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.