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    • Data Engineer - Pretoria - PlaceTalent

    PlaceTalent
    PlaceTalent Pretoria

    4 days ago

    Default job background
    Description

    Job Description

    Summary

    We are seeking a highly skilled Data Engineer to join our team at placetalent. The ideal candidate will have a strong background in computer science and engineering, with expertise in data modeling, schema design, and database optimization.

    Key Accountabilities:

    • Data Engineering Development: Automate data workflows, ensure they are fault-tolerant and optimized.
    • Implement Logging and Monitoring: Implement logging, monitoring, and alerting for data pipelines.
    • ETL Job Performance Optimization: Optimize ETL job performance by tuning configurations and analyzing resource usage.
    • Data Storage Optimization: Optimize data storage solutions for performance, cost, and scalability.
    • AWS Resource Optimization: Ensure the optimization of AWS resources for scalability for data ingestion and outputs.
    • Machine Learning Model Deployment: Deploy machine learning models into productions using cloud-based services like AWS Sagemaker.
    • Scalable ETL Pipelines: Design, develop, and optimize scalable ETL pipelines using batch and real-time processing frameworks (using AWS Glue and PySpark).
    • Data Extraction, Transformation, and Loading: Implement data extraction, transformation, and loading processes from various structured and unstructured sources.
    • API Integration: Develop and integrate APIs to ingest and export data between various source and target systems, ensuring seamless ETL workflows.
    • ML Workflows Integration: Enable scalable deployment of ML models by integrating data pipelines with ML workflows.
    • Data Architecture: Design and maintain scalable data architectures using AWS services, such as AWS S3, AWS Glue, and AWS Athena.
    • Data Partitioning and Cataloging: Implement data partitioning and cataloging strategies to enhance data organization and accessibility.
    • Schema Evolution and Versioning: Work with schema evolution and versioning to ensure data consistency.
    • Metadata Repositories: Develop and manage metadata repositories and data dictionaries.
    • Data Access Roles and Privileges: Assisted and supported the definition, setup, and maintenance of data access roles and privileges.

    Minimum Requirements:

    • Bachelor's Degree: Bachelors degree in Computer Science or Engineering (or similar)
    • Certifications: AWS Certified Data Engineer or AWS Certified Solutions Architect or AWS Certified Data Analyst
    • Experience: 5+ years experience in a similar role
    • Programming Skills: Strong skills in Python (especially PySpark for AWS Glue)
    • Data Modeling and Schema Design: Strong knowledge of data modeling, schema design, and database optimization
    • AWS and Infrastructure as Code: Proficiency with AWS and infrastructure as code
    • SQL and NoSQL Databases: Knowledge of SQL, Python, AWS serverless microservices, deploying and managing ML models in production, version control (Git), unit testing, and agile methodologies

    Required Experience:

    • Data Engineering Development: Data Engineering development
    • AWS Services Experience: 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
    • SQL and NoSQL Databases Experience: Experience with SQL and NoSQL databases (e.g., PostgreSQL, MySQL, DynamoDB)
    • SQL Querying and Transformation Experience: Experience with SQL for querying and transformation of data
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Data engineer