Role: AWS Data Engineer
Experience: 7–10 Years
Relevant Experience: Minimum 6 Years in Data Engineering
Location: Pune (Work from office 5 days)
Key Skills Required
- Python
- PySpark
- Data Modeling
- Databricks
- AWS Services – S3, Lambda, ECS
- ETL/Data Pipeline Development
- Cloud Data Engineering
Job Responsibilities
- Design, develop, and maintain scalable data pipelines using Python and PySpark.
- Build and optimize ETL/ELT workflows for large-scale data processing.
- Work extensively on Databricks for data transformation and analytics workloads.
- Implement robust data models to support business reporting and analytics needs.
- Utilize AWS services such as S3, Lambda, and ECS for cloud-based data solutions.
- Collaborate with cross-functional teams including Data Analysts, Architects, and Business stakeholders.
- Ensure data quality, performance optimization, and reliability of data platforms.
- Troubleshoot production issues and support deployment activities.
Required Qualifications
- 7–10 years of overall IT experience with at least 5 years in Data Engineering.
- Strong hands-on experience in Python and PySpark.
- Good understanding of Data Modeling concepts.
- Experience working with Databricks in enterprise environments.
- Hands-on experience with AWS cloud services, especially S3, Lambda, and ECS.
- Experience in building scalable and high-performance data solutions.
- Strong problem-solving and communication skills.
Preferred Skills
- Experience with CI/CD pipelines and DevOps practices.
- Knowledge of Agile/Scrum methodologies.
- Exposure to big data technologies and cloud-native architectures.
Notice Period Preference
- Immediate to 30 Days Preferred.
Skills: aws,databricks,s3,data engineering,python,data modeling,aws lambda,pyspark
