processes
Personal Attributes
- Analytical and detail‑oriented, with the ability to work independently
- Comfortable operating between technical data structures and business context
- Able to collaborate effectively across engineering, analytics, and business teams
- Methodical, disciplined, and consistent in applying data standards
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