
AWS Data Engineer
- Pretoria, Gauteng
- Permanent
- Full-time
- Honors degree in Computer Science or Engineering (or similar)
- AWS Certified Data Engineer; or
- AWS Certified Solutions Architect; or
- AWS Certified Data Analyst
- Data Engineering development
- Experience with AWS services used for data warehousing, computing and transformations i.e. AWS Glue (crawlers, jobs, triggers, and catalog), AWS S3, AWS Lambda, AWS Step Functions, AWS Athena and AWS CloudWatch
- Experience with SQL and NoSQL databases (e.g., PostgreSQL, MySQL, DynamoDB)
- Experience with SQL for querying and transformation of data
- Strong skills in Python (especially PySpark for AWS Glue)
- Strong knowledge of data modelling, schema design and database optimization
- Proficiency with AWS and infrastructure as code
- Knowledge of SQL, Python, AWS serverless microservices,
- Deploying and managing ML models in production
- Version control (Git), unit testing and agile methodologies
- Design and maintain scalable data architectures using AWS services for example, but not limited to, AWS S3, AWS Glue and AWS Athena.
- Implement data partitioning and cataloging strategies to enhance data organization and accessibility.
- Work with schema evolution and versioning to ensure data consistency.
- Develop and manage metadata repositories and data dictionaries.
- Assist and support with defining setup and maintenance of data access roles and privileges.
- Design, develop and optimize scalable ETL pipelines using batch and real-time processing frameworks (using AWS Glue and PySpark).
- Implement data extraction, transformation and loading processes from various structured and unstructured sources.
- Optimize ETL jobs for performance, cost efficiency and scalability.
- Develop and integrate APIs to ingest and export data between various source and target systems, ensuring seamless ETL workflows.
- Enable scalable deployment of ML models by integrating data pipelines with ML workflows.
- Automate data workflows and ensure they are fault tolerant and optimized.
- Implement logging, monitoring and alerting for data pipelines.
- Optimize ETL job performance by tuning configurations and analyzing resource usage.
- Optimize data storage solutions for performance, cost and scalability.
- Ensure the optimisation of AWS resources for scalability for data ingestion and outputs.
- Deploy machine learning models into productions using cloud-based services like AWS SageMaker.
- Ensure API security, authentication and access control best practices.
- Implement data encryption, access control and compliance with GDPR, HIPAA, SOC2 etc.
- Establish data governance policies, including access control and security best practices.
- Work closely with data scientists, analysts and business teams to understand data needs.
- Collaborate with backend teams to integrate data pipelines into CI/CD.
- Assist with developmental leadership to the team through coaching, code reviews and mentorship.
- Ensure technological alignment with B2C division strategy supporting overarching strategy and vision.
- Identify and encourage areas for growth and improvement within the team.
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