Senior Data Engineer / Platform Lead

ATS Client; Pretoria; On-site; ZAR 900,000 - 1,300,000; Full time

Job summary

ATS Client is seeking a Senior Data Engineer to design, build, and scale a modern data platform. You will own end-to-end data pipelines, govern data quality, and mentor a growing team of engineers.

Collaborate with analytics, data science, and product teams to deliver reliable, scalable data foundations that empower reporting and BI across the business. The role requires hands-on leadership with deep experience in SQL, cloud platforms (AWS/Azure), and the modern data stack, with a focus on

Qualifications

• 10+ years in data engineering or related field.
• Strong SQL, MS Fabric, Data Factory, Power BI.
• Cloud platform experience (AWS/Azure).
• Modern data stack & orchestration tools experience.
• Strong data modeling, system design, and production pipeline experience.

Responsibilities

• Design scalable, secure, high-performance data architectures (lakehouse, warehouse, hybrid).
• Lead batch & real-time data pipelines and CI/CD, version control, and IaC best practices.
• Ensure data quality, governance, and observability.

Skills

SQL

Data modeling

System design

Production pipelines

Cloud platforms

Tools

MS Fabric

Data Factory

Power BI

Kafka

Kinesis

Pub/Sub

Job description

Job Description

We are seeking a highly skilled and experienced Senior Data Engineer to design, build, and scale our modern data platform. This role is ideal for a hands‑on technical leader who can architect robust data pipelines, drive best practices in data engineering, and mentor a growing team.

You will play a critical role in enabling analytics, data science, owning the end to end engineering of data pipelines and data products so that downstream reporting, and integrations run on reliable, scalable, governed, and observable data foundations.

Key Responsibilities

Technical Leadership

• Design scalable, secure, high-performance data architectures (lakehouse, warehouse, hybrid).
• Lead batch & real-time data pipelines and CI/CD, version control, and IaC best practices.
• Ensure data quality, governance, and observability.

Data Platform & Engineering

• Build & maintain ETL/ELT workflows, optimize queries, and manage storage.
• Integrate data from APIs, 3rd‑party systems, and streaming platforms.
• Support analytics and BI tooling with curated datasets.

Collaboration & Mentorship

• Mentor junior/mid-level engineers.
• Partner with Data Scientists, Analysts, Product Managers, and Engineering teams.
• Translate business requirements into scalable technical solutions.

SDLC‑Aligned Responsibilities

1. Discovery & Planning - Clarify requirements, define acceptance criteria, break initiatives into implementable slices.
2. Solution Design & Architecture - Own data architecture, define standards, ensure performance, security, and monitorability.
3. Build & Implementation - Develop pipelines, transformations, orchestrations, and automation.
4. Testing & Quality - Execute validations, reconcile data, ensure testability and reduce defects.
5. Release & Deployment - Support automated deployment, post-release validation, rollback strategies.
6. Operations & Monitoring - Own production pipelines, monitor, troubleshoot, implement preventive controls.
7. Governance & Documentation - Maintain lineage, dataset definitions, runbooks; enforce security and compliance.
8. Leadership & Team Enablement - Review work, set standards, coordinate dependencies, drive continuous improvement.

Required Qualifications

• 10+ years in data engineering or related field
• Strong SQL, MS Fabric, Data Factory, Power BI
• Cloud platform experience (AWS/Azure)
• Modern data stack & orchestration tools experience
• Strong data modeling, system design, and production pipeline experience

Preferred Qualifications

• Real‑time streaming (Kafka, Kinesis, Pub/Sub)
• Infrastructure as Code
• Machine learning data pipelines
• Data governance, security, compliance
• Team leadership / technical lead experience