Data Engineer

ADG; Johannesburg; On-site; ZAR 900,000 - 1,500,000; Full time

Job summary

ADG in Johannesburg seeks an experienced Data Engineer to join our Data and AI practice. You will design, build, and lead robust batch and streaming data pipelines on GCP and open-source ecosystems, delivering value to clients and our business.

You will drive project delivery, mentor junior engineers, and apply GenAI concepts to real-world data challenges, ensuring scalable, reliable solutions across the data stack.

Qualifications

• 7+ years of proven industry experience in data engineering, data architecture, and enterprise software systems.
• A Computer Science (or equivalent) degree, or equivalent practical experience.
• Deep expertise in modern cloud architectures and GCP data engineering services for designing resilient batch and streaming pipelines.
• Exceptional, hands-on proficiency in Python, SQL, and Apache Spark, as well as data management concepts.
• Deep understanding of diverse data architectures, Hadoop, distributed computing, cloud-native databases, data lakehouses, and analytics.
• Strong grasp of Generative AI (GenAI) technologies and their business applications.

Responsibilities

• Lead the design and delivery of robust batch and real-time data pipelines on GCP and open-source ecosystems.
• Drive technical accountability, timelines, and high-quality outcomes aligned with client goals.
• Mentor junior engineers and guide technical discussions and POC development.
• Translate complex architectures into business value and opportunities for service improvements.

Skills

Python

SQL

Apache Spark

Education

Bachelor's degree in Computer Science or equivalent

Tools

BigQuery

Cloud Dataflow

Cloud Storage

Pub/Sub

Cloud Dataproc

Cloud Composer

Dataplex

Job description

We are seeking an experienced, energetic, and highly motivated Data Engineer to join our dynamic organisation. This role forms part of our Data and AI practice within our Data Engineering Team. You will be a lead part of a team of Data and AI practitioners delivering amazing technical solutions to our customers and our own business.

This position demands a high level of expertise in Data Engineering technologies, particularly across the Google Cloud Platform (GCP) data stack and open-source big data ecosystems, a deep understanding of business contexts, and a strong motivation to innovate and lead. ADG is not a place for being still; this is an environment where you bring your energy and ideas, and we help you translate them into tangible solutions which drive real value.

The successful candidate will be expected to deliver excellence across three core pillars:

What we expect from you:

Technical Mastery and Execution:

At ADG we believe in mastery. We expect you to bring a wealth of experience to the table, specifically in architecting and building robust, scalable batch and real-time streaming pipelines. You must possess a deep understanding of cloud-native data ecosystems, open-source big data specifications, and distributed computing, while also staying at the forefront of GenAI technologies to solve complex, modern problems.

Project Leadership and Delivery:

You will take leading roles in project delivery, ensuring that technical solutions are successfully executed from concept to production. We expect you to drive accountability, manage complex technical timelines, and ensure high-quality outcomes that align with our clients' strategic goals.

Business Acumen and Initiative:

At ADG, we are always improving. We expect you to go beyond the code to deeply understand the underlying business challenges our customers face and translate complex technical architectures into business value. If you see an opportunity for us to improve our services, architectures, or internal systems, speak up and take the initiative to drive that change.

Mentorship and Skills Development:

We believe in staying certified and ahead of the curve on technologies our customers use and want. This means we expect you to continuously refine your own skills, while also stepping up to mentor junior engineers, guide technical discussions, lead the development of Proof of Concepts (POCs), and elevate the overall capability of our Data practice.

What you can expect from us:

Technology Stack.

At ADG we adapt to what our customers need. This coalesces around a robust set of data engineering technologies, with a heavy focus on the Google Cloud Platform (e.g., BigQuery, Cloud Dataflow, Cloud Storage, Pub/Sub, Cloud Dataproc, Cloud Composer) combined with core open-source big data specs (Apache Spark, Hadoop, Python, SQL) and an eye toward Generative AI frameworks. But we’re always learning more!

A platform for impact.

We provide a supportive environment that values your senior expertise from day one. You’ll be given the space and resources to architect innovative data solutions, lead complex projects, and have a direct, tangible impact on our customers' success in a forward-deployed environment.

A culture which values your journey.

At ADG, we believe in autonomy, mastery, and purpose. We trust you to bring your best self to ADG and pursue continuous growth. We provide interesting and challenging work which assists that. We are a very collaborative organisation, which means you’ll find colleagues who support each other, brainstorm together, and build together.

Requirements of this role:

At least 7 years of proven industry experience in data engineering, data architecture, and enterprise software systems.

A Computer Science (or equivalent) degree, or equivalent practical experience.

Deep expertise in modern cloud architectures and GCP data engineering services (e.g., BigQuery, Cloud Dataflow, Cloud Storage, Pub/Sub, Cloud Dataproc, Cloud Composer, and Dataplex) for designing resilient batch and streaming pipelines.

Exceptional, hands-on proficiency in core Data Engineering technologies, specifically Python, SQL, and Apache Spark, as well as key Data Management concepts.

Deep understanding of diverse data architectures (e.g., open-source Big Data ecosystems, Hadoop, distributed computing, cloud-native databases, enterprise data lakehouses, and advanced analytics).

A strong foundational grasp of both traditional data engineering paradigms and modern Generative AI (GenAI) technologies.