Requirements: 

Data Engineering & Cloud Solutions
Architect, build, and optimize scalable and cloud-agnostic data solutions
using Azure, Databricks, Spark, Lakehouse, and Delta Lake tables.
Develop, implement, and maintain big data pipelines for ingesting, processing, and
storing large volumes of structured and unstructured data.
Manage and optimize data lake and data warehouse architectures for performance,
cost, and scalability

Cloud & DevOps
Work within Azure environments (Azure Synapse, Data Factory, ADLS, etc.) to
develop and maintain cloud-based data solutions.
Implement best DevOps practices for CI/CD pipelines, infrastructure-as-code, and
automation.
Utilize Azure DevOps and Git for managing code repositories, version control, and
continuous integration/deployment.
Ensure high levels of security, compliance, and data governance across data
engineering processes.

Big Data Processing & Development
Utilize Spark, Databricks, and distributed computing to process and analyse large
datasets efficiently.
Write advanced Python and T-SQL scripts for data transformations, ETL/ELT
processes, and real-time data processing.
Optimize performance for data pipelines and SQL queries for efficiency and costeffectiveness.
Experience with Graph databases is a big advantage

Collaboration & Leadership
Work closely with data scientists, analysts, and business stakeholders to understand
data requirements and develop solutions that meet business objectives.
Lead initiatives to enhance data engineering capabilities, introduce new
technologies, and drive best practices.
Mentor junior engineers, conduct code reviews, and contribute to building a culture
of technical excellence.
Communicate effectively with technical and non-technical stakeholders, translating
complex data concepts into actionable insights.

Requirements: 

6+ years of extensive experience.
Education / Degrees: Computer science degree or comparable data engineering certification
in one of the cloud platforms.

Minimum required skills and experience:
Extensive experience in cloud-based data engineering, with expertise in Azure (Azure
Synapse, Azure Data Factory, ADLS, etc.).
Strong expertise in cloud-agnostic data tools such as Databricks, Spark, Delta Lake, and
Lakehouse architectures.
Advanced proficiency in T-SQL and Python for developing complex data pipelines,
transformations, and optimizations.
Hands-on experience in big data processing, ETL/ELT, and data pipeline orchestration.
Solid understanding of data modelling, warehouse design, and data lakehouse architecture.
Experience in setting up, managing, and processing with Azure DevOps (or similar DevOps
tools).
Strong knowledge of DevOps, CI/CD, Git, and infrastructure-as-code for automated
deployments.
Excellent verbal and written communication skills, with the ability to collaborate across
teams and explain complex data concepts clearly.
Ability to work independently on high-impact projects while maintaining a team-oriented
approach.

Interested applicants should submit their CV to Gaby Turner at *****@*****.co.za or you may forward your CV directly to the IT Department at *****@*****.co.za