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Data Engineer
Dentsuaegis · DGS India - Mumbai - Goregaon Prism Tower · Pune
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Job Description: Job Description – Data Engineer (AWS) 1. Basic Information
- Job Title: Data Engineer (AWS)
- Experience: 3 to 7 Years 2. Role Overview We are looking for a hands-on Data Engineer – AWS with 3 to 7 years of experience in developing, building, and maintaining scalable, secure, and high-performance data platforms on AWS . This is an individual contributor role focused on data pipeline development, cloud data engineering, and analytics enablement . The candidate should have strong hands-on expertise in AWS data services, SQL, and Python , along with experience in building reliable batch and streaming pipelines in a global delivery environment. 3. Must-Have Skills Cloud & Data Engineering (AWS)
- Strong hands-on experience with:
- Amazon S3
- AWS Glue
- Amazon Athena
- Amazon Redshift
- Amazon EMR
- Experience designing cloud-native data lakes and data warehouse architectures
- Solid understanding of batch data processing and basic exposure to streaming concepts SQL & Python (Mandatory)
- Strong SQL skills (mandatory):
- Complex queries, joins, aggregations, and transformations
- Experience working with large datasets in Redshift/Athena
- Strong Python skills (mandatory):
- Python for data engineering and ETL use cases
- Experience with PySpark / Spark (preferred)
- Good understanding of:
- Data modeling
- Transformations
- Performance tuning Data Processing & Engineering
- Hands-on experience with Spark / PySpark
- Experience handling:
- Structured and semi-structured data
- Knowledge of:
- Schema evolution
- Data quality checks
- Validation logic DevOps & Platform Basics
- Working knowledge of Infrastructure as Code (Terraform / CloudFormation)
- Basic experience with CI/CD pipelines for data workloads
- Understanding of logging and monitoring using AWS CloudWatch Collaboration
- Ability to work with architects, DevOps, QA, and business stakeholders
- Good communication skills to clearly explain technical concepts 4. Good-to-Have Skills
- Experience with streaming technologies (Amazon Kinesis / Kafka)
- Familiarity with Lakehouse and modern data platform architectures
- Integration experience with BI / reporting tools
- Basic knowledge of:
- Data governance
- Data quality
- Metadata management
- Awareness of AWS cost optimization (FinOps basics)
- Experience in Agile delivery models with global teams
- Exposure to AI / ML use cases 5. Key Responsibilities Data Engineering & Development
- Design and build scalable ETL/ELT pipelines on AWS
- Develop:
- SQL-based data transformations
- Python-based data pipelines
- Implement data ingestion pipelines using S3, Glue, EMR
- Build data models optimized for analytics, performance, and cost efficiency Platform & Operations
- Support deployment and execution of data pipelines
- Monitor:
- Pipeline performance
- Reliability
- Data quality
- Troubleshoot data issues and perform root cause analysis
- Apply best practices for:
- Security
- Reliability
- Scalability Collaboration & Delivery
- Work with architects and product teams to understand requirements
- Translate business needs into AWS data engineering solutions
- Contribute to:
- Documentation
- Code reviews
- Engineering best practices 6. Education Qualification
- Bachelor’s or Master’s degree (or equivalent) in:
- Computer Science
- Information Technology
- Data Engineering
- or related field 7. Certifications (Preferred)
- AWS Certified:
- Solutions Architect
- DevOps (Professional)
- Snowflake Core Certification (optional) Location: DGS India
- Mumbai
- Goregaon Prism Tower Brand: Merkle Time Type: Full time Contract Type: Permanent