Data Engineer

📋 Description

• Develop and maintain high-performance data pipelines leveraging Airflow, dbt, and Python to structure raw data for analysis, modeling, and product applications.

• Collaborate with Product, Data Science, and ML Engineering teams to establish the infrastructure that supports machine learning operations, including training datasets, feature pipelines, and model output tables.

• Create production-quality SQL queries (Amazon Redshift) and oversee query optimization to meet the rapidly evolving demands of the business.

• Implement instrumentation, monitoring, and alerting systems to ensure data freshness, quality, and availability in production settings.

• Recognize and execute enhancements by automating manual processes and decreasing pipeline runtimes.

• Regularly use AI-assisted developer tools (such as Claude Code) to expedite development and engage in design reviews and on-call duties.

⛳️ Requirements

• Bachelor’s degree (Master’s preferred) in Computer Science, Data Engineering, or a related discipline.

• 2–4 years of relevant experience in a data engineering position, or a comparable mix of education and experience.

• Expertise in Python and SQL, with a background in constructing orchestration workflows (Airflow preferred) and performing data transformations (dbt).

• Practical experience with cloud-based data warehouses (Amazon Redshift) and data lakes (AWS S3).

• Familiarity with tools such as DuckDB, pandas, Jupyter, UNIX shell scripting, and Git.

• A strong grasp of dimensional modeling and the ability to build data infrastructure that supports AI workloads.

🏝️ Benefits

• Comprehensive medical, dental, and vision coverage (with 65% coverage for dependents).

• Optional life insurance and long-term disability coverage.

• A 401(k) retirement plan.

• Fully remote work-from-home opportunities available in 28* states.

• 8 weeks of paid parental leave.

• Paid holidays every year.

• Flexible vacation time.

• Sick and safety leave.

• Volunteer time off.