Legal jobs in South Africa

The Company: Dotdigital is a thriving global community of passionate, dedicated professionals, committed to the collective success of the organization and its clients. Our core principles of innovation, teamwork, and client-focused solutions drive us to approach challenges with a growth mindset and take ownership of our work. At Dotdigital, collaboration and curiosity pave the way for meaningful connections and learning opportunities with diverse peers. Our work environment encourages knowledge sharing, fosters exploration, and cherishes creative ideas. Combined, these guide us towards a shared vision in which brands around the world exceed customer expectations through the adoption of responsible marketing practices.

The Product: Dotdigital is an all-in-one customer experience and data platform (CXDP) that empowers marketing teams to exceed customer expectations with highly personalized cross-channel journeys. With Dotdigital, marketers can seamlessly unify, enrich, and segment customer data. Breaking down data silos, Dotdigital streamlines decision-making and paves the way for marketing creativity that delivers customer engagement at scale. With powerful AI capabilities, Dotdigital makes it easy to automate deeply personalized experiences across web, email, SMS, WhatsApp, chat, push, social, ads, and more.

We’re looking for a highly skilled Machine Learning Engineer to join our data and analytics team. You’ll design, build, and optimize scalable, high-performance data pipelines and ML workflows on Databricks, leveraging PySpark, Unity Catalog, and modern data lake house technologies such as Delta Lake and Apache Iceberg. This is an exciting opportunity to shape our ML infrastructure and production pipelines, working at the intersection of data engineering and applied machine learning. We supply our customers with an array of predictive data science models. We do this for all of our customers meaning we train and execute 1000’s of models that are uniquely configured to provide tailored results.

• Architect and implement high-throughput data pipelines using PySpark on the Databricks platform to support large-scale ML workloads.
• Develop and operationalise ML workflows and model pipelines leveraging industry-leading frameworks and MLOps practices.
• Drive data governance and metadata management via feature stores to ensure data quality, lineage and compliance.
• Work with modern data lake house storage formats such as Delta Lake and Apache Iceberg to deliver reliable, performant data architectures.
• Collaborate across cross-functional teams including data engineering, data science, analytics and product to translate business challenges into scalable ML solutions.
• Monitor, tune and optimise the performance, cost-efficiency and reliability of data/ML pipelines in a production environment.
• Stay abreast of emerging technologies and best practices in data engineering, ML infrastructure and pipeline design to lift our platform continuously.

Technical Expertise

• A strong track record (typically 5+ years) in data engineering or ML engineering, with significant experience in building large-scale data pipelines and production ML systems.
• Proficiency in Python, and strong hands‑on experience with PySpark in distributed, big‑data environments.
• Proven experience with Databricks (cluster config, job orchestration, runtime optimisation).
• Deep understanding and practical use of Unity Catalog, Delta Lake and Apache Iceberg in data lake house architectures.
• Expertise in data modelling, partitioning strategies, performance tuning and best practices for high-throughput data systems.
• Familiarity with ML frameworks (e.g., TensorFlow, PyTorch, Scikit‑learn) and experience deploying models into production.
• Experience with CI/CD pipelines for data and ML code.
• Excellent communication skills and ability to work collaboratively in agile team environments.

Engineering Leadership

• Proven experience owning complex technical problems, guiding and influencing cross-team solutions and lifting platform standards.
• Comfortable driving infrastructure or platform-level initiatives, making architectural decisions that align with business outcomes.
• A proactive mindset with the ability to identify and evangelise tools, practices and improvements that elevate the team’s capability.

Bonus

• Experience on cloud platforms such as AWS, Azure or GCP.
• Exposure to streaming architectures (e.g., Structured Streaming, Kafka) or real‑time ML.
• Background with feature stores, data governance frameworks or data quality tooling.
• Experience using Databricks or similar data platforms.

“As a member of the Data Engineering team I have had the opportunity to work on a wide variety of data platforms, which not only broadens my knowledge base but also keeps me constantly engaged with evolving technologies. The team I work with is highly skilled team and truly inspiring. We motivate each other to innovate and excel in solving complex, large-scale problems with multi‑terabyte datasets and high throughput rates. Moreover, Dotdigital embraces a relaxed and flexible work culture, ensuring the great balance between productivity and well‑being. If you seek an environment that fosters personal and professional growth, Dotdigital's data team is the perfect match.”

• 15 min Screening Call with Talent Team
• Stage 1: Role deep dive with hiring manager(s)
• Stage 2: Technical interview with data science team

• Parental leave
• Medical benefits
• Paid sick leave
• Dotdigital day
• Share reward
• Wellbeing reward
• Wellbeing Days
• Loyalty reward

As an equal opportunities employer we are committed to equality in all its practices with regard to race, religion, national origin, age, sex, marital status, ancestry, physical or mental disability, veteran status, or sexual orientation. If you have any additional requirements or adjustments to assist an application then please don't hesitate to contact us and advise us how we can best support you.

No agencies/recruiters please. We are only accepting applications directly from the applicants. If you are a recruiter, please refrain from reaching out to our staff about this position. Anything contrary will be treated as unsolicited approach under the applicable data protection law.