Senior Data Engineer who will be responsible for implementation and improvementsResponsibilities:
Identify and Implement Process Improvements: Automate manual tasks, optimize data delivery, and enhance technology scalability.
Enhance Data Systems: Implement new features and improvements across data platforms.
Streamline CI/CD Processes: Optimize data pipelines within continuous integration and delivery workflows.
Manage Complex Data Sets: Assemble large, complex datasets to meet business and technical requirements.
Optimize ETL Processes: Ensure efficient data extraction, transformation, and loading.
Conduct Testing for Data Consistency: Develop and execute unit tests to maintain data accuracy across pipelines.
Automate Monitoring: Build and maintain automated solutions for tracking data pipeline performance and health.
Support Analytics Infrastructure: Maintain and improve reporting and analytics systems.
Ensure Data Quality and Governance: Uphold data governance standards and maintain infrastructure (AWS, database security, etc.).
Manage Metadata and Documentation: Maintain the data warehouse, data lake metadata, catalogs, and user documentation.
Ensure Best Practices in Database Management: Maintain optimal configurations, including collations, engines, and indexing strategies.
Education:
5+ years experience as a Data Engineer
BSc degree in Computer Science / Information system / Engineering or related or equivalent experience
Atleast 2 years experience builidng and optimising 'big data' data pipelines, architecture and maintaining data sets
Experience in Python, SQL, AWS, PySpark (desirable), AWS, Airflow, Docker
Proficiency in manipulating, processing and architecting large disconnected data sets for analytical requirements
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