We're hiring
Senior Full Stack Data Engineer
Capital Numbers is seeking a senior-level Full Stack Data Engineer to design, build, and scale core enterprise data infrastructure. This role demands an engineering-first mindset to take ownership of end-to-end data architecture, real-time pipelines, backend API integrations, platform reliability, and AI-ready data foundations. Operating from our Hyderabad office, the ideal candidate will work on-site, drive architectural decisions independently, optimize production-scale systems, and enforce high technical standards while collaborating with cross-functional leadership teams.
- Function
- Data Engineering & Platform Architecture
- Location
- Hyderabad
- Mode of Work
- From Office
- Experience
- 6 - 8 Years
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
Qualification & Experience
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.