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Photon

CDP,Snowflake,SQL,Java, API,AWS - (6-9 Yrs) - BLR

Posted 3 Days Ago
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Remote
Hiring Remotely in India
Senior level
Remote
Hiring Remotely in India
Senior level
Implement and support Customer Data Platform solutions and Snowflake-based warehouse architectures. Build integrations across web, mobile, APIs, and marketing platforms; develop cloud-native AWS solutions (Kubernetes, Lambda), perform Snowflake data engineering, and enable audience activation and cross-channel marketing campaigns while collaborating with marketing and tech stakeholders.
The summary above was generated by AI

Location: BLR
Experience: 6-9 Years
Candidate should have experience in at least any one of the following but preferred Salesforce Data Cloud or any of one or more of  Adobe Real-Time CDP, Microsoft Dynamics 365 Customer Insights, Tealium AudienceStream, Treasure Data, mParticle, Hightouch, Census, or GrowthLoop. 
 
The Skills that are Key to this role
Technical
• Hands-on experience with one or more leading Customer Data Platforms (CDPs) such as Twilio Segment (preferred), Salesforce Data Cloud, Adobe Real-Time CDP, Microsoft Dynamics 365 Customer Insights, Tealium AudienceStream, Treasure Data, mParticle, Hightouch, Census, or GrowthLoop.
• Strong understanding of customer profile unification, identity resolution, audience management, data governance, and activation capabilities.
• Experience implementing and supporting CDP integrations across multiple data sources and destinations, including Web, Mobile, Events, APIs, Data Warehouses, Salesforce, Adobe, Marketing Automation platforms, Files, and custom enterprise applications.
• Experience working with modern warehouse-connected and zero-copy architectures leveraging Snowflake for customer data management, audience activation, and analytics.
• Experience leveraging CDP platforms for customer engagement and cross-channel activations across Email, Web, Mobile, and journey-based marketing campaigns.
• Strong experience developing cloud-native solutions on AWS, including Kubernetes, Lambda, event-driven architectures, messaging platforms, and API-based integrations, with programming experience in Java and Python.
• Experience with Snowflake data engineering, including data modeling, SQL development, data transformation, and performance optimization for large-scale data processing workloads
• Experience with database technologies such as DynamoDB and PostgreSQL.
• Experience building scalable, secure, and high-performing solutions with strong consideration for availability, reliability, maintainability, performance, and operational excellence.
Behavioral Skills
• Excellent communication and articulation skills, with the ability to build relationships and influence cross-functional teams
• Proven ability to collaborate with marketing, business, and technology stakeholders, as well as SaaS vendors, to simplify complex concepts and drive alignment on solutions and trade-offs
• Strong presence to demonstrate platform features, capabilities, and solutions to support key organizational initiatives
• Excellent analytical and problem-solving skills, with an innovative and forward-thinking approach to addressing challenges within complex data and SaaS environments
• Subject matter expertise in marketing segmentation, data, and end-to-end campaign setup and activation across Email, Web, Mobile, and Paid Media channels
• Highly adaptable and curious, with a passion for learning new technologies, frameworks, and industry best practices.
The Skills that are Good to Have for this role
• Strong front end skills using frameworks and technologies such as React, Vue, HTML/CSS, and JavaScript/TypeScript.
• Familiarity with AI/ML and Generative AI technologies, including LLMs, prompt engineering, RAG, and embeddings, and their application across CDPs, customer data, personalization, customer journeys, and marketing activation use cases.
• Exposure to predictive and AI-driven customer analytics, including propensity modeling, churn prediction, customer lifetime value (CLV) optimization, and audience intelligence.
• Knowledge of responsible AI practices, including governance, data privacy, explainability, and model performance monitoring.


 

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