Senior Backend Engineer - Real-Time Data Systems

Weekday AI

11d•$180,000 - $280,000

About The Position

We are looking for a seasoned backend engineer who excels at building high-performance systems that power real-time data processing at scale. You will architect and implement backend services that ingest, transform, and correlate massive volumes of data across distributed environments. This role is ideal for someone who thrives in fast-paced, data-intensive ecosystems and enjoys solving complex engineering challenges with clean, efficient, and reliable solutions.

Requirements

Strong experience developing backend systems in Python or another modern backend language.
Proven track record of building large-scale data ingestion or streaming systems.
Deep hands-on knowledge of orchestration tools (Temporal, Celery, Airflow, etc.).
Solid understanding of distributed systems, concurrency, and performance tuning.
Experience handling high-volume, high-velocity data streams in production environments.
You approach problems with a systems-thinking perspective.
You write clean, well-tested, maintainable code.
You enjoy optimizing at both micro and macro levels—from code paths to architecture.
You collaborate effectively with cross-functional teams and communicate with clarity.

Responsibilities

Design and implement high-throughput backend services capable of processing live data streams.
Build resilient ingestion frameworks that support low-latency, high-frequency data workflows.
Ensure real-time reliability through robust retry, error-handling, and monitoring mechanisms.
Develop and optimize workflow automation using orchestration tools such as Temporal, Celery, Airflow, or similar systems.
Streamline data operations by designing efficient pipelines that support complex event flows.
Conduct deep-dive performance analysis to reduce latency, optimize queries, and fine-tune resource utilization.
Leverage advanced data modeling techniques to support scalable, distributed data operations.
Work closely with platform, data engineering, and infrastructure teams to enhance ingestion, transformation, and processing layers.
Integrate backend systems with cloud environments, security layers, and third-party tools.
Contribute to architectural discussions and long-term technology roadmap planning.
Investigate production issues across distributed pipelines and drive root-cause resolution.
Continuously improve backend reliability, observability, and fault-tolerance.