CDP,Snowflake,SQL,Java, API, AWS - (6-9 Yrs) - CHN
Photon · India
IT Services and IT Consulting · 5,001-10,000 employees
About the role
The candidate will implement and support CDP integrations across various data sources and destinations while managing customer profile unification and identity resolution. They will also develop cloud-native solutions on AWS and perform data engineering tasks using Snowflake to support marketing campaigns and analytics.
What they look for
Requirements
The role requires 6-9 years of experience with at least one leading Customer Data Platform and strong proficiency in SQL, Java, and Python. Candidates must have a solid understanding of cloud-native architectures, data modeling, and experience working with modern data warehouses like Snowflake.
Full description
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Location: CHN 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.
