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Job Title: Cloud Data Engineer (AWS Big Data)
Location: Sandton (Hybrid)
Type: Permanent

We are looking for a Cloud Data Engineer with strong AWS expertise to join our growing data team. The role focuses on building and supporting scalable big data solutions in the cloud, ensuring performance, reliability, and compliance across ETL and data warehouse environments.



Key Responsibilities



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Design, develop, and support ETL pipelines and big data solutions using AWS services such as Glue, Athena, Redshift, Airflow, Lake Formation, and S3.
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Optimise data flows for performance, cost, and scalability, ensuring efficient data transformations and storage.
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Troubleshoot and resolve operational issues using AWS monitoring and logging tools (CloudWatch, CloudTrail, X-Ray).
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Contribute to the migration of on-premises and legacy data solutions into AWS cloud-based architectures.
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Collaborate with data analysts, engineers, and cloud specialists to ensure compliance with governance and regulatory requirements.
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Provide guidance on AWS best practices and mentor junior engineers when needed.



Skills & Experience



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Proven experience as a Cloud/Data Engineer or Support Engineer working with large-scale data solutions.
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Strong AWS background, ideally with hands-on experience in Glue, Athena, Airflow, Redshift, S3, and Lake Formation.
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Solid understanding of ETL design, data warehousing concepts, and performance tuning.
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Experience with SQL, SSIS, Oracle, or other data integration tools.
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Exposure to banking, risk, or compliance data environments is advantageous.
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Strong problem-solving skills, with the ability to work in a fast-paced, customer-focused environment.



What's on Offer



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Opportunity to work with cutting-edge cloud data technologies.
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Hybrid working model with flexibility.
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Career growth in a collaborative and supportive environment.

Data Engineer - Automotive

We are looking for a skilled Data Engineer to help design and build the next generation of data platforms that power large-scale telematics, IoT, and fleet-management systems. In this role, you will work with high-volume, real-time data generated from connected devices, vehicles, sensors, and safety systems, and help transform this data into reliable, accessible, analytics-ready products.

You will play a key part in modernising our data ecosystem across Azure and AWS, enabling scalable ingestion, advanced analytics, machine learning, and real-time operational insights for internal teams and enterprise clients.

What You'll Do

Core Responsibilities

* Design and build cloud-native data pipelines for high-velocity telematics and IoT data using Azure and AWS services.
* Develop and maintain data lake / lakehouse architectures (S3, ADLS, Delta Lake, Iceberg).
* Implement streaming and batch processing frameworks using tools such as Spark, Databricks, Kinesis, Event Hub or Kafka.
* Build reliable ETL/ELT jobs for preparing and curating bronze/silver/gold datasets.
* Support real-time analytics, including geofencing, driver behaviour analysis, alerting, and operational monitoring.
* Create and maintain data APIs, microservices, and integrations for internal teams and external partners.
* Work closely with ML engineers to enable feature stores, training datasets, and productionised ML workflows.
* Implement robust data governance, POPIA compliance, lineage, and access controls across the data environment.
* Participate in the modernisation and migration of legacy data systems to cloud platforms.
* Optimise for reliability, cost efficiency, performance, and scalability.

What You'll Bring

Essential Skills

* Experience building data platforms on both Azure and AWS.
* Strong skills in Python, SQL, and distributed processing frameworks (e.g., Spark).
* Hands-on expertise with:

* Azure Data Factory, Event Hub, Databricks, ADLS
* AWS Glue, S3, Lambda, Kinesis, API Gateway

* Experience with streaming architectures and real-time data processing.
* Understanding of data lakehouse design, metadata management, and data modelling.
* Familiarity with IoT or telematics-style data (high-volume events, time-series data) is a strong advantage.

Nice to Have

* Knowledge of containerisation (Docker, Kubernetes).
* Experience with infrastructure-as-code (Terraform, CloudFormation, Bicep).
* Exposure to ML pipelines, driver scoring, or predictive maintenance models.
* Background in fleet, IoT, logistics, telecoms, or similar data-heavy industries.

What We Offer

* Work on high-impact, real-time data systems used by thousands of businesses and millions of devices.
* Opportunities to innovate within cloud, IoT, telematics, and AI-driven analytics.
* A modern engineering environment with autonomy, collaboration, and continuous learning.
* Competitive salary, benefits, and growth opportunities.

Be part of a forward-thinking environment dedicated to customer value!

We are seeking a Data Scientist to join a dynamic team in Sandton, focusing on enhancing customer value streams. This permanent, hybrid position offers a unique opportunity to apply your machine learning expertise while contributing to impactful projects within the Data Science team. The expected start date for this role is November 1, 2025.

Key Responsibilities and Skills Required:

- SAS, AWS, BedrockAI, SQL, Python
- Proficient in machine learning techniques and methodologies.
- Experience in data analysis and interpretation, driving data-driven decisions.
- Ability to collaborate with cross-functional teams to optimise customer value streams.
- Strong problem-solving skills and innovative thinking in a fast-paced environment.
- Excellent communication abilities to convey complex insights to non-technical stakeholders.

This is an excellent opportunity for candidates looking to make a meaningful impact in a collaborative setting. If you are passionate about leveraging data to enhance customer experiences and meet business goals, we encourage you to apply for this role. Your insights and expertise can shape the future of customer value at our client's company.

About the Role

We're seeking an experienced AI Engineer to lead the design and implementation of AI-driven solutions within a complex enterprise environment. This is a strategic role requiring strong technical depth and the ability to influence architecture decisions at an enterprise level. You'll work closely with senior stakeholders to shape AI road maps and deliver impactful solutions.



Key Responsibilities:



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Consulting & Advisory:

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Assess and prepare data sources for AI readiness, including APIs.

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Provide strategic guidance on business process improvement using generative AI.

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Implementation & Integration:

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Deploy AI capabilities leveraging Microsoft technologies such as Copilot Studio (Lite & Full) and Azure AI Foundry.

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Integrate AI solutions into Dynamics 365 (D365) environments.

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Architecture & Strategy:

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Lead architecture discussions and create solution roadmaps from scratch.

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Ensure data readiness and security for AI applications, including cybersecurity considerations.

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Cross-Platform Expertise:

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Evaluate and incorporate AI offerings beyond Microsoft's ecosystem (AWS Bedrock, GCP).

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Explore model concept protocols and multi-cloud strategies



What We're Looking For

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Solid technical foundation with senior-level C# development experience.

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Strong understanding of AI architecture, data integration, and Azure AI Foundry.

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Ability to hold your own in architecture discussions and communicate complex ideas clearly.

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Experience in enterprise environments, ideally banking or large corporate settings.

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Familiarity with Dynamics 365, Copilot Studio, and generative AI applications.

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Bonus: Knowledge of AWS Bedrock, GCP, and data security best practices for AI.



Why This Role?

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Full-time allocation to a major enterprise AI initiative.

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Opportunity to influence strategic decisions and work on cutting-edge AI projects.

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Join a team that's ahead of the curve in implementing AI solutions at scale.

Principal Machine Learning Engineer - Johannesburg (Hybrid) / Cape Town (Remote)

Full-time | Permanent

A leading technology and data-driven organisation is looking for an exceptional Principal Machine Learning Engineer to join their Intelligent Data team. This is a senior, high-impact role driving the architecture, strategy, and delivery of advanced AI and machine learning systems.



The Opportunity

You will provide both technical and strategic leadership, shaping the next generation of real-time AI solutions. The team builds high-performance, production-grade systems with a strong emphasis on engineering excellence, governance, and scalable design.

Examples of the types of projects you may contribute to include:

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Real-time fraud prevention systems analysing behavioural and financial signals to stop fraudulent transactions instantly.
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Advanced event-driven telemetry solutions processing real-time device data to reduce false alerts and automate critical decisioning.
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Cutting-edge LLM-based initiatives within an organisation with several years of production experience in applied generative AI.

This role suits a hands-on engineering leader who is passionate about building robust platforms, driving ML strategy, and inspiring a world-class technical team.

Key Responsibilities

Technical & Architectural Leadership

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Lead the design and architecture of complex, real-time, scalable ML systems.
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Resolve advanced engineering challenges and guide high-level architectural decisions.
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Provide deep expertise in data streaming and event-driven tooling.
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Evaluate new technologies and keep the practice at the forefront of industry innovation.

Strategic Contribution

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Partner with leadership to define and evolve ML strategy and platform direction.
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Research emerging tools and trends (LLMs, Generative AI, AI assistants) and apply them to real use cases.

Team Leadership & Mentorship

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Coach, mentor, and uplift a high-performing technical team.
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Drive best practices, code quality, and engineering excellence.

Thought Leadership & Communication

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Represent the ML discipline effectively, presenting to internal and external audiences.
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Contribute to content, talks, and community engagement.

Ideal Candidate Profile

This individual is a rare combination of technical depth, architectural thinking, leadership, and communication excellence.

Non-negotiables:

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Hands-on ML Engineer: Proven track record building full end-to-end ML and AI application ecosystems.
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Streaming & Platform Expertise: Strong experience with Kafka, Flink, Beam, or similar.
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Multi-cloud engineering: Strongest in AWS, with exposure to GCP and Azure.
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Technical versatility: Deep experience across Python, Go, Java, C#, or similar languages.
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Leadership: Demonstrated ability to mentor, lead, and inspire engineering teams.
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Communication: Ability to translate complex concepts for both technical and non-technical audiences; public speaking or content creation a plus.

Technical Skill Matrix

CategoryTechnologies / Concepts
Cloud PlatformsAWS, GCP, Azure
Data StreamingKafka, Flink, Beam
ProgrammingPython, Go, Java, C#, JavaScript
ArchitectureMicroservices, Event-Driven Architecture, Kubernetes, Docker
Data & MLStructured & unstructured data, semi-supervised learning, ML ops tooling
DatabasesSQL (MS SQL, MySQL), NoSQL (MongoDB), Graph (Neo4j)
ProcessAgile (Scrum, Kanban)

We're working with an organisation that is building out its data function from the ground up. With recent international investment, they're scaling quickly and are focused on transforming their analytics capability into a premium driver of business decisions.

They are currently looking to add another Data Scientist to an innovative, cutting-edge, brand new department.



What you'll be doing:



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Supporting the product development and analytics teams with automated reporting solutions
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Analysing demographic data to support service bundling and increase product premium potential
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Utilising SAS and AWS for predictive modelling and lifetime value modelling.
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Structuring, problem-solving, and working cross-functionally to deliver insights that drive business decisions
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Contributing to a relatively new team (you'll be joining a highly capable team member already in place) with a large project backlog and opportunity for growth



Tech environment:



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SAS
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AWS
* Machine Learning (BedRock)
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Python



What they're looking for:



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A solutions-oriented mindset - if you see problems everywhere, this won't be the right environment
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Curiosity and willingness to learn - sector experience (retail) is not essential, but it is nice to have.
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A genuine interest in turning data into actionable business insights



Hiring Process:



1

Introductory coffee chat
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Formal interview
3

Remote technical assessment



Other Details:



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Hybrid working: 3 days in office, Sandton
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Clear and fast-moving interview process
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Company is scaling fast - lots of autonomy, not a place for micromanagement



If you're looking for a hands-on opportunity to build something meaningful from the ground up, let's chat.