Technical Data Engineer

Mandatory Skillsets: Python, Snowflake, dbt, dremio, glue jobs, Apache iceberg, AWS,SQL Key Responsibilities: Architect and Develop: Contribute to the platform''s architectural design and build integration, modelling, data persistence, and analytical systems. Data Pipelines: Implement, maintain, and test robust data pipelines. Metadata Management: Develop and manage metadata processes and tools. Performance Monitoring: Ensure the stability and performance of data pipelines. Data Quality: Implement tools for data curation, metadata management, and quality assurance. Collaboration: Engage with business and technology teams to align the platform with organizational goals. Preferred Technical Skills: Programming: 5+ years of experience in Python/Java. Cloud Expertise: Strong understanding of AWS services (eg, Lambda, Step Functions, ECS). Data Platforms: Hands-on experience with Snowflake and data stack technologies like Apache Iceberg and Spark. Workflow Orchestration: Exposure to tools like Apache Airflow, Prefect, Dagster, or DBT. Data Services: Familiarity with AWS Glue, Lake Formation, EMR, EventBridge, Athena, and similar services. Metadata Tools: Experience with tools like Amundsen, Atlas, DataHub, OpenDataDiscovery, or Marquez. RDBMS: Knowledge of PostgreSQL is a plus. Industry Experience: Proven experience building enterprise-wide data and analytics systems, preferably in financial services or asset management. ..... full job details .....