Data Engineers

Blue Pearl PTY LTD; Johannesburg; On-site; ZAR 900,000 - 1,500,000; Full time

Job summary

Blue Pearl PTY LTD in Johannesburg is seeking a data engineer to design and build scalable data platforms and modern lakehouse architectures.

You will develop and optimize data pipelines using Python and SQL, implement dbt, Databricks, and cloud components across AWS, Azure, and Google Cloud.

The role combines hands-on delivery with client engagement, mentoring, and contributing to technical strategy in a dynamic consulting environment.

Qualifications

• 3–5 years' experience in data engineering.
• Strong proficiency in Python and/or SQL, including query optimisation.
• Experience 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 major cloud platforms (AWS) and familiarity with Databricks, Snowflake, PySpark, dbt.
• Version control using Git and CI/CD practices for data workflows.
• Excellent communication and stakeholder engagement skills.
• 6–8+ years' experience in data engineering.
• Leading end-to-end data platform delivery; architecting lakehouse environments; IaC with Terraform/Bicep/AWS CDK/Pulumi; DevOps.

Responsibilities

• Design and build scalable data platforms using cloud-native and lakehouse architectures.
• Develop and optimise data pipelines using Python, SQL and tools like dbt and Databricks.
• Modernise legacy data environments migrating to cloud-native platforms (e.g., AWS, Azure, Google).
• Engage with clients to conceptualize data solutions aligned to business strategy.
• Provide guidance and mentorship to junior consultants.
• Lead technical reviews and contribute to growth plans.
• Identify opportunities to automate data workflows and improve scalability.
• Collaborate with stakeholders to address data infrastructure needs.

Skills

Python

SQL

Data engineering

Analytical thinking

Stakeholder communication

Education

Bachelor's degree in Computer Science

Bachelor's degree in Information Systems

Bachelor's degree in Information Technology

Master's degree

Tools

Databricks

Snowflake

Git

Terraform

AWS CDK

Pulumi

Bicep

dbt

PySpark

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