Big Data Architectural Specialist
1 week ago
Job Overview:
We are seeking a highly skilled Data Engineer to join our team at Network Recruitment.
Salary Range: $120,000 - $180,000 per annum
About the Role:
In this exciting role, you will be responsible for designing and implementing large-scale data systems, ensuring data quality, integrity, and scalability. Your primary focus will be on developing efficient ETL processes, optimizing data delivery, and enhancing data systems.
Responsibilities:
- Process Optimization: Identify opportunities to automate manual processes, improve data delivery, and enhance overall system efficiency.
- System Enhancements: Develop and implement new features and enhancements across our data systems, focusing on optimal data pipelines and CI/CD process improvements.
- Data Pipeline Development: Assemble and manage complex data sets, meeting both functional and non-functional business requirements.
- ETL Processes: Lead the design, development, and optimization of efficient ETL pipelines, ensuring high-quality data transformation and integration.
- Testing & Consistency: Develop and execute unit tests to guarantee data consistency and reliability across pipelines.
- Monitoring & Reporting: Implement and maintain automated monitoring solutions to support reporting and analytics infrastructure.
- Data Governance & Quality: Ensure high standards of data governance, quality assurance, and the maintenance of data infrastructure systems (AWS, databases, security).
- Metadata & Documentation: Maintain data warehouse and data lake metadata, data catalogs, and user documentation for internal business users.
- Best Practices: Enforce best practices across our database systems (e.g., collations, indices, database engines) to ensure performance and reliability.
Technologies:
- Programming Languages: Python, SQL
- Data Engineering: PySpark, Airflow, Terraform
- Cloud Platforms: AWS (primary), Azure, GCP
- Containerization: Docker
- Version Control & CI/CD: GitHub, Jenkins, etc.
Qualifications and Experience:
- Educational Background: BSc Degree in Computer Science, Information Systems, Engineering, or a related technical field (or equivalent work experience).
- Experience: 5+ years of related work experience, including at least 2 years of experience in building and optimizing 'big data' data pipelines and maintaining large data sets.
- Technical Proficiency:
- Strong experience with Python and SQL (PostgreSQL, MS SQL).
- Hands-on experience with cloud services, particularly AWS (experience with Azure or GCP is a plus).
- Proficiency in ETL processes and data lifecycle management.
- Experience with Glue and PySpark is highly desirable.
- Skilled in version control, CI/CD pipelines, and GitHub.
- Data Management Expertise: Deep understanding of data quality assurance, data governance, and best practices for managing data transformation processes, metadata, and dependencies.
- Analytical Skills: Strong problem-solving abilities and experience working with unstructured datasets.
- Big Data: Familiarity with message queuing, stream processing, and working with highly scalable 'big data' stores.
- Attention to Detail: A meticulous eye for detail and a commitment to maintaining high-quality data systems.
- Communication: Strong communication skills and the ability to work collaboratively in a team.
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