Software Engineer - Data Integration

What you'll do

• Design and build reliable data pipelines for ingestion, transformation, and distribution of large-scale datasets
• Develop ETL/ELT workflows using distributed computing frameworks on cloud infrastructure
• Build API-first services exposing ingestion, processing, and distribution capabilities
• Implement data quality validation, monitoring, and observability
• Build reusable platform components serving downstream consumers
• Take ownership of components within the data integration platform and drive their reliability and iteration
• Build partner and destination integrations end-to-end including throughput tuning and operational handoff
• Apply GDPR, CCPA, and Samba data governance requirements to systems
• Collaborate with team members and adjacent teams to understand downstream use cases
• Drive technical design for components, produce design documents, and participate in architecture discussions
• Conduct code reviews and uphold standards for code quality, testability, and maintainability
• Build working relationships with adjacent teams and reason about cross-functional requirements
• Own reliability of components, monitor health, respond to incidents, and follow through on post-mortem improvements
• Participate in on-call rotations and contribute to improving operational practices
• Build and maintain CI/CD pipelines, deployment processes, and testing coverage

Requirements

• 5+ years of professional software engineering experience with a Bachelor's degree in Computer Science, Software Engineering, or related technical field (or 3+ years with a Master's, PhD with no prior experience, or equivalent)
• Meaningful focus on data engineering, backend systems, or distributed data infrastructure
• Proficiency in Python and SQL; ability to write clean, well-tested, production-ready code
• Hands-on experience with distributed processing frameworks (e.g., Spark, Databricks) in production
• Hands-on production experience building cloud-native data systems on AWS, GCP, or Databricks
• Experience building API-first services with focus on correctness and reliability
• Working experience with streaming or event-driven data processing frameworks (e.g., Kafka, Flink, Spark Streaming)
• Experience with workflow orchestration tools (Apache Airflow, dbt, Prefect)
• Familiarity with data privacy regulations (GDPR, CCPA) and understanding of their impact on system design
• Clear communicator who participates actively in design discussions and works well across teams
• Comfortable advising more junior engineers on technical matters

Tech stack

Benefits