Data Engineer & Analyst

Data Pipeline Engineering

• Architect, develop, and maintain scalable and resilient data pipelines using Kubeflow and Python, enabling efficient ingestion, transformation, and enrichment
• Ensure seamless integration of various internal and external data sources into Snowflake, converting them into relational formats optimized for reporting and analytics.
• Build up operational frameworks for logging and monitoring across data pipelines and systems

Data Modeling & AI/ML Enablement

• Design Snowflake-based data models tailored for AI/ML readiness, supporting e.g. predictive analytics, anomaly detection, or automated alerting systems.
• Collaborate with data scientists and business analysts to implement and maintain a robust machine learning life cycle
• Perform deep-dive data analyses to identify relevant business insights

Collaboration & Documentation

• Maintain comprehensive documentation and version control of data workflows, models, and pipelines using GitHub, ensuring transparency, reproducibility, and team-wide collaboration.
  • Actively contribute to data governance initiatives, promoting best practices in data quality, lineage, and compliance.