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Data Engineering Lead

2 weeks ago

Pretoria, Gauteng, South Africa Hearx Group Full time

About This Role

We are seeking an experienced AWS Solutions Engineer to join our team and contribute to the design and implementation of scalable data systems using AWS services. As a key member of our team, you will be responsible for building and managing complex data architectures, ensuring high performance, scalability, and cost efficiency.

Key Responsibilities

  1. Data Architecture & Management: Design and maintain data systems using AWS services such as S3, Glue, and Athena. Ensure data partitioning and cataloging strategies are effective and easy to access.
  2. ETL Pipeline Development: Develop and optimize ETL pipelines using AWS Glue and PySpark. Focus on improving performance, scalability, and cost-efficiency in batch and real-time data processing.
  3. Automation & Monitoring: Automate workflows and ensure they run efficiently. Set up monitoring and alerts for data pipelines, and optimize AWS resources for scalability and performance.
  4. Security & Compliance: Follow security best practices, including API authentication, data encryption, and compliance with GDPR, HIPAA, and SOC2.
  5. Collaboration & Mentorship: Work closely with data scientists, analysts, and backend teams to integrate data pipelines. Provide mentorship to junior team members and encourage growth and collaboration.
  6. Quality Management: Ensure high-quality software development standards by adhering to best practices and complying with industry regulations like ISO, CE, and FDA.

Requirements

  • AWS Services: Experience with AWS Glue, S3, Lambda, Athena, and CloudWatch.
  • Data Engineering: Proven experience developing and optimizing ETL pipelines. Familiarity with SQL and NoSQL databases (e.g., PostgreSQL, MySQL, DynamoDB).
  • Programming: Strong skills in Python, particularly using PySpark with AWS Glue.
  • Data Modeling & Optimization: Experience in data modeling, schema design, and database optimization.
  • Machine Learning: Experience integrating data pipelines with machine learning workflows and deploying models with AWS SageMaker.
  • Compliance & Security: Knowledge of data governance, API security, and compliance with industry standards and regulations.