Data Engineers

Indsafri; South Africa; On-site; ZAR 500,000 - 750,000; Full time

Job summary

A financial services company in South Africa is seeking a skilled Data Engineer to design and maintain scalable data pipelines critical for analytics and decision-making in various financial domains. Applicants should have a Bachelor’s degree and 4-7 years of relevant experience. Strong programming skills in Python and SQL, as well as experience with data warehousing and cloud platforms, are essential. This role demands attention to detail, strong problem-solving abilities, and excellent collaboration skills.

Qualifications

• 4-7 years of experience as a Data Engineer.
• Experience integrating data from multiple financial systems.
• Strong understanding of data quality and governance standards.

Responsibilities

• Design, develop, and maintain ETL/ELT pipelines for data.
• Build scalable data architectures (data lakes, warehouses).
• Collaborate with cross-functional teams to deliver data solutions.

Skills

Python

SQL

Data pipeline tools (e.g., Apache Airflow, SSIS, Informatica, dbt)

Data warehousing solutions (e.g., Snowflake, Redshift, Azure Synapse)

Big data technologies (e.g., Spark, Hadoop)

Cloud platforms (AWS, Azure, GCP)

Streaming technologies (e.g., Kafka, Kinesis)

Data modelling techniques

Version control (e.g., Git)

CI/CD practices

Education

Bachelor’s degree in Computer Science, Information Technology, Engineering, or a related field

Job description

We are seeking a skilled Data Engineer with 4–7 years of experience to design, build, and maintain scalable data pipelines and architectures across key financial domains including Payments, Investor Services & Trade, Pricing & Billing, and Liquidity Management. The role focuses on enabling high-quality, reliable, and timely data to support analytics, reporting, and operational decision-making.

Key Responsibilities

• Design, develop, and maintain robust ETL/ELT pipelines for structured and unstructured data.
• Build scalable data architectures (data lakes, data warehouses) to support analytics and business intelligence.
• Integrate data from multiple financial systems including payments platforms, trading systems, and billing engines.
• Ensure data quality, integrity, and consistency across all pipelines and datasets.
• Optimise data workflows for performance, scalability, and cost-efficiency.
• Collaborate with Data Analysts, AI/ML Engineers, and business stakeholders to deliver data solutions aligned to business needs.
• Implement data governance, security, and compliance standards.
• Support both batch and real-time/streaming data processing where required.
• Troubleshoot data issues and provide ongoing support for production data environments.

Required Qualifications

• Bachelor’s degree in Computer Science, Information Technology, Engineering, or a related field.

Technical Skills

• Strong programming skills in Python, SQL (mandatory).
• Experience with data pipeline tools (e.g., Apache Airflow, SSIS, Informatica, dbt).
• Hands-on experience with data warehousing solutions (e.g., Snowflake, Redshift, Azure Synapse).
• Knowledge of big data technologies (e.g., Spark, Hadoop).
• Experience with cloud platforms (AWS, Azure, or GCP).
• Familiarity with streaming technologies (e.g., Kafka, Kinesis) is advantageous.
• Understanding of data modelling techniques (dimensional modelling, star/snowflake schemas).
• Experience with version control (e.g., Git) and CI/CD practices.

Domain Experience (Highly Preferred)

• Liquidity Management: Cash flow data pipelines, treasury systems integration, liquidity reporting.

Core Competencies

• Strong problem-solving and analytical thinking.
• Attention to detail with a focus on data accuracy and quality.
• Ability to work with complex, high-volume financial datasets.
• Good communication and stakeholder engagement skills.
• Ability to manage multiple priorities in a fast-paced environment.