Decision Inc

Data Engineer - DISA-DIA-DE-CT-0120

Decision Inc Cape Town, Western Cape, South Africa

Business Consulting and Services · 51-200 employees

4 d ago
data-engineer Mid (2-5 yrs) Full-time South Africa
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About the role

You will design and build scalable cloud-native data platforms and pipelines while leading delivery across diverse client engagements. Additionally, you will provide technical mentorship to junior consultants and support pre-sales activities through technical proposals and proof-of-concept deliveries.

What they look for

Python SQL Azure Data Factory AWS Glue Google Cloud Dataflow Databricks Dbt Microsoft Fabric Azure Synapse Analytics AWS Redshift Google BigQuery Data Engineering Cloud-native architectures Lakehouse architectures Git CI/CD

Requirements

Candidates must have 3–5 years of hands-on data engineering experience with strong proficiency in Python and SQL. A bachelor's degree in a relevant technical field is required, along with practical experience in cloud platforms like Azure, AWS, or GCP.

Full description

Decision Inc. is seeking talented Data Engineers to join our Data, Information, and Analytics practice as client-facing consultants. You will design and build modern data platforms, lead delivery across diverse industries, and help our clients become genuinely data-driven businesses.

You will work across the full engineering lifecycle, from architecture and pipeline development to mentoring junior colleagues and contributing to pre-sales engagements. A passion for data, a curiosity for new technologies, and the ability to adapt quickly to different business environments are essential.

About Decision Inc.

Decision Inc. is a global management and technology consulting organisation. We help companies become Data Driven Businesses that are fit to take on the challenges of a digital world. Transforming their current operations and developing their new business platforms to scale innovation into the future. Our experience in leading technology and industry specialisations have enabled us to help companies to make better decisions, faster. We represent the leading technology brands and are experts in the implementation, support and execution of these technologies.

What You Will Do

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 conceptualise 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

What We Are Looking For

  • 3–5 years of hands-on experience in data engineering
  • Strong proficiency in Python and/or SQL, including query optimisation and working with both relational and non-relational databases
  • Experience designing and building data pipelines, data models, and lakehouse architectures (medallion pattern)
  • Practical experience with one or more cloud platforms: Microsoft Azure (Data Factory, ADLS Gen2, Synapse Analytics, Fabric), AWS (Glue, S3, Redshift, EMR), or GCP (Dataflow, BigQuery, Cloud Storage, Dataproc)
  • Familiarity with Databricks, Snowflake, Delta Lake, and PySpark
  • Understanding of data transformation frameworks such as dbt
  • Experience with version control (Git) and CI/CD practices for data workflows
  • Strong analytical skills and the ability to perform root cause analysis on complex data problems
  • Good communication and stakeholder engagement skills

Qualifications

  • Bachelor's degree in computer science, Information Systems, Information Technology, or a related field
  • A master's degree in a relevant field is advantageous

Ideal Certifications

Primary certifications – one or more:

DP-700

Microsoft Fabric Data Engineer Associate

DP-203

Microsoft Azure Data Engineer Associate

Databricks DE Associate

Databricks Certified Data Engineer Associate

Google Professional

Professional Data Engineer (GCP)

AWS DEA-C01

AWS Certified Data Engineer – Associate

Databricks DE Professional

Databricks Certified Data Engineer Professional

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