Senior Full Stack Engineer (Audience Builder & CDP)

Hello Everyone,

Hope you are doing good!!!!

My name is Pavan and I work with SPAR Information System., I have a great opportunity for you, please find the job details below, if you are interested in applying please send me your updated resume and best time for you to discuss about this opportunity in details.

Role: Senior Full Stack Engineer (Audience Builder & CDP)

Location: Remote

Duration: Long term contract

Based on the JD, the strongest candidates are those who combine:

1. React/TypeScript
2. Databricks/Delta Lake
3. Kafka/Event Hubs
4. Audience Builder/CDP experience
5. AI-assisted segmentation exposure

Biggest Hiring Risks

Candidates may have: React . Node.js.APIs

But lack: Audience segmentation .Databricks,Delta Lake,Kafka,CDP knowledge

These candidates may look technically strong but require significant ramp-up

A great candidate typically comes from one of these backgrounds

Option 1

CDP / MarTech

Examples:

• Adobe Experience Platform
• Real-Time CDP
• Audience Manager
• Salesforce Data Cloud

Option 2

Customer Analytics Platforms

Examples:

• Segment
• Customer 360
• Marketing platforms

Option 3

Full Stack + Data Engineering

Experience with:

• React
• Node/Python
• Databricks
• Kafka
• Customer data products

Critical Skills (Must Have)

1. React + TypeScript + Next.js

Why?

Because the Audience Builder UI itself is complex.

Examples:

• Rule builders
• Drag-and-drop conditions
• Nested AND/OR groups
• Audience preview screens
• Customer profile views

Candidates should have built complex business applications, not just websites.

2. API Design

The engineer will create APIs for:

• Audience creation
• Audience updates
• Audience preview
• Audience activation

Look for:

• Node.js
• Python
• REST API
• Microservices

3. Databricks / Delta Lake

This is one of the biggest differentiators.

Many React engineers won't have this experience.

Discussion point:

Audience calculations may run against hundreds of millions of customer records.

Databricks is likely the primary audience computation platform.

Good candidates should understand:

• Spark
• Delta Lake
• Partitioning
• Query optimization
• Large-scale datasets

4. ClickHouse

Used for:

• Fast audience preview
• Real-time analytics
• Interactive querying

Meeting talking point:

Databricks computes the audience, ClickHouse serves low-latency previews and analytics.

5. Kafka / Event Hubs

Role requires event-driven thinking.

Examples:

Customer actions generate events:

Plain Text

Purchase

Login

Page View

Cart Abandonment

These events update audience membership in near real time.

Good candidates should understand:

• Event streaming
• Consumer groups
• Message ordering
• Retry patterns

6. Redis

Likely used for:

• Audience preview caching
• Session storage
• Temporary counts

Not usually a primary screening area but useful.

AI Component

This separates the role from a traditional CDP role.

The JD specifically says:

Build AI-assisted segmentation and customer preview experiences

Examples:

User types:

Thanks & Regards,

Pavan Raikhelkar

LEAD TALENT ACQUISITION SPECIALIST

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