> Markdown version of [/jobs/ext/3661590-sr-backend-data-engineer](https://www.wearedevelopers.com/jobs/ext/3661590-sr-backend-data-engineer). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md).

---

# Sr. Backend/Data Engineer

- **Company:** BRIGHTEDGE LLC
- **Location:** Foster City, CA, United States (Remote available)
- **Experience:** Expert
- **Contract:** Permanent contract
- **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Amazon Web Services, BigQuery, Mobile Application Development, Cloud Computing, Cloud Storage, Code Generation, Software Quality, Databases, Continuous Integration, Data Warehousing, Cursor, Database Queries, Database Schema, Software Debugging, Programming Tools, Distributed Systems, Fault Tolerance, Python (Programming Language), Routing, Performance Tuning, Software Architecture, Query Optimization, Software Engineering, SQL Databases, Data Streaming, Management of Software Versions, Data Processing, GitHub Copilot, Claude Code, Snowflake, Indexer, AI Coding Agents, Backend, Information Technology, Apache Flink, Apache Kafka, Build Tools, Graphql, Spark Streaming, Vertica, Stream Processing, Data Pipelines, Amazon Redshift, Microservices
- **Published:** October 9, 2026
- **Apply:** https://arc.dev/remote-jobs/j/redirect/pq002p35og

## About the Role

* Bachelor's degree in Computer Science or Information Technology only.
 * Proven track record of shipping production-grade software with measurable impact.
 * Proven experience designing, versioning, and deploying external-facing APIs, with strong ownership of database schema modelling and query-performance tuning.
 * Demonstrated ability to deliver high-quality work quickly using modern AI tools.
 * Strong experience in Python for production-grade backend systems; Go is a plus.
 * Hands-on experience with distributed systems, backend architecture, and cloud platforms such as AWS or GCP.
 * Solid expertise in SQL, schema design, indexing, and query optimisation.
 * Experience in writing queries/views for product, analytics, or customer-facing use cases, more on reading and design, not just doing the pipeline.
 * Experience with data warehouses such as BigQuery, Redshift, Snowflake, or ClickHouse.
 * Working experience with real-time or batch data processing systems such as Kafka, Spark Streaming, or Flink.
 * Strong ownership mindset, clear communication, and a bias toward shipping reliable solutions.

AI-Native Development Expectations:

 * Comfortable using tools like Cursor, Claude Code, GitHub Copilot, or equivalent AI assistants as part of your daily workflow.
 * Able to break down large problems, use AI to accelerate implementation, and still maintain strong judgment on architecture and code quality.
 * Comfortable reviewing AI-generated code critically, improving it, and ensuring it meets maintainability and production standards.
 * Able to use AI to speed up testing, debugging, documentation, and exploratory problem solving without relying on black-box output.

## Description

We are looking for Backend Engineers who can design and build scalable, reliable, and data-intensive backend systems while working in an AI-native development environment. This role sits at the intersection of backend engineering, data pipelines, automation, and modern AI-assisted software development. You will not be training models, but you will use AI tools and AI-powered services to build faster, ship cleaner code, and create more intelligent backend workflows., * Design, build, and own robust public-facing APIs (REST/GraphQL) and microservices consumed by external developers and customers, alongside reliable data ingestion pipelines.

 * Integrate with diverse data sources, including APIs, databases, streaming systems, cloud storage, and third-party services.
 * Build systems that are scalable, fault-tolerant, observable, and cost-efficient.
 * Take end-to-end ownership of database schema design, query-layer optimisation, data modelling, and self-healing pipelines to support fast search and analytical query needs.
 * Work with product, platform, and data teams to ensure smooth and reliable data flow across systems.
 * Use AI coding assistants and AI-native developer tools to accelerate delivery, refactor code, debug issues, and improve documentation.
 * Build or integrate AI-driven automation for tasks like anomaly detection, intelligent routing, query optimisation, and operational support.
 * Contribute to testing, monitoring, alerting, CI/CD, and production readiness for all services you build.