Key skills
AirflowApacheAWSBigQueryCloudGoogle Cloud PlatformKafkaPythonAIMLAnalyticsApache KafkaApache AirflowGCPGoogle Cloud
About this role
Role Overview
- Design and evolve scalable, cloud-native data architectures for advanced analytics and AI
- Develop and maintain real-time and batch data processing platforms
- Define and implement data modeling standards for structured/unstructured data
- Integrate innovative technologies (vector databases, LLMs, real-time streaming)
- Ensure data quality, lineage, and governance
- Collaborate with engineering/product teams to translate business needs into solutions
- Optimize platform scalability, cost, and performance in cloud environments
- Establish architectural standards for data-driven decision-making
Requirements
- 5+ years of experience in data architecture and engineering
- Proficiency in Python for data processing/scripting
- Hands-on experience with Apache Airflow
- Experience with n8n low-code workflow automation
- Strong knowledge of Google BigQuery
- Familiarity with VectorDB or similar
- Expertise in AWS or GCP cloud services
- Experience integrating with OneDrive
- Upper-Intermediate English proficiency
- Experience with data governance tools (e.g., Collibra, Alation)
- Knowledge of streaming platforms like Apache Kafka
- AI/ML model deployment experience
- Multi-cloud architecture expertise
- Background in large-scale enterprise data migrations
Tech Stack
- Airflow
- Apache
- AWS
- BigQuery
- Cloud
- Google Cloud Platform
- Kafka
- Python
Benefits
- Flexible work arrangements
- Professional development opportunities