Hiring Alert - Stagg Application Architect - Hybrid - BI-CFFID

Bounteous; Gurugram District, Chennai District, Bengaluru; Hybrid; INR 4,000,000 - 7,000,000; Full time

Job summary

Bounteous is seeking a Staff Application Architect in India to lead architecture and development of our customer-facing analytics engine. You will own end-to-end data modeling, semantic layer, and embedded analytics, ensuring a single source of truth across dashboards and APIs.

You will guide cross‑functional teams, optimize performance, and mentor engineers, with strong expertise in Ruby on Rails, PostgreSQL, Cube.js, and embedded BI platforms such as ThoughtSpot or Looker.

Qualifications

• 8+ years of experience in software architecture and SaaS analytics.
• Strong expertise in Ruby on Rails and PostgreSQL.
• Experience with embedded analytics platforms and data modeling.

Responsibilities

• Design and maintain a low-latency analytics stack end to end.
• Build scalable backend services in Ruby on Rails powering analytics.
• Develop ingestion pipelines from PostgreSQL and Kafka/Kinesis.
• Model metrics with Cube.js and ensure consistency across surfaces.
• Integrate embedded BI/analytics platforms with SDKs and theming.
• Optimize OLAP query performance and API response times.
• Define REST/GraphQL APIs for embedded analytics needs.
• Enforce multi-tenant data security in semantic and API layers.
• Provide technical leadership and mentorship across teams.

Skills

Ruby on Rails

Architecture

PostgreSQL

Data Modeling

Cube.js

Kafka

REST/GraphQL APIs

Embedded Analytics

SDK Integration

Tools

Cube.js

Kafka

REST APIs

GraphQL

Embedded SDK Integration

Job description

Hello Everyone,

Greetings from Bounteous!!

We have an excellent Opening for the below Skills:

Job Title: Staff Application Architect

Experience: 8+Years

Primary Skills: Ruby on Rails, Architecture, Postgresql, Data Modelling

Job Location:

Kindly share the updated Profile to [e-mail] along with the below details,

Current CTC:

Expected CTC:

Available Time to Join:

Preferred Location:

Job Description

We are looking for a Staff Application Engineer to lead the architecture and development of our customer-facing analytics engine. Our Sales Engagement Platform processes millions of events daily from email interactions to live call metadata. Your mission is to transform this firehose of raw data into high-performance, actionable insights, and to own the full path from data model to the customer-facing experience.
You will operate across the stack backend services, the semantic layer, and an embedded analytics UI (e.g., ThoughtSpot) ensuring customers see the same "Single Source of Truth" across every dashboard, report, and API, and that the embedded experience feels like a native part of our product.

Key Responsibilities

• Full-Stack Architecture: Design and maintain a low-latency analytics stack end to end, from ingestion through the semantic layer to the embedded analytics UI, capable of handling high-concurrency queries from thousands of concurrent SaaS users. Lead re-architecture efforts where needed to ensure long-term scalability.
• Backend Services: Build and maintain scalable backend services in Ruby on Rails (and other languages as needed) that power the analytics experience, including APIs consumed by the embedded UI and downstream systems.
• Real-time Ingestion: Build and optimize ingestion pipelines that move data from transactional databases (PostgreSQL) and event streams (Kafka/Kinesis) into our OLAP data store.
• Semantic Layer Development: Use Cube (Cube.js) to model complex sales metrics (e.g., "Sequence Conversion Rate,", "Attributed Revenue,", "Meeting Booked Rate") and ensure consistency across every surface that consumes them, including the embedded analytics layer.
• Embedded Analytics Integration: Integrate and customize an embedded BI/analytics platform (e.g., ThoughtSpot, Looker, Sigma) within our product SDK integration, white-labeling/theming, single sign-on, and API-driven customization so the experience feels native rather than bolted on.
• Performance Engineering: Optimize across the stack OLAP query performance, Cube pre-aggregations, API response times, and embedded dashboard load times — to ensure widgets load in under 300ms.
• API Strategy: Design and expose data models via REST/GraphQL APIs with a strong eye toward what the embedded analytics platform and third‑party consumers need.
• Data Governance: Implement multi-tenant security logic within the semantic layer and API layer to ensure strict data isolation between customer accounts, and enforce it consistently through the embedded tool's row-level security model.
• Technical Leadership: As a Staff‑level engineer, set technical direction across teams, mentor senior and mid-level engineers, and drive architectural decisions that span the data, backend, and embedded‑UI layers.

Technical Requirements

• Full‑Stack Proficiency: Strong backend experience (Ruby on Rails) plus hands‑on experience integrating a third‑party embedded analytics/BI platform (e.g., ThoughtSpot, Looker, Sigma, embedded Power BI) into a SaaS product via SDKs and APIs — including auth, theming, and customization.
• Data Store Mastery: Strong knowledge of PostgreSQL, including analytical query optimization.
• Semantic Modeling: Experience with Cube (Cube.js) or a comparable semantic layer, including pre‑aggregations and multi‑tenant security contexts.
• Streaming & Messaging: Hands‑on experience with Kafka or similar event‑streaming systems.
• Language: Mastery of complex SQL and the ability to translate business logic into code‑based data schemas.
• Staff‑Level Scope: Track record of leading cross‑team technical initiatives, mentoring engineers, and making architectural tradeoffs that hold up in production at scale.

Bonus Points If You Have

• Direct experience embedding ThoughtSpot specifically (Embed SDK, Liveboards, TML/metadata APIs).
• Experience building analytics specifically for CRM or Sales Tech ecosystems.
• Experience with OLAP/columnar data stores (Apache Pinot, ClickHouse, StarRocks, etc.).
• Practical experience with dbt, Airflow, or Spark for data transformation and orchestration.
• Experience with Infrastructure as Code (Terraform, Kubernetes) for managing services and data clusters.
• Proficiency using AI tools (Claude, Augment, etc.) to navigate legacy codebases and close technical gaps.