Job Description:
About the Role
We are seeking a highly motivated and analytical Data Engineer to support the evolution of our customer analytics and AI-enabled data platform on Google Cloud Platform (GCP).
This role will focus on integrating Adobe Analytics clickstream data with enterprise systems such as Salesforce, POS, and customer data platforms while building scalable data transformation frameworks using Dataform and BigQuery. The role will play a critical part in enabling a semantic data layer that supports enterprise analytics, self-service insights, and next-generation AI initiatives powered by Gemini and BigQuery.
The ideal candidate combines strong GCP data engineering skills with a solid understanding of customer journey analytics, clickstream data, semantic modeling, and modern AI-ready data architectures.
Key Responsibilities
1. Customer Analytics Data Engineering
- Design and maintain scalable data pipelines supporting customer journey analytics.
- Integrate Adobe Analytics clickstream data with:
- Salesforce CRM
- POS and transaction systems
- Marketing platforms
- Build reliable ingestion, transformation, and serving layers for analytics and AI use cases.
- Ensure high-quality, governed, and trusted customer analytics datasets.
2. Dataform & Data Transformation Modernization
- Develop and maintain enterprise-grade ELT pipelines using Dataform and BigQuery.
- Support migration and modernization of existing workflows into Dataform-based architectures.
- Implement reusable transformation logic and standardized data engineering patterns.
- Optimize data processing performance, maintainability, and scalability.
- Establish best practices around testing, deployment, monitoring, and documentation.
3. Clickstream & Customer Journey Analytics Enablement
- Build data models supporting customer journey analysis and behavioral insights.
- Enable tracking and reporting across customer touchpoints and digital experiences.
- Support creation of unified customer views by integrating digital, CRM, and transaction data.
- Collaborate with analytics teams to improve data accessibility and business usability.
4. Semantic Layer Development
- Design and implement semantic data models that simplify enterprise data consumption.
- Define business-friendly metrics, dimensions, and reusable analytical entities.
- Support creation of governed semantic layers for reporting, analytics, and AI applications.
- Collaborate with business and analytics stakeholders to standardize KPIs and data definitions.
- Contribute to metadata management and enterprise data catalog initiatives.
5. AI & Gemini Data Enablement
- Build AI-ready datasets and data structures supporting enterprise GenAI initiatives.
- Support implementation of semantic data foundations for Gemini-powered analytics experiences.
- Enable integration with Gemini Enterprise and BigQuery connectors.
- Prepare and optimize datasets for conversational analytics and AI-assisted data interaction.
- Contribute to future-state AI and knowledge-driven data architectures.
- Support stakeholder discussions around customer analytics, semantic modeling, and AI readiness.
Technical Expertise Required
Area
Skills / Technologies
Customer Analytics
Adobe Analytics, Clickstream Analytics, Customer Journey Analytics
Cloud Data Engineering
GCP, BigQuery, Cloud Storage
Data Transformation
Dataform, SQL, Python
Data Modeling
Dimensional Modeling, Semantic Modeling
Data Integration
Salesforce Integration, POS Data Integration, Customer Data Platforms
Analytics
Advanced SQL, Reporting Datasets, KPI Frameworks
AI Enablement
Gemini Enterprise, BigQuery Connectors, AI-Ready Data Platforms
Metadata & Governance
Data Catalog, Metadata Management, Lineage
DevOps
Git, CI/CD, Data Pipeline Automation
Qualifications
- Bachelor's degree in Computer Science, Engineering, Information Systems, Analytics, or related field.
- 4 - 6 years of experience in cloud data engineering and analytics platform development.
- Strong hands-on experience with BigQuery, SQL, and Dataform.
- Experience working with clickstream and customer behavioral datasets.
- Exposure to Adobe Analytics or similar digital analytics platforms.
- Experience integrating enterprise systems such as Salesforce, CRM platforms, POS systems, or customer data platforms.
- Strong understanding of semantic modeling and analytical data structures.
- Familiarity with AI-enabled analytics ecosystems and modern data platforms.
- Strong stakeholder communication and problem-solving skills.
Preferred Experience
- Retail, eCommerce, Digital Commerce, or Customer Experience Analytics domain.
- Adobe Analytics implementation or support experience.
- Experience building customer 360 or customer journey analytics platforms.
- Experience developing semantic layers for self-service analytics.
- Exposure to Gemini Enterprise, GenAI, or conversational analytics initiatives.
- GCP Professional Data Engineer certification.
Location:
DGS India - Bengaluru - Manyata N1 BlockBrand:
MerkleTime Type:
Full timeContract Type:
PermanentSkills Required
- Bachelor's degree in Computer Science, Engineering, Information Systems, Analytics, or related field
- 4 - 6 years of experience in cloud data engineering and analytics platform development
- Strong hands-on experience with BigQuery
- Advanced SQL experience
- Hands-on experience with Dataform
- Experience with Python
- Experience working with clickstream and customer behavioral datasets
- Exposure to Adobe Analytics or similar digital analytics platforms
- Experience integrating enterprise systems such as Salesforce, CRM platforms, POS systems, or customer data platforms
- Strong understanding of semantic modeling and analytical data structures
- Familiarity with AI-enabled analytics ecosystems and GenAI data platforms
- Experience with metadata management, data catalog, and lineage
- Experience with Git, CI/CD, and data pipeline automation
- Strong stakeholder communication and problem-solving skills
- Retail, eCommerce, Digital Commerce, or Customer Experience Analytics domain experience
- Adobe Analytics implementation or support experience
- Experience building customer 360 or customer journey analytics platforms
- Experience developing semantic layers for self-service analytics
- Exposure to Gemini Enterprise, GenAI, or conversational analytics initiatives
- GCP Professional Data Engineer certification
dentsu Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about dentsu and has not been reviewed or approved by dentsu.
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Parental & Family Support — Paid parental leave at full pay and caregiver supports (including backup care) are emphasized as standout elements. Feedback suggests family-oriented benefits are a strong part of the package.
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Leave & Time Off Breadth — Flexible or unlimited PTO, extensive paid holidays, and a year-end office closure are established components. Feedback suggests time-off policies are generous and add meaningful flexibility.
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Retirement Support — A large, established 401(k) plan with employer matching is clearly documented. Feedback suggests retirement benefits feel competitive and straightforward.
dentsu Insights
What We Do
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