Senior Cloud Data Engineer

Job Title: Senior Cloud Data Engineer

Experience Required: 8+ years in data engineering, with substantial hands-on cloud experience

Role Overview
We are seeking a Senior Cloud Data Engineer to design, build, and optimize scalable data infrastructure and pipelines in a cloud environment, with a strong focus on financial and business intelligence use cases. This role requires deep technical expertise in cloud data platforms, strong architectural judgment, and the ability to work closely with clients and cross-functional teams to translate business requirements into robust technical solutions.

Key Responsibilities

• Design, build, and maintain robust, scalable ETL/ELT pipelines for structured and unstructured data
• Architect cloud-based data solutions (data lakes, data warehouses, lakehouses) on Azure, AWS, or GCP
• Work with clients to understand current business processes, architecture, and reporting, and help define their digital transformation roadmap and future-state BI environment
• Define new application or process requirements where existing systems don't meet client needs
• Run workshops with enterprise clients to gather and interpret requirements, then document and present solutions back to the client
• Optimize data pipeline performance, cost, and reliability at scale
• Lead the implementation of data governance, security, and compliance best practices
• Collaborate with data scientists, analysts, project managers/scrum masters, modeling teams, and BI teams to ensure high-quality implementation
• Own CI/CD pipelines for data infrastructure using Infrastructure as Code (Terraform, ARM/Bicep, or CloudFormation)
• Mentor and provide technical guidance to junior and mid-level data engineers
• Do deep dives into business processes and reporting to understand how transactions and activities flow into daily, weekly, monthly, and annual reporting
• Design and implement visual reporting, insights, and analysis of financial and operational information
• Identify risks and gaps in solution implementation and propose improvements to increase client ROI
• Establish and enforce data quality standards and monitoring frameworks

Required Skills & Experience

• 8+ years in data engineering, with 4+ years working specifically in cloud environments
• Experience working with financial systems and financial system integrations
• Data warehouse expert
• Expert-level proficiency in SQL and at least one programming language (Python, Scala, or Java)
• Strong hands-on experience with a major cloud platform (Azure preferred, or AWS/GCP)
• Deep experience with cloud-native data services (e.g., Azure Data Factory, Databricks, Synapse, Snowflake, Redshift, BigQuery, or equivalent)
• Proven experience with distributed data processing frameworks (Spark, Kafka, or similar)
• Strong understanding of data modeling, data warehousing concepts, and dimensional design
• Experience with orchestration tools (Airflow, Azure Data Factory, dbt)
• Solid grasp of DevOps practices for data engineering (CI/CD, version control, IaC)
• Ability to understand, analyse, and utilise large/complex data sets (banking/financial data an advantage)
• Excellent written and verbal communication skills; able to translate and simplify complex requirements for both technical and non-technical stakeholders
• Excellent analytical, system design, and problem-solving skills

Good-Fit Traits

• Able to identify, understand, and communicate complex issues concisely to both technical and non-technical audiences
• Naturally inclined to automate and optimize mundane/routine tasks
• Works well under pressure with strict timelines and deadlines
• Thrives in a fast-paced, ambiguous environment and can multitask across several priorities
• Highly analytical, detail-oriented, with solid conceptual thinking
• Naturally curious with a genuine interest in technology

Preferred Qualifications

• Bachelor's degree in Computer Science, Engineering, Finance, or related field (or equivalent experience)
• Cloud certification (Azure Data Engineer Associate, AWS Certified Data Analytics, or GCP Professional Data Engineer)
• Experience in a consulting or client-facing environment
• Prior experience leading or mentoring a team

Soft Skills

• Strong communication skills, able to explain technical concepts to non-technical stakeholders
• Leadership mindset with a collaborative approach
• Comfortable working in fast-paced, evolving environments

Pay: R409 262,05 - R1 109 775,73 per year

Work Location: Hybrid remote in Johannesburg, Gauteng