Data Engineer (Senior)

Parvana

Job Location:

Cape Town - South Africa

Monthly Salary: Not Disclosed

Posted on: 8 days ago

Vacancies: 1 Vacancy

Job Summary

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.

For a more comprehensive list of opportunities that we have on offer do visit our website - 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

Required Skills:

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

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...

About our client:

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.

Required Skills:

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