Scalable Backend For SaaS Analytics Platform
Budget: ₹250,000 – ₹500,000 INR
We are building a SaaS platform that combines analytics, attribution, and engagement features into one solution. We need a backend engineer who can design and implement the MVP backend with scalability and cost-efficiency in mind.
Key Responsibilities:
Build secure event ingestion APIs (REST/GraphQL) with batched event support.
Implement streaming pipeline (serverless queues or event brokers) to process and store events.
Design and manage data storage:
Hot store (real-time OLAP database)
Cold store (object storage with Parquet/columnar format)
Profile DB (SQL database)
Implement identity resolution (merge anonymous + logged-in users).
Build attribution logic (mapping user actions like clicks → installs/conversions).
Create a simple campaign trigger system (event-based push/email/SMS).
Ensure multi-tenant support with project-level isolation.
Implement basic dashboards/APIs to fetch events, active users, funnels, and attribution reports.
Ensure scalability and low infra costs (serverless-first, partitioned storage, compression).
Add privacy features (data export and deletion requests).
Must-have Skills:
Strong experience in backend development (Go, Node.js, or Python).
Hands-on with cloud platforms (AWS/GCP/Azure).
Experience with event-driven systems (message queues, pub/sub, or stream processors).
Proficiency in databases: SQL + real-time OLAP.
Knowledge of real-time analytics pipelines and attribution logic.
Familiarity with API design, authentication, and rate-limiting.
Nice-to-have Skills:
Experience with push/email/SMS campaign integrations.
Knowledge of data privacy compliance (GDPR/CCPA).
Exposure to observability tools (metrics, logging, dashboards).
Deliverables (MVP Phase):
Event ingestion API + SDK specification.
Pipeline to store events in OLAP + object storage.
Profile DB with identity resolution.
Basic attribution logic.
Campaign trigger (event → notification).
Admin API/dashboard for reporting (users, funnels, attribution).
Engagement:
Duration: 2–3 months (MVP build).
Type: Fixed price preferred, milestone-based.
Key Responsibilities:
Build secure event ingestion APIs (REST/GraphQL) with batched event support.
Implement streaming pipeline (serverless queues or event brokers) to process and store events.
Design and manage data storage:
Hot store (real-time OLAP database)
Cold store (object storage with Parquet/columnar format)
Profile DB (SQL database)
Implement identity resolution (merge anonymous + logged-in users).
Build attribution logic (mapping user actions like clicks → installs/conversions).
Create a simple campaign trigger system (event-based push/email/SMS).
Ensure multi-tenant support with project-level isolation.
Implement basic dashboards/APIs to fetch events, active users, funnels, and attribution reports.
Ensure scalability and low infra costs (serverless-first, partitioned storage, compression).
Add privacy features (data export and deletion requests).
Must-have Skills:
Strong experience in backend development (Go, Node.js, or Python).
Hands-on with cloud platforms (AWS/GCP/Azure).
Experience with event-driven systems (message queues, pub/sub, or stream processors).
Proficiency in databases: SQL + real-time OLAP.
Knowledge of real-time analytics pipelines and attribution logic.
Familiarity with API design, authentication, and rate-limiting.
Nice-to-have Skills:
Experience with push/email/SMS campaign integrations.
Knowledge of data privacy compliance (GDPR/CCPA).
Exposure to observability tools (metrics, logging, dashboards).
Deliverables (MVP Phase):
Event ingestion API + SDK specification.
Pipeline to store events in OLAP + object storage.
Profile DB with identity resolution.
Basic attribution logic.
Campaign trigger (event → notification).
Admin API/dashboard for reporting (users, funnels, attribution).
Engagement:
Duration: 2–3 months (MVP build).
Type: Fixed price preferred, milestone-based.