Job Description
About our client:
Our client, a reputable financial services firm listed on the Johannesburg Stock Exchange (JSE), holds a strong belief in the transformative power of incremental progress. They are committed to empowering individuals and businesses alike, offering tailored solutions and expert guidance to help pave the way to success. With a focus on innovation and excellence, they provide secure financial futures through personalised advice and cutting-edge products. Their mission is to support diverse goals and aspirations, enriching lives across every journey.
What you will be doing:
Design scalable relational and analytical data models, building structures optimised for both operational (OLTP) and reporting (OLAP) workloads.
Build and maintain robust data ingestion and transformation processes, developing reliable ETL/ELT pipelines to integrate data from diverse internal and external systems.
Analyse execution plans, troubleshoot performance issues, and implement advanced indexing, partitioning, and optimization strategies to resolve bottlenecks in high-volume workloads.
Define and enforce engineering standards for naming conventions, database design, and documentation; lead code reviews to ensure quality and consistency.
Work closely with application developers, BI teams, and stakeholders to support data requirements while mentoring junior developers on data engineering practices.
Maintain rigorous, high-quality technical documentation and log changes to ensure infrastructure transparency and auditability.
What our client is looking for:
6 - 10+ years of hands-on experience in complex query development and data engineering.
Expertise in SQL (T-SQL/PL-SQL), complex stored procedures, views, functions, and query optimization.
Advanced experience in normalised relational models (3NF) and dimensional models (star/snowflake schemas).
Deep knowledge of indexing strategies, partitioning, statistics, and transaction management (locking, deadlocks).
Proficiency in pipeline design using tools like Azure Data Factory (ADF), SSIS, dbt, or Apache Airflow.
Proficiency in Python, Java, or Scala for data manipulation and scripting.
Experience with cloud data services such as Azure (Synapse, Fabric), AWS (Redshift, S3), or GCP (BigQuery).
Familiarity with version control (Git), Azure DevOps/GitHub Actions, and CI/CD pipelines.
Experience with Databricks for data engineering and analytics workloads.
Advanced critical thinking and debugging abilities to resolve complex data issues.
Ability to interpret business requirements and translate them into effective technical solutions for stakeholders.
Requirements
Data Engineering, SQL (T-SQL, PL-SQL), Azure, Python, Java, Scala, Databricks, ETL/ELT, Pipelines, Data Modelling, Cloud Services (Azure/AWS/GCP), CI/CD, Git, Analytics, Performance Tuning
