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Remote, mid-level generalist title and common Python/PySpark skillset create high applicant competition.
Core skills (Python, PySpark, SQL, cloud) are highly transferable across industries.
Explicit 2–4 years plus mandatory Python, PySpark, SQL, and cloud experience makes screening moderately strict.
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Develop and maintain scalable backend systems and distributed data pipelines powering a multi-tenant B2B SaaS platform.
Build production-grade Python web services and REST APIs using frameworks like FastAPI and Flask, ensuring security and scalability.
Troubleshoot production issues and continuously improve platform reliability, performance, and scalability.
2–4 years of experience in backend or data engineering in scalable product environments.
Strong Python programming skills with experience in backend applications, REST APIs, and data processing.
Hands-on experience with PySpark, SQL, relational database design, query optimization, and cloud platforms (Microsoft Azure preferred or AWS).
Experience with Docker, Git, and troubleshooting production systems using logs and metrics.
Experienced in B2B SaaS or data-intensive product companies, preferably with exposure to supply chain, compliance, or risk management domains.
Familiarity with modern cloud data platforms like Databricks, Snowflake, or Lakehouse technologies (Delta Lake).
Has worked with or exposed to Java, Kafka, Redis, Apache Airflow, or Kubernetes.