Senior Full Stack Data Engineer | Capital Numbers | Capital Numbers

Roles & Responsibilities:

Pipeline & Architecture Engineering: Design, build, and maintain scalable batch and real-time streaming ETL/ELT data pipelines, cloud data platforms, and lakehouse storage.
Backend & API Development: Develop robust, production-grade REST APIs, microservices, and event-driven backends to integrate data platforms seamlessly with operational systems.
AI & Analytics Enablement: Structure clean data architectures, CDC pipelines, and semantic layers to support operational analytics, feature engineering, and downstream AI/ML workflows.
Platform Governance & Performance: Enforce data quality, observability, cost control, and monitoring while resolving production incidents and managing schema evolutions.
Infrastructure & DevOps: Manage containerized deployments, automated CI/CD pipelines, and cloud infrastructure monitoring across enterprise networking environments.
Leadership & Mentorship: Drive engineering best practices, conduct code reviews, unblock team members, and mentor junior engineers across projects.

Skills:

Data Engineering: Python, SQL, Spark / PySpark, Airflow, Kafka, Google Pub/Sub, dbt, Snowflake / BigQuery / Redshift, PostgreSQL / MySQL, Parquet / Delta Lake / Iceberg
Backend & Platform: REST APIs, FastAPI / Flask / Node.js, Microservices, Event-Driven Architectures, Message Queues (RabbitMQ / ActiveMQ), Async Processing
Cloud & DevOps: AWS / GCP / Azure, Docker, Kubernetes, CI/CD (GitHub Actions / Jenkins), Terraform basics, Juniper enterprise networking ecosystems
AI/ML Exposure: ML/AI data pipelines, Feature Stores, Vector Databases, LLM / RAG architectures, Real-Time Analytics
Soft Skills: Technical Ownership, Production Debugging, Systems Thinking, Mentorship, Executive Communication

Education: B.Tech / B.E. in Computer Science, IT, or equivalent engineering discipline (candidates from premier

institutes like IITs, NITs, BITS, IIITs preferred).

Track Record: Proven background building production-scale data platforms within product companies, SaaS

platforms, high-scale startups, or data-intensive software organizations.

Domain Advantage (Preferred): Prior experience in Healthcare Tech, EMR/HMIS systems, clinical data

platforms, or healthcare data privacy standards.

We value diversity and are an equal opportunity employer.