Data Engineer - Permanent
Indexed description
Collective.work is building the next-generation AI-powered sourcing platform for recruiters. Our mission is to help talent teams identify, engage, and hire the best candidates faster through intelligent automation and data-driven insights. We operate at the intersection of data, AI, and recruiting workflows—where high-quality data infrastructure is critical to our success.
Missions
- Design and maintain scalable data pipelines (batch and real-time)
- Build and optimize ETL/ELT workflows across Azure and/or GCP
- Develop data models and architectures to support analytics and ML use cases
- Ensure data quality, integrity, and reliability across systems
- Collaborate with ML engineers to prepare and serve training datasets
- Monitor and improve pipeline performance, cost efficiency, and scalability
- Implement best practices for data governance, security, and compliance
- Contribute to tooling and infrastructure decisions
- Cloud: Azure (Data Factory, Synapse) and/or GCP (BigQuery, Dataflow)
- Data Processing: Python, SQL, Spark
- Orchestration: Airflow / Prefect
- Storage: Data lakes, warehouses
- Streaming: Kafka / PubSub (nice to have)
- DevOps: Docker, CI/CD
- Flexible remote work environment
- Opportunity to work on a product at the cutting edge of AI and recruiting
- High ownership and impact from day one
- Collaborative, product-driven engineering culture
- Opportunity to shape the data foundation of a growing platform
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