Job highlights

- Pipeline Architecture Engineering: Design,build,and maintain scalable batch and real-time streaming ETL / ELT data pipelines,cloud data platforms,and lakehouse storage

Job Summary 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 in office, drive architectural decisions independently, optimize production-scale systems, and enforce high technical standards while collaborating with cross-functional leadership teams.

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.

Location

Hyderabad Disclaimer: This job posting has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.

📌 Sr Full Stack Data Engineer (Hyderabad)
🏢 Capital Numbers Infotech
📍 Hyderabad