Data Engineers

Blue Pearl PTY; Johannesburg; On-site; ZAR 800,000 - 1,200,000; Full time

Benefits offered by this job

None

Job summary

Blue Pearl PTY in Johannesburg is seeking a data engineer to design and build scalable data platforms using cloud-native and lakehouse architectures. You will develop data pipelines with Python, SQL, and tools such as Databricks, dbt, and Git.

You will lead end-to-end data platform delivery, mentor junior consultants, and collaborate with stakeholders to align data solutions with business strategy while practising CI/CD and IaC.

Qualifications

• 3–5 years of hands-on data engineering experience.
• Strong Python and SQL skills with query optimisation.
• Experience with relational and non-relational databases.
• Designing/building data pipelines and data models.
• Practical knowledge of lakehouse architectures and medallion pattern.
• Experience on AWS, Azure, Google Cloud or similar cloud platforms.
• Knowledge of Databricks, Snowflake, and dbt.
• Version control and CI/CD for data workflows.

Responsibilities

• Design and build scalable data platforms and pipelines.
• Engage with stakeholders to align data solutions with business strategy.
• Mentor junior and intermediate consultants.
• Lead end-to-end data platform delivery and architecture.
• Support pre-sales activities and technical proposals.
• Identify automation opportunities and optimise data delivery.
• Contribute to technical strategy and knowledge sharing.

Skills

Python

SQL

Data pipelines

Query optimisation

Cloud platforms

Git

Databricks

dbt

Spark (PySpark)

Leadership

Education

Bachelor's degree in Computer Science

Bachelor's degree in Information Systems

Bachelor's degree in Information Technology

Master's degree advantageous

Tools

Databricks

Snowflake

Terraform

AWS CDK

Pulumi

Microsoft Fabric

Azure Synapse

Google BigQuery

Git

Job description

Johannesburg, South Africa | Posted on 09/02/2026

You will be assigned a portfolio of client engagements where you will be expected to:

• Design and build scalable data platforms using modern cloud-native and Lakehouse architectures
• Develop and optimise data pipelines using Python, SQL, and tools such as Azure Data Factory, AWS Glue, Google Cloud Dataflow, Databricks, and dbt
• Modernise legacy data environments, migrating from on-premises solutions to cloud-native platforms such as Microsoft Fabric, Azure Synapse Analytics, AWS Redshift, Google BigQuery, or Databricks
• Engage with clients to conceptualize data solutions aligned to their business strategy
• Support our sales team with pre-sales activities, proof-of-concept deliveries, and technical proposals
• Provide technical guidance and mentorship to junior and intermediate consultants
• Lead technical reviews and contribute to consultants’ growth plans
• Identify opportunities to automate manual processes, optimise data delivery, and improve infrastructure scalability
• Work with stakeholders, including executive, product, and analytics teams, to address data infrastructure needs
• Drive knowledge sharing through technical blogs, internal forums, and workshops
• Balance billable project work with team support responsibilities

Requirements

• 3–5 years' experience
• 3–5 years of hands‑on experience in data engineering.
• Strong proficiency in Python and/or SQL, including query optimisation.
• Experience working with both relational and non‑relational databases.
• Experience designing and building data pipelines and data models.
• Understanding and practical experience with lakehouse architectures, including the medallion pattern.
• Practical experience with at least one major cloud platform, including:
• AWS
• Familiarity with:
• Databricks
• Snowflake
• PySpark
• Understanding of data transformation frameworks such as dbt.
• Experience with version control using Git.
• Understanding of CI/CD practices for data workflows.
• Strong analytical and problem-solving skills.
• Ability to perform root-cause analysis on complex data issues.
• Good communication and stakeholder engagement skills.
• 6–8+ years' experience
• 6–8+ years of hands‑on experience in data engineering.
• All intermediate‑level technical requirements, together with demonstrable experience in:
• Leading end‑to‑end data platform delivery.
• Architecting enterprise‑grade lakehouse environments.
• Infrastructure‑as‑code using tools such as Terraform, Bicep, AWS CDK or Pulumi.
• DevOps and CI/CD pipelines.
• Working effectively with cross‑functional teams in a dynamic consulting environment.
• Contributing to technical strategy and solution direction.

Qualifications

• Bachelor's degree in:
• Computer Science
• Information Systems
• Information Technology
• or a related field.
• Master's degree in a relevant field is advantageous.

Certifications

• One or more of the following certifications would be advantageous:
• Microsoft Fabric Data Engineer Associate
• Google Professional Data Engineer