Description

Responsibilities

• Design, build, and manage production ETL/ELT data pipelines, including data integration, monitoring, and data quality assurance
• Lead and mentor data engineers, driving technical decisions and communicating effectively with business and technical stakeholders
• Establish data engineering best practices and discipline within a developing engineering organization
• Take initiative in providing technical direction and working independently on strategic data platform initiatives
• Support and lead additional team members as the organization scales
• Design and implement scalable data architecture, data warehouse solutions, and data modeling approaches
• Implement workflow orchestration, CI/CD practices, and automated data pipeline deployment

Qualifications

• Required
  • 5+ years of hands-on experience designing, building, and managing production ETL/ELT data pipelines
  • Experience leading, mentoring, or managing data engineers
  • Hands-on experience with Snowflake and AWS data infrastructure (S3, EMR, distributed data processing)
  • Strong SQL skills, including query optimization
  • Proficiency in Python and PySpark for large-scale data processing
  • Experience with data warehouse design, data modeling, and distributed processing
  • Experience with Apache Airflow or similar orchestration tools
  • Knowledge of CI/CD, DevOps, and automated data pipeline deployment
• Preferred
  • Kafka, streaming data, and Change Data Capture (CDC) experience
  • PostgreSQL or other relational database expertise
  • Data observability and monitoring tools (Dynatrace, Prometheus, Grafana, ELK)
  • ML/AI data pipeline support and feature engineering
  • Docker, Kubernetes, or OpenShift experience
  • SnowPro or AWS certifications

Key Skills

Education

Bachelor's degree