Job Description:
Must-Have Skills
Cloud & Data Engineering (AWS)
Strong hands-on experience with:
Amazon S3, AWS Glue, Athena, Redshift
Experience designing cloud-native data lakes and data warehouses
Deep understanding of batch and streaming data pipelines
Experience building scalable and fault-tolerant data workflows
SQL & Python (Mandatory)
Strong expertise in SQL, including:
Complex transformations and aggregations
Performance tuning and analytics queries
Experience working with large-scale datasets in Redshift/Athena
Strong Python programming skills for data engineering use cases
PySpark / Spark Processing
Hands-on experience with Spark / PySpark
Build reusable ETL components and utilities
Strong understanding of:
Data modeling
Transformations
Performance optimization
Data Processing & Engineering
Experience with distributed processing frameworks (Spark/PySpark)
Handling structured, semi-structured, and unstructured data
Expertise in:
Schema design
Partitioning
Query optimization
DevOps & Platform Engineering
Experience with Infrastructure as Code (Terraform / CloudFormation)
Hands-on experience in building CI/CD pipelines for data platforms
Exposure to containerization (Docker, ECS, EKS)
Collaboration & Ownership
Strong ownership mindset for:
Solution quality
Performance
Production stability
Excellent communication and stakeholder collaboration skills
Good-to-Have Skills
Experience with streaming technologies (Kinesis, Kafka, MSK)
Exposure to Lakehouse architectures and modern data platforms
Integration with BI and analytics tools
Knowledge of:
Data governance
Data quality frameworks
Metadata management
Familiarity with FinOps (cost optimization on AWS)
Exposure to Marketing/Customer Data Platforms (CDP / MarTech)
Experience working in Agile delivery models with global teams
Education Qualification
Bachelor’s or master’s degree in:
Computer Science
Information Systems
Data Engineering
or related field
Certifications
Preferred:
AWS Certified Data Analytics
AWS Solutions Architect
(Any two preferred)
Plus:
Databricks
Snowflake or other cloud data platform certifications
Location:
DGS India - Mumbai - Goregaon Prism TowerBrand:
MerkleTime Type:
Full timeContract Type:
PermanentSkills Required
- 6 to 10 years of experience in data engineering
- Bachelor's or Master's degree in Computer Science, Information Systems, Data Engineering or related
- Strong hands-on experience with Amazon S3, AWS Glue, Athena, Redshift
- Experience designing cloud-native data lakes and data warehouses
- Deep understanding of batch and streaming data pipelines
- Strong SQL expertise including complex transformations, aggregations, and performance tuning
- Strong Python programming skills for data engineering use cases
- Hands-on experience with Spark / PySpark and distributed processing frameworks
- Experience with schema design, partitioning, and query optimization for large-scale datasets
- Experience with Infrastructure as Code (Terraform or CloudFormation)
- Hands-on experience building CI/CD pipelines for data platforms
- Exposure to containerization technologies (Docker, ECS, EKS)
- Strong ownership, communication, and stakeholder collaboration skills
- Experience with streaming technologies (Kinesis, Kafka, MSK)
- Exposure to Lakehouse architectures, BI tool integration, data governance, metadata management
- Familiarity with FinOps (AWS cost optimization), CDP/MarTech, Agile delivery models
- Preferred certifications: AWS Certified Data Analytics, AWS Solutions Architect, Databricks, Snowflake
What We Do
Dentsu Creative is a global creative agency network designed to unlock exponential growth for clients. We use Transformative Creativity as a differentiating, driving force to bring our capabilities together to positively impact people, business and society. Established in 2022, Dentsu Creative is integrated with dentsu’s Media and CXM businesses in over 145 countries and regions, to offer Integrated Growth Solutions.







