Data Engineers

Blue Pearl HQ

Johannesburg

On-site

ZAR 600,000 - 1,100,000

Full time

7 days ago

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Job summary

Blue Pearl HQ is seeking a seasoned Data Engineer to design scalable cloud-native data platforms and lead end-to-end data pipelines. You will work with Python/SQL, lakehouse architectures, and major cloud platforms to modernise ecosystems.

You'll engage clients, support pre-sales with PoCs, mentor colleagues, and drive automation and CI/CD for data workflows in a dynamic consulting environment.

Qualifications

3-5 years hands-on data engineering experience.
Strong Python and/or SQL with query optimisation.
Experience with relational and non-relational databases.
Design/build data pipelines and data models.
Knowledge of lakehouse architectures (medallion pattern).
Practical cloud platform experience (Azure/AWS/GCP).
Familiar with Databricks, Snowflake, Delta Lake, PySpark.
Understanding of dbt, Git, and CI/CD for data workflows.
Analytical, problem-solving, and stakeholder communication skills.

Responsibilities

Design and build scalable data platforms using cloud-native and Lakehouse architectures.
Develop and optimise data pipelines with Python and SQL; utilise ADF, Glue, Dataflow, Databricks, dbt.
Modernise legacy environments by migrating to cloud-native platforms (Azure, AWS, GCP, Databricks).
Engage with clients to conceptualise data solutions aligned to business strategy.
Support sales with pre-sales activities, PoCs, and technical proposals.
Mentor junior/intermediate consultants; lead technical reviews.
Identify opportunities to automate, improve data delivery and scalability.
Collaborate with executives, product, and analytics teams on data infra needs.

Skills

Python

SQL

PySpark

dbt

Education

Bachelor's degree in Computer Science/Information Systems/Information Technology or related field

Master's degree in a relevant field (advantageous)

Microsoft Fabric Data Engineer Associate

Microsoft Azure Data Engineer Associate

Databricks Certified Data Engineer Associate

Google Professional Data Engineer

AWS Certified Data Engineer - Associate

Databricks Certified Data Engineer Professional

Tools

Databricks

Snowflake

Delta Lake

Terraform

Azure Data Factory

AWS Glue

Google Dataflow

BigQuery

Databricks Workflows

Git

CI/CD pipelines

Job description

Key Responsibilities

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

Data Engineer Candidate Requirements

Intermediate Level

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:
- Microsoft Azure
- AWS
- Google Cloud Platform (GCP)
Familiarity with:
- Databricks
- Snowflake
- Delta Lake
- 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.

Senior Level

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.
- Implementing data mesh patterns.
- 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.
- Mentoring junior engineers.
- 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