Remote Software Engineer, Data

Summary

Join our team as a Software Engineer, Data, and contribute to the development and automation of our data pipelines. You will work on complex data projects, support technical initiatives, and ensure the scalability and performance of our data solutions. This role offers opportunities for professional growth and development, and you will have the chance to focus on building with cutting-edge technologies and innovative projects.

Requirements

• Bachelor’s degree in Computer Science, Information Technology, or a related field, or equivalent practical experience
• 3-5 years of experience in software development, with significant experience in Python, SQL, and data pipelines
• Experience in building and automating ETL/ELT pipelines using Airflow or other DAG-based orchestration software
• Experience managing dbt models using macros and test-driven development
• Proficiency in Python or comparable back-end, API development, and software architecture
• Experience with databases like PostgreSQL and BigQuery, including query optimization for performance and cost
• Understanding of business intelligence tools like Looker or comparable alternatives
• Familiarity with Google Cloud Platform, Kubernetes, and managing infrastructure as code using Terraform
• Knowledge of advanced data formats (Parquet, Avro, Delta Lake, Hive, JSONL) and data integration techniques
• Understanding of agile methodologies, continuous integration, and test-driven development
• Strong problem-solving skills and a willingness to learn from senior engineers
• Ability to work collaboratively within cross-functional teams and projects
• Familiarity with version control systems and CI/CD tools like GitHub Actions

Responsibilities

• Collaborate with senior engineers to design, implement, maintain, and unit test scalable data solutions with a focus on automation using DAG-based orchestration software like Airflow
• Build dbt models, leveraging macros and test-driven development practices
• Provide implementation, configuration, and deployment documentation
• Proactively address issues and problems, suggesting and implementing innovative solutions
• Participate in agile ceremonies and knowledge-sharing activities within the engineering team
• Monitor, troubleshoot, and optimize the performance of data pipelines and workflows
• Ensure data quality and integrity through testing and validation processes
• Stay updated with industry trends and technologies to support continuous improvement and innovation in data engineering practices