Senior Data Engineer

Topstep is a company focused on data intelligence, seeking a Senior Data Engineer to architect and implement foundational systems for analytics and automation. The role involves building scalable data pipelines, optimizing workflows, and collaborating with cross-functional teams to enhance data usage across the organization.

Responsibilities:

• Data Pipeline Development & Ownership: Design, build, and maintain robust and scalable data pipelines from diverse sources including APIs, AWS native databases, and third-party systems with the focus on data quality, reliability, and performance
• Data Orchestration & Modeling: Leverage expert-level experience with dbt and Snowflake to structure, transform, and organize data for improved accessibility and usage
• Monitoring & Troubleshooting: Implement and maintain comprehensive data monitoring and alerting processes to ensure pipeline reliability
• Technical Mentorship: Collaborate with the team on technical design discussions and share best practices to support scalable, reliable, and well-structured data solutions
• Cross-Functional Collaboration: Work closely with engineering, product, and analytics teams to deliver data solutions that drive business value and to communicate complex technical topics to a variety of audiences
• Implementing Standards: Establish best-in-class processes, implement CI/CD for data pipelines, reproducible analytics, and rigorous code review, testing, and documentation standards

Requirements:

• 6+ years of experience in data engineering or related fields
• Proficiency in SQL and at least one programming language (e.g., Python)
• Strong experience with cloud platforms, particularly AWS (RDS, Redshift, S3, Lambda, etc.), Snowflake, GCP
• Hands-on experience with building and maintaining scalable ETL pipelines, monitoring data quality and debugging data workflows
• Advanced-level proficiency with dbt and experience with data orchestration tools like Dagster or Airflow
• Hands-on experience with data integration from APIs and CDC processes
• Deep understanding of data modeling, warehousing concepts, and performance optimization
• Excellent communication and collaboration skills, with the ability to bridge technical and non-technical teams
• A proactive, ownership-driven mindset with a passion for solving complex data challenges