01Key Responsibilities
Architect and Develop: Contribute to the platforms 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 (e.g., 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 .
