Data Engineer responsible for backend data engineering tasks, developing ETL processes for legal data integration. Collaborating with teams to ensure efficient data pipelines and governance.
About the role
- Data Engineer enhancing data management and infrastructure for COSMOTE Global Solutions. Constructing data pipelines and ensuring data quality while collaborating with analysts and scientists.
Responsibilities
- Constructing, maintaining, and optimizing data pipelines for a variety of data sources.
- Working with various databases and cloud technologies to manage and store data effectively.
- Ensuring data quality and integrity through regular monitoring and validation.
- Collaborating with data scientists and analysts to implement data-driven solutions.
- Assisting in the establishment of best practices for data engineering within the organization.
- Contributing to the strategic direction of data-related projects and initiatives.
- Staying updated with the latest industry trends and technologies in data engineering.
Requirements
- Bachelor's degree in Computer Science, Engineering, or a related field.
- Excellent SQL skills including complex transformations and query optimization
- Proven experience in the design, development, and maintenance of robust ETL/ELT pipelines
- Experience managing data flow across staging, raw, business vault, and data mart layers
- Ability to implement and maintain Data Vault 2.0 models designed by the Data Modeler
- Experience integrating SQL-based and NoSQL data sources (e.g., JSON format data)
- Ability to technically implement governance and lineage tracking mechanisms
- Capability to optimize workloads, queries, and processing performance
- Implementation of data validation, reconciliation, and quality controls in pipelines
- Application of performance, maintainability, and coding best practices
- Experience implementing monitoring, alerting, and logging frameworks
- Ability to define and document data engineering standards and best practices
- Experience querying MongoDB or other NoSQL databases
- Experience implementing automated data quality checks
- Ability to optimize cloud resource usage and manage costs
- Exposure to AI-driven performance optimization techniques
- Experience with modern cloud data platforms
- Experience with large-scale or near real-time data processing environments
- Knowledge of encryption, masking, and secure data handling practices
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