Senior Data Engineer

BOSS ERP Consulting; Wes-Kaap; On-site; ZAR 616,000 - 822,000; Full time

Job summary

BOSS ERP Consulting invites an experienced Senior Data & ML Engineer to lead the design and delivery of scalable data platforms in a hybrid Cape Town setting. You will build automated pipelines, a unified SSOT, and ML-ready data structures to enable advanced analytics and AI use cases across the business.

Focus areas include end-to-end data development, modular data models, and MLOps practices. The role requires 5+ years in data engineering and strong Python/SQL skills, with cross-functional

Qualifications

• 5+ years in data engineering or data platform development at a senior/lead level.
• Strong Python and SQL skills; experience with ML data readiness.
• Experience with API integrations, ETL/ELT orchestration, and data modelling across layers.
• Hands-on responsibility for building scalable data solutions and SSOT concepts.

Responsibilities

• Design, build and maintain end-to-end automated data pipelines into a central data platform.
• Develop SSOT database consolidating data from ERP, OT/IoT, SharePoint.
• Own end-to-end data development solutions and ML-ready data structures.
• Implement scalable data models across staging, core, marts, and feature sets.
• Apply MLOps practices and CI/CD for models and data.
• Ensure data governance, security and change management.

Skills

Python

SQL

API integration

ETL/ELT

Data modelling

ML concepts

C#

Data pipelines

Education

Bachelor's degree in Computer Science, Information Systems, Engineering

Tools

Airflow

Azure Data Factory

Power Apps

Power Automate

TensorFlow

PyTorch

SQL Server

Job description

Job Title: Senior Data & ML Engineer

• Location: Cape Town
• Employment Type:: Hybrid Permanent

Main Purpose of Role

The Senior Data & ML Engineer is responsible for executing the technical implementation of the Data Transformation. The role focuses on designing and building the data ingestion and processing platform, including automated data pipelines, an integrated database, cross-functional system integrations and AI/ ML-ready data structures.

The Senior Data & ML Engineer must translate strategic direction into concrete technical solutions, make sound architectural recommendations, and deliver scalable, robust, production-grade data capabilities that support reliable reporting, advanced analytics and machine learning use cases across the business.

This role will form part of our technical shared services team, contributing to the development of digital management systems, O&M projects implementations and ongoing development within the Data Transformation Project.

Key Responsibilities

Design, build and maintain end-to-end automated data pipelines from internal and external sources into a central data platform:

• Develop an integrated and scalable Single Source of Truth (SSOT) database, consolidating data from ERP, OT/IoT, SharePoint ensuring scalable data flows.
• Develop modular and scalable data ingestion developing API integrations, SQL Stored Procedures and ETL frameworks, maintaining reliable, automated data ingestion between internal and external platforms to the SSOT database.
• Own end to end data development solutions.

Design and develop scalable data models (staging, core, marts, feature sets) that support strategic reporting, advanced analytics and ML.

• Design scalable data models across clearly defined layers, including staging (raw landed data), core (cleaned and standardised single source of truth), marts (business-ready views for specific domains), and feature sets (model-ready tables for machine learning and advanced analytics).
• Implement MLOps practices (versioning of data and models, CI/CD for models, monitoring, retraining strategies) as ML use cases mature.
• Own end-to-end development and processing (data algorithms and ML solutions)
• Ensure all data models, pipelines and storage approaches are AI/ML-ready.

Technical platform development, data orchestration and data management

• Apply and enforce data management, security and governance standards in line with the Data Governance Policy.
• Implement structured change management (version control, release processes, approvals, rollback plans).
• Work with divisional data owners to reduce data silos, standardise data flows and ensure adherence to agreed standards and timelines.

Asset Lifecycle Management & Platform Integration

• Oversee the full onboarding and offboarding process for company assets and equipment within the central asset management platforms.
• Ensure seamless data integration by validating that all asset information is correctly captured and synchronized.
• Maintain data integrity and platform compliance by routinely reviewing asset entries, resolving discrepancies.

Skills and Competencies

Full-stack data engineering competence:

• API integration (REST/JSON, auth, pagination, error handling)
• ETL/ELT orchestration and job scheduling (Automated workflows)
• Data modelling (staging, core, marts, feature sets); production operations (monitoring, alerting, incident response)
• Strong SQL; proficiency in Python for data engineering and ML-enabling tasks; and solid programming foundations in Python, SQL and/ or C#
• Ability to make scalable architectural decisions and prepare data for ML and model integration into workflows.
• Solid ML foundations (feature engineering, evaluation, overfitting, drift) and ability to design data pipelines that are fit for ML.

Senior, hands-on engineering mindset; comfortable owning technical direction.

• Proven ability to design and lead data platform or data product builds.
• Self-directed and proactive: identifies problems, proposes solutions and drives implementation without detailed step-by-step direction.
• Clear, structured communication skills. can explain technical options and trade-offs to non-technical stakeholders and leadership.

Strong systems thinking and architecture skills: designs for scalability, maintainability and AI/ML-readiness from the outset.

• Strong engineering discipline: version control, testing, deployment processes, documentation and incident handling.
• Enjoys building automation, integrations and ML-ready datasets.
• Cross-team coordination and influence – able to work with multiple divisions, follow up with stakeholders and enforce agreed standards and timelines.

Experience, Knowledge and Qualifications

Minimum requirements:

• Degree in Computer Science, Information Systems, Engineering, Mathematics or a related field. Proficient in data engineering.
• 5+ years in data engineering/ data platform development at a senior/ lead level.
• Programming foundations in Python, SQL and/or C#.
• Hands‑on responsibility for API integration (REST/JSON, auth, pagination, error handling); ETL/ELT orchestration and job scheduling; data modelling (staging, core, marts/ feature sets); and production operations (monitoring, alerting, incident response).
• Strong SQL skills (DDL/DML, performance tuning, stored procedures, views, functions).
• Proficiency in Python for data engineering and ML-enabling tasks, plus experience with ETL.
• Strong foundations in ML concepts and practical experience preparing data for ML and integrating models into data workflows (even if not a pure data scientist).

Advantageous

• Hands-on experience with ML models in production (e.g. forecasting, classification, anomaly detection) and associated MLOps tooling.
• Exposure to neural networks/ deep learning (e.g. TensorFlow, PyTorch) and modern ML pipelines.
• Design and support workflow automation and lightweight data applications using tools such as Power Apps and Power Automate, integrating these solutions with the core data platform to enable efficient business processes.
• Experience with data lakes/ big data architectures and orchestration tools (e.g. Airflow, Prefect, Azure Data Factory or similar).
• Familiarity with AI/ ML governance, model risk and secure data handling.
• Experience working with industrial/IoT or energy sector data.

This role is a weekly hybrid role in Cape Town with a Cost To Company range of ZAR 616K - ZAR 822K (ZAR 51,000 - ZAR 68,500 per month).