Senior Data Engineer

Topstep

3d•Hybrid

About The Position

Are you a hands-on data expert who thrives on building scalable pipelines, shaping modern data platforms, and turning raw data into business value? As a Senior Data Engineer, you will architect and implement the foundational systems that power analytics, automation, and insight across the company. Working at the crossroads of data engineering, analytics, and business, you’ll lead the development of robust data pipelines, optimize workflows with tools like dbt, and drive best practices that scale with our growth. If you're passionate about solving tough data challenges, influencing architecture, and creating impact across teams, join us and help elevate how data is used company-wide because we are never finished learning, and are always seeking to improve.

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.

Responsibilities

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.
Leverage expert-level experience with dbt and Snowflake to structure, transform, and organize data for improved accessibility and usage.
Implement and maintain comprehensive data monitoring and alerting processes to ensure pipeline reliability.
Collaborate with the team on technical design discussions and share best practices to support scalable, reliable, and well-structured data solutions.
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.
Establish best-in-class processes, implement CI/CD for data pipelines, reproducible analytics, and rigorous code review, testing, and documentation standards.