About the Role
The role involves developing and maintaining robust data pipelines to ensure efficient movement and transformation of data across platforms. The engineer will work closely with data scientists and product teams to deliver high-quality data solutions.
Responsibilities
- Design and implement scalable data ingestion systems
- Build and maintain ETL workflows for structured and unstructured data
- Optimize data pipeline performance and reliability
- Collaborate with cross-functional teams to define data requirements
- Ensure data consistency, accuracy, and accessibility
- Monitor pipeline health and troubleshoot production issues
- Implement data validation and error handling mechanisms
- Support data governance and compliance standards
- Integrate data from multiple sources into centralized repositories
- Work with streaming and batch processing frameworks
- Develop automated testing for data workflows
- Document architecture and operational procedures
- Improve data observability and monitoring capabilities
- Evaluate and adopt new data technologies
- Contribute to system security and access controls
- Participate in code reviews and technical design discussions
- Mentor junior engineers on data engineering practices
- Support incident response for data-related outages
- Ensure efficient data storage and retrieval patterns
- Drive improvements in data freshness and latency
Nice to Have
- Master’s degree in computer science or related field
- Experience with real-time data processing systems
- Familiarity with data mesh or data fabric architectures
- Contributions to open-source data projects
- Experience in regulated industries (e.g., finance, healthcare)
- Knowledge of data lineage and metadata management tools
Compensation
Competitive salary and equity package
Work Arrangement
Remote-first with flexible hours
Team
Collaborative engineering team focused on data infrastructure and systems reliability
Tech Stack
Python, Apache Airflow, Kafka, AWS, Snowflake, Docker, Kubernetes
Growth Opportunities
- Opportunities to lead data infrastructure initiatives
- Access to conferences and learning resources
- Mentorship in advanced data engineering topics
Available for qualified candidates
