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
Solid 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

📌 Technical Lead (Mumbai)
🏢 dentsu
📍 Mumbai