Software Engineer - Data Infrastructure

Responsibilities

• Design, build, and maintain scalable data pipelines and infrastructure
• Develop batch and streaming systems for ingesting and processing large-scale data
• Own core components of the data platform (warehouse, lake, orchestration, tooling)
• Implement data modeling, transformation, and versioning frameworks
• Ensure data quality, observability, and reliability across pipelines
• Optimize systems for performance, cost, and scalability
• Build tooling to support reproducible datasets and experimentation
• Partner with data scientists and engineers to productionize ML and analytics workflows
• Contribute to secure and compliant data infrastructure in cloud environments

Requirements

Must-Have:

• 3–7+ years of experience in data infrastructure, infrastructure, or platform engineering
• Strong understanding of real-time and batch data processing systems, including stream processing, messaging architectures, and large-scale data workflows (Spark, Kafka, etc.)
• Experience with modern data tooling (dbt, Airflow, etc.)
• Strong understanding of data modeling, ETL/ELT, reverse ETL, and orchestration
• Experience designing for scalability, reliability, and observability
• Hands-on experience with cloud platforms (AWS/GCP) and storage systems
• Ability to operate in a fast-moving startup environment with high ownership

Nice-to-Have:

• Familiarity with ML infrastructure or feature stores
• Experience with data versioning, lineage, or reproducibility systems
• Background in security, compliance, or high-sensitivity data domains
• Previous experience at an early-stage startup

Compensation

• Estimated salary range: $160K - $225K / year
• Total compensation may include Restricted Stock units, sign-on bonus and other potential future incentives