Senior Backend Software Engineer

Reacher•San Francisco, CA

About The Position

About Reacher We're the #1 TikTok Shop partner helping brands like Under Armour, Hanes, HeyDude, and Logitech scale their affiliate marketing. We've crossed 7 figures in ARR and are rapidly scaling our team this year. Our vision is to become the Hubspot for creator marketing, powering brands and creators to connect and grow across all commerce platforms (Youtube Shopping, Instagram Shopping, Shopify, Amazon). We're building key infrastructure for the creator economy and implementing AI with the world's largest brands and creators. Your work will directly impact users on day 1 - our user base depends on our product daily. What You'll Do Architect & Own Core Systems : Lead the end-to-end design and implementation of high-throughput backend services and complex data pipelines. Scale Data Infrastructure: Design and optimize data engineering systems that handle massive streams of commerce and creator data, ensuring reliability and observability. Technical Leadership: Set the gold standard for engineering excellence. Define our patterns for schema design, service boundaries, and distributed data processing . Lead and shape engineering architecture - set standards for code quality, testing, and development practices across the stack Mentor and guide other engineers , establishing best practices and patterns Drive Velocity: Balance "shipping fast" with "building right," ensuring our infrastructure scales ahead of our growth trajectory. Own the testing strategy for our entire stack , moving beyond unit tests to include end-to-end integration tests , load testing , and automated data quality checks . You're a Fit If 5–9 years of professional experience including significant time spent in high-growth startups or big-tech environments owning "Tier 0" services. Backend & Data Mastery: You are expert-level in Python and deeply comfortable navigating both relational databases ( PostgreSQL ) and specialized data systems. Proven Data Engineering Track Record: You’ve built and maintained production-grade ETL/ELT pipelines, handled schema evolution at scale, and managed data lake/warehouse integrations. Systems Thinker: You don't just write functions; you think in terms of eventual consistency, backpressure, and system bottlenecks. Product Intuition: You care about the why behind the data. You can identify when a requirement is technically feasible but strategically flawed. Can be the technical expert and set standards for engineering quality Resourceful and thrive in ambiguous environments —you figure things out independently You believe that code isn't 'done' until it's tested, documented, and observable Technical Skills We Value Core Backend: Expert Python, Django, FastAPI, and advanced PostgreSQL (indexing, optimization, locking patterns). Data Stack: Hands-on experience with GCP data tools (Cloud Composer/Airflow, BigQuery, Pub/Sub, Cloud Run Jobs) or equivalent (Kafka, Spark, Snowflake). Reliability: Deep knowledge of observability (distributed tracing, structured logging) and testing strategies for data integrity. Experience with distributed locking , idempotency patterns , and microservices orchestration . Testing & Reliability: Expert-level knowledge of testing frameworks (e.g., pytest , Cypress ). Deep experience in Data Quality testing (e.g., Great Expectations, dbt tests) to ensure pipeline accuracy. Bonus Points If You've worked at an early-stage startup or been a first/early engineering hire You’ve built systems that process millions of events per day. You've led technical initiatives or mentored junior engineers You're curious about AI, e-commerce, or automation—we work in this space You've shipped side projects or contribute to open-source data tooling or backend frameworks. You have experience with AlloyDB or advanced vector databases for AI applications. Why Join Us Post-revenue company solving real problems for real customers Be a technical leader : define our engineering culture and standards as we scale High autonomy and visibility : no boring tickets High Leverage: At our scale, your architectural decisions will directly impact the success of global brands. Direct Impact: Your code reaches users and impacts revenue within days. Strong engineering-first culture Shape both the product and the company When Applying Feel free to send a short note about something you've built and why this role excites you. GitHub/LinkedIn/resume is great, but we care more about how you think and build!

Requirements

5–9 years of professional experience including significant time spent in high-growth startups or big-tech environments owning "Tier 0" services.
Expert-level in Python and deeply comfortable navigating both relational databases ( PostgreSQL ) and specialized data systems.
Built and maintained production-grade ETL/ELT pipelines, handled schema evolution at scale, and managed data lake/warehouse integrations.
Think in terms of eventual consistency, backpressure, and system bottlenecks.
Care about the why behind the data.
Can identify when a requirement is technically feasible but strategically flawed.
Can be the technical expert and set standards for engineering quality
Resourceful and thrive in ambiguous environments —you figure things out independently
Believe that code isn't 'done' until it's tested, documented, and observable
Expert Python, Django, FastAPI, and advanced PostgreSQL (indexing, optimization, locking patterns).
Hands-on experience with GCP data tools (Cloud Composer/Airflow, BigQuery, Pub/Sub, Cloud Run Jobs) or equivalent (Kafka, Spark, Snowflake).
Deep knowledge of observability (distributed tracing, structured logging) and testing strategies for data integrity.
Experience with distributed locking , idempotency patterns , and microservices orchestration .
Expert-level knowledge of testing frameworks (e.g., pytest , Cypress ).
Deep experience in Data Quality testing (e.g., Great Expectations, dbt tests) to ensure pipeline accuracy.

Nice To Haves

Worked at an early-stage startup or been a first/early engineering hire
Built systems that process millions of events per day.
Led technical initiatives or mentored junior engineers
Curious about AI, e-commerce, or automation—we work in this space
Shipped side projects or contribute to open-source data tooling or backend frameworks.
Experience with AlloyDB or advanced vector databases for AI applications.

Responsibilities

Lead the end-to-end design and implementation of high-throughput backend services and complex data pipelines.
Design and optimize data engineering systems that handle massive streams of commerce and creator data, ensuring reliability and observability.
Set the gold standard for engineering excellence.
Define our patterns for schema design, service boundaries, and distributed data processing
Lead and shape engineering architecture - set standards for code quality, testing, and development practices across the stack
Mentor and guide other engineers , establishing best practices and patterns
Balance "shipping fast" with "building right," ensuring our infrastructure scales ahead of our growth trajectory.
Own the testing strategy for our entire stack , moving beyond unit tests to include end-to-end integration tests , load testing , and automated data quality checks