You will get a public app / website hosted on a VPS with Docker
Project details
Production-grade VPS deployment from a backend engineer who runs this stack for real - Docker Compose, Traefik reverse proxy, auto-renewing Let's Encrypt SSL, and a hardened firewall, all handed over with a written runbook so you stay in control. Not a tutorial-grade setup: built from live production experience and the unglamorous failures I've already debugged so you don't have to.
Programming Languages
HTML & CSS, JavaScript, TypeScriptCoding Expertise
Cross Browser & Device Compatibility, Security, DesignWhat's included
| Service Tiers |
Starter
$60
|
Standard
$150
|
Advanced
$300
|
|---|---|---|---|
| Delivery Time | 3 days | 5 days | 7 days |
Number of Revisions | 1 | 3 | 5 |
Design Customization | |||
Content Upload | |||
Responsive Design | |||
Source Code | - |
Optional add-ons
You can add these on the next page.
Fast Delivery
+$30 - $100
Additional Revision
+$25
Source Code
(+ 1 Day)
+$100
30-day Post Deployment Support
(+ 2 Days)
+$50About Sundaresan
Data Engineer | AI Pipelines | Healthcare Specialization
Bengaluru, India - 3:27 am local time
Hi, I'm Sundaresan — a Data Engineer who builds and owns the entire data stack, not just a part of it. I've designed end-to-end pipelines, real-time architectures, analytics layers, and ML infrastructure from scratch — and I've done it in high-stakes environments like tele-ICU healthcare and Series A SaaS startups.
I don't stand on the sidelines with a list of suggestions. I get into the arena and build.
- Trusted By: Teams at Cloudphysician, Toplyne (Peak XV / Sequoia-backed), and Swiggy — across healthcare, developer tools, and consumer tech.
- Impact Delivered: 1M+ events/day pipelines, 99.9% reliability, 3–5× query performance improvements, $X million incremental revenue identified through ML-driven analytics.
- Approach: I join as a full-stack data owner — data engineer, analytics engineer, and analyst rolled into one — and stay until the problem is solved.
🟢 Technical Skills
- Designed and owned end-to-end data pipelines — CDC, streaming, and batch — with sub-5-minute latency at production scale
- Built unified data architectures (BigQuery, Snowflake, AWS) with medallion architecture and clean separation of concerns
- Established product analytics infrastructure covering 90%+ of user interactions across web and mobile
- Built real-time ML model monitoring frameworks for 100+ models using MLFlow, Airflow, and Grafana
- Worked with HL7, FHIR, ICD and SNOMED codes — HIPAA and ABDM-compliant clinical data pipelines
- ETL and data science pipeline migration to PySpark, reducing infrastructure costs by 30%
LLM integration in production: Gemini Flash for document parsing, speech-to-text transcription, and ambient AI note-taking
- Power user of dbt, Metabase, Looker, Grafana, and modern data stack tooling
- Proficient in Python, SQL, Spark, Airflow, and workflow automation (n8n)
🟢 Soft Skills
- Clear, direct communicator — comfortable working with doctors, product managers, and engineers alike
- Neurotic about data model design — I will push back if the schema is wrong
- Full ownership mentality: I treat your data infrastructure as if it were mine
- Strong documentation practices and data governance discipline
- Proactive in surfacing insights, not just shipping pipelines
🟢 Roles and Responsibilities
- Design, build, and own data pipelines from ingestion through to BI and ML consumption
- Establish data infrastructure from scratch — empty cloud project to production-grade ecosystem
- Partner with product, engineering, and clinical/business teams to translate requirements into data models
- Build and maintain KPI dashboards that reduce reporting time from days to minutes
- Deploy and monitor ML pipelines in production with automated alerting and drift detection
- Ensure compliance with healthcare data standards (HIPAA, HL7, FHIR, ABDM)
- Mentor and scale data teams; establish best practices and coding standards
🟢 Conclusion
With 5+ years building the full data stack across healthcare and SaaS, I specialise in taking messy, fragmented data environments and turning them into reliable, low-latency systems that teams actually trust. Whether you need a pipeline built from zero, a slow warehouse optimised, or an ML monitoring framework standing up — I own it end-to-end.
Clean data, fast queries, and systems that don't break at 3am. That's what I deliver.
Steps for completing your project
After purchasing the project, send requirements so Sundaresan can start the project.
Delivery time starts when Sundaresan receives requirements from you.
Sundaresan works on your project following the steps below.
Revisions may occur after the delivery date.
Kickoff & access check
I confirm your requirements, verify SSH access to the VPS, and check that your domain's DNS points to the server. I'll flag anything missing before the clock starts so there are no surprises.
Server preparation & hardening
I update the OS, configure the UFW firewall to expose only ports 80 and 443, and install Docker and Docker Compose so the host is clean and secure.