Senior Integration Engineer - Embedded Analytics (Multi-Tenant SaaS)

Our US-based client is looking for a full-time, remote Senior Integration Engineer - Embedded Analytics (Multi-Tenant SaaS) with 7+ years of experience. The role focuses on designing and building the backend services and integrations that enable secure, scalable, multi-tenant embedded analytics within a SaaS platform. This role sits at the intersection of application engineering, identity management, and the data platform. The primary focus is on integrating embedded analytics tools into a multi-tenant application with strict tenant isolation, SSO-based access control, and high-concurrency usage patterns.

While AWS QuickSight is the primary BI platform, we are open to candidates with experience embedding other modern, multi-tenant analytics solutions (such as Looker, Tableau, Power BI, Mode, or Superset). The emphasis is on a strong understanding of how embedded analytics work in SaaS environments, rather than on expertise in a single tool.

This is a senior-level role with meaningful influence over analytics architecture, security considerations, and integration standards across the platform.

Our client provides integrated software and marketing solutions for the hospitality industry, specializing in short-term rental management. Their platform provides vacation rental companies with an enterprise-class Property Management System integrating booking, guest communications, and financial reporting systems - all built with partner organization integrations in mind.

Responsibilities

Design and implement multi-tenant embedded analytics within customer-facing SaaS applications

Build backend services that generate and manage embed sessions, URLs, and permissions dynamically per tenant and user

Implement SSO and identity propagation (Auth0, Cognito, OIDC) to enforce tenant-aware access and role-based controls

Ensure row-level and dataset-level security is consistently applied across embedded analytics experiences

Partner with Analytics Engineers to align datasets, semantic models, and RLS logic with application roles

Translate analytics platform constraints into clean, reliable application-facing abstractions

Design and maintain tenant-aware APIs that abstract analytics tools behind stable, versioned interfaces

Build service-layer patterns that isolate application code from direct BI or warehouse dependencies

Implement caching, pagination, throttling, and batching strategies for high-concurrency analytics traffic

Ensure APIs gracefully handle tenant onboarding / offboarding and evolving analytics assets

Collaborate with the Data Platform Architect to design scalable backend patterns supporting hundreds of tenants

Optimize service-to-warehouse and service-to-analytics-tool interactions for latency and cost efficiency

Identify and mitigate failure modes in embedded analytics workflows (timeouts, permission drift, stale sessions)

Contribute to architecture documentation, integration diagrams, and design reviews

Enforce least-privilege access and tenant isolation across all analytics integrations

Ensure compliance with PII, data governance, and audit requirements in embedded reporting flows

Implement logging and audit trails for analytics access and permission changes

Partner with InfoSec to support security reviews and compliance initiatives

Implement CI / CD pipelines for integration services and analytics-related configuration

Contribute to infrastructure-as-code (Terraform or CloudFormation)

Support observability through CloudWatch, Datadog, or OpenTelemetry

Improve operational reliability through monitoring, alerting, and runbook development

Act as a technical owner for embedded analytics integrations

Partner with Product to shape analytics capabilities and roadmap decisions

Mentor mid-level engineers on integration patterns, security, and service design

Drive standards for analytics integration consistency and developer experience

Required Experience :

Excellent English communication skills

7+ years of backend or integration engineering experience in SaaS environments

Strong experience building backend services in Node.js, Python, or PHP

Hands-on experience embedding analytics or BI tools into multi-tenant applications

Strong understanding of SSO, OAuth2, OpenID Connect, and identity propagation

Experience implementing tenant-aware access controls (RLS, role mapping, dataset isolation)

Solid SQL knowledge and experience integrating with data warehouses

Proven experience with CI / CD pipelines and cloud-native deployment (AWS or equivalent)

Desired Experience :

Bachelor's degree in Computer Science or some technical engineering

Experience embedding AWS QuickSight in multi-tenant SaaS applications

Experience with other embedded analytics platforms (Looker, Tableau, Power BI, Superset, Mode, etc.)

Familiarity with row-level security models and permission orchestration

Experience with Auth0 or Cognito in analytics contexts.

Knowledge of caching layers (Redis) and high-concurrency API design

Exposure to data governance, lineage, or analytics access auditing

Additional Information

Knowing your ideas are heard and matter, think big!

You get to own your job and be recognized for your contributions

Work with smart and creative people

Making mistakes is human. Let's learn from them. Be transparent!

We recognize you as an individual, with no presumptions or judgment. Be the extraordinary you!

15 days Paid Time Off (PTO), 1 floating day, 3 sick days, and designated national holidays

Start : ASAP

About Velozient

We are a privately held, nearshore software development company providing outsourced development resources to North American companies. Our mission is to offer development talent who enjoy taking on challenging work, want to grow their skills and experiences building software, and excel in a fast-paced, dynamic team environment. We focus on providing world-class remote resources who work as valued members of client teams. If this type of opportunity excites you, then consider joining our team!