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Data Engineer | DISA-DIA-DEAWS-JHB-0037

Decision Inc.🌍 South AfricaSenior · Data/AIPosted today
✓ South Africa confirmedThe posting names South Africa or Africa, or was posted here for SA applicants.

Last checked 2 hr ago on Himalayas.

Salary not listed.

PythonAWSSQLAI/ML

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This job was first published on Himalayas. Check the original posting to confirm you're eligible from South Africa.

Decision Inc. is looking for a talented Senior AWS Data Engineer to join our Data, Information & Analytics practice. In this role, you'll design, build and maintain scalable, secure, high-performance data platforms and integration solutions using native AWS services. Working alongside experienced consultants, you'll help deliver trusted, high-quality data that powers analytics, reporting and AI/ML initiatives. This role offers the opportunity to contribute across the full data engineering lifecycle—from building modern data pipelines and supporting cloud migrations to delivering robust, enterprise-scale data platforms. At Decision Inc., we're committed to developing our people through mentorship, continuous learning and meaningful project experience, with a proven track record of supporting long-term technical and career growth. Who Are We? Decision Inc. is a global digital partner that enables businesses to reinvent themselves to realise their full potential. We deliver agility, resilience, and intelligence to any enterprise, enabling them to adapt quickly and thrive through innovation and opportunity. Our teams have engaged with more than 400 clients globally over the past 15 years, providing them with the expertise to build, operate, and optimise their digital businesses. We achieve this by leveraging the world's best technology to drive our client's business ambitions forward into tomorrow's reality. These technologies include but are not limited to: Microsoft, SAP, Qlik, Snowflake, Alteryx, Automation Anywhere, and Workday Adaptive Insights. Our success is ultimately driven by our entrepreneurial culture, industry exposure, and the passion of our people. We have three key cross-functional teams – Functional and Specialist Consulting, Development, and Engineering teams. Based in four global offices, our exceptional consultants focus on delivering value to clients by keeping them at the centre of our service delivery. To find out more about our exciting fast-paced culture visit: Careers at Decision Inc. What Will You Do? Key Responsibility: You will be assigned a portfolio of client engagements where you will be expected to: Design, develop, and maintain scalable data pipelines. Build and optimise cloud-based data lakes and data processing solutions using native AWS services. Develop ETL/ELT processes to ingest, transform, and curate data from a variety of source systems. Implement data quality, monitoring, and error-handling processes to ensure reliable data delivery. Optimise data solutions for performance, scalability, security, and cost efficiency. Collaborate with architects, analysts, and business stakeholders to deliver data solutions aligned with business requirements. Support CI/CD practices, Infrastructure as Code, and operational excellence across the data estate. Contribute to engineering best practices. Who Do You Need to Be? Technical Skill: Strong experience with native AWS data services such as S3, Glue, Lambda, Redshift, Athena, Lake Formation and related services. Proficiency in Python, SQL, and Apache Spark (PySpark). Experience building ETL/ELT pipelines and cloud-based data solutions. Understanding of data modelling, data quality, and data governance principles. Experience with Git, CI/CD, and Infrastructure as Code. Experience: 5+ years of data engineering experience, including hands-on delivery on AWS. Experience designing and implementing enterprise-scale data pipelines and analytics solutions. Strong understanding of cloud architecture, security, and performance optimisation. Preferred Qualifications: AWS Data Engineer or Solutions Architect Associate certification. Experience with real-time data processing and event-driven architectures. Exposure to AI/ML data engineering workloads. Originally posted on Himalayas

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