Senior Full-Stack Engineer, Payments
Circle
MySQLPostgresReactRubyRuby on RailsSCSSTypeScript
Software Engineer – Data Platform
ALGOQUANT
full-time
Posted on:
Location Type: Remote
Location: Remote • 🌎 Anywhere in the World
Visit company websiteJob Level
SeniorLead
Tech Stack
AirflowApacheAWSAzureCloudDockerGoogle Cloud PlatformKafkaKubernetesLinuxPythonPyTorchSparkTensorflow
About the role
- Design, build, and maintain real-time and batch data processing pipelines for market, alternative, and on-chain data sources.
- Ensure high availability and low latency across critical ingestion and transformation processes.
- Develop and evolve our internal Data Lake and the surrounding data processing ecosystem.
- Implement modern lakehouse technologies to enable scalable, queryable, and versioned data storage.
- Build validation, monitoring, and alerting systems to guarantee the accuracy, consistency, and completeness of data.
- Establish robust data quality frameworks and observability tooling across the pipeline stack.
- Develop and maintain internal Python and C++ libraries for feature calculation, data processing, backtesting, and ML inference.
- Promote code reuse, performance optimization, and reproducibility across teams.
- Work closely with quant researchers, traders, and the execution team to understand data requirements and support their workflows.
- Translate research and trading needs into reliable, production-grade data infrastructure.
Requirements
- Experience: 10+ years in software engineering or data infrastructure development.
- Languages: Expert-level Python and C++.
- Distributed Data Systems: Proven experience with Spark, Flink, Slurm, Dask, or similar frameworks.
- Data Lakehouse Technologies: Hands-on with Apache Iceberg, Delta Lake, or equivalent systems.
- Messaging & Streaming: Strong experience with Kafka or similar streaming platforms.
- Infrastructure: Proficient with Linux, Kubernetes, Docker, and workflow orchestrators like Airflow.
- Machine Learning Exposure: Familiarity with PyTorch, TensorFlow, or model inference frameworks.
- Cloud Platforms: Experience deploying and maintaining systems on AWS, GCP, or Azure.
- AI Engineering Tools: Experience using Claude Code, GitHub Copilot, Codex, or similar AI-assisted coding tools.
Benefits
- Help build the data backbone of a cutting-edge digital asset investment platform.
- Collaborate directly with world-class engineers, researchers, and quants.
- Be part of a fully remote, high-performance culture that values innovation, autonomy, and continuous learning.
- Shape the future of data infrastructure in a company where technology drives alpha.
Applicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard skills
PythonC++SparkFlinkSlurmDaskApache IcebergDelta LakeKafkaMachine Learning
Soft skills
collaborationcommunicationproblem-solvingperformance optimizationcode reusedata quality assuranceobservabilityworkflow support