Data Engineer

Wynd Labs is an early-stage startup focused on making public web data accessible for AI through its Grass network, a platform that enables users to earn rewards by sharing unused internet bandwidth. The company is building a distributed residential proxy network designed to support large-scale data collection and power the next generation of AI systems.

Wynd Labs is an innovative early-stage startup dedicated to democratizing access to public web data for artificial intelligence through its Grass network. This platform enables users to share unused internet bandwidth in exchange for rewards, creating a distributed residential proxy network. As a Data Engineer, you will play a vital role in building and optimizing the data infrastructure that powers this ecosystem, ensuring seamless and reliable data flow across systems.

Responsibilities:
- Designing, building, and optimizing scalable data pipelines to process and integrate data from various sources in real-time or batch modes.
- Developing and managing ETL/ELT workflows to transform raw data into structured formats for analysis and reporting.
- Integrating and configuring database infrastructure, ensuring performance, scalability, and data security.
- Automating data workflows and infrastructure setup using tools like Apache Airflow, Terraform, or similar.
- Collaborating with data scientists, analysts, and other stakeholders to ensure efficient data accessibility and usability.
- Monitoring, troubleshooting, and improving the performance of data pipelines and infrastructure to ensure data quality and flow consistency.

Requirements:
- Bachelor’s degree in Computer Science, Information Systems, Data Engineering, or a related technical field.
- Extensive experience with database systems such as Redshift, Snowflake, or similar cloud-based solutions.
- Advanced proficiency in SQL and experience with optimizing complex queries for performance.
- Hands-on experience with building and managing data pipelines using tools such as Apache Airflow, AWS Glue, or similar technologies.
- Solid understanding of ETL (Extract, Transform, Load) processes and best practices for data integration.
- Knowledge of programming languages such as Python, Scala, or Java and familiarity with Docker, Kubernetes, and infrastructure automation tools.

Benefits:
- Competitive salary and equity package.
- Opportunity to work on cutting-edge AI data infrastructure and innovation.
- Collaborative, low-ego, and high-output team culture.
- High autonomy and ownership within a fast-paced startup environment.

Join Wynd Labs to help shape the future of equitable internet data access.