AWS Data Engineer
AWS Data Engineer
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1 Vacancy
Job Description
Job Description
INTRODUCTION:
An exciting opportunity has become available within the medical technology and devices industry for an AWS Data Engineer. Our client is an impactdriven digital health company passionate about affordable access to healthy hearing for everyone everywhere. This is an opportunity to be part of making a change and impacting human lives.
The position is based in Pretoria East.
PURPOSE:
Responsible for creating and managing the technological part of data infrastructure in every step of data flow. From configuring data sources to integrating analytical tools all these systems would be architected built and managed by a generalrole data engineer.
MINIMUM REQUIREMENTS:
Minimum education (essential):
Bachelors degree in Computer Science or Engineering (or similar)
Minimum education (desirable):
Honors degree in Computer Science or Engineering (or similar)
AWS Certified Data Engineer or
AWS Certified Solutions Architect or
AWS Certified Data Analyst
Minimum applicable experience (years):
5 years working experience
Required nature of experience
- Data Engineering development
- Experience with AWS services used for data warehousing computing and transformations ie.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
Skills and Knowledge (essential)
- 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
- English vernacular due to international interaction
- South African Citizens only
Skills and Knowledge(desirable):
- Knowledge of SQL Python AWS serverless microservices
- Deploying and managing ML models in production
- Version control (Git) unit testing and agile methodologies
RESPONSIBILITIES:
Data Architecture and Management 20
- 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.
Pipeline Development and ETL 30
- Design develop and optimize scalable ETL pipelines using batch and realtime 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.
Automation Monitoring and Optimization 30
- 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 cloudbased services like AWS Sagemaker.
Security Compliance and Best Practices 10
- Ensure API security authentication and access control bestpractices
- Implement data encryption access control and compliance with GDPR HIPAA SOC2 etc.
- Establish data governance policies including access control and security bestpractices.
DevelopmentTeam Mentorship and Collaboration 5
- 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 hearX strategy and vision.
- Identify and encourage areas for growth and improvement within the team.
QMS and Compliance 5
- Document data processes transformations and architectural decisions.
- Maintain high standards of software quality within the team by adhering to good processes practices and habits including compliance to QMS system and data and system security requirements.
- Ensure compliance to the established processes and standards for the development lifecycle including but not limited to data archival.
- Drive compliance to the hearX Quality Management System in line with the Quality Objectives Quality Manual and all processes related to the design development and implementation of software related to medical devices.
- Comply to ISO CE FDA (and other) standards and requirements as is applicable to assigned products.
- Safeguard confidential information and data.
This job description is not a definitive or exhaustive list of responsibilities and is subject to change depending on changing business requirements. Employees will be consulted on any changes. Employees performance will be reviewed based on the agreed upon objectives.If you do not hear from us within 30 days please consider your application unsuccessful
Employment Type
Full-Time
