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Data Engineer at Wynd Labs, Remote

We are seeking a Data Engineer with expertise in building and maintaining robust data pipelines and integrating scalable infrastructure. You will join a small, talented team and play a critical role in designing and optimizing our data systems, ensuring seamless data flow and accessibility. Your contributions will directly support our mission to position Grass as a key player in the evolution of data-driven innovation on the internet.

Who You Are:

• 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.
• Experience with infrastructure automation tools (e.g., Terraform, CloudFormation) for managing data ecosystems.
• Knowledge of programming languages such as Python, Scala, or Java for pipeline orchestration and data manipulation.
• Strong analytical and problem-solving skills, with an ability to troubleshoot and resolve data flow issues.
• Familiarity with containerization (e.g., Docker) and orchestration (e.g., Kubernetes) technologies for data infrastructure deployment.
• Collaborative team player with strong communication skills to work with cross-functional teams.

What You’ll Be Doing:

• 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.
• Working with cloud infrastructure (AWS, GCP, Azure) to manage databases, storage, and compute resources efficiently.
• Implementing best practices for data governance, data security, and disaster recovery in all infrastructure designs.
• Staying current with the latest trends and technologies in data engineering, pipeline automation, and infrastructure as code.

Why Work With Us:

• Opportunity. We are at at the forefront of developing a web-scale crawler and knowledge graph that allows ordinary people to participate in the process, and share in the benefits of AI development.
• Culture. We’re a lean team working together to achieve a very ambitious goal of improving access to public web data and distributing the value of AI to the people. We prioritize low ego and high output.
• Compensation. You’ll receive a competitive salary and equity package.