Enterprise Data Engineer | Cloud (AWS, Azure) | Big Data (Spark, Hadoop) | ETL & Data Pipelines | SQL & NoSQL
Pune - Hinjewadi (Ascendas), India
INR 3000K-4000K (estimate) Senior-level Full Time
Tasks
- Automate deployment and infrastructure changes
- Collaborate with stakeholders to gather requirements
- Design data pipelines
- Develop ETL workflows
- Implement data governance and validation
- Maintain data architecture documentation
- Maintain enterprise data integrations
- Monitor pipeline performance and reliability
- Optimize data quality and scalability
- Troubleshoot pipeline issues and perform root cause analysis
Perks/Benefits
Skills/Tech-stack
AWS | AWS Glue | Access Control | Amazon EMR | Amazon S3 | Apache Airflow | Apache Spark | Azure | Azure Data | Azure Data Factory | CI/CD | CloudFormation | Data Factory | Data masking | DataOps | Docker | DynamoDB | Encryption | Flink | GCP Dataflow | Git | Hadoop | Java | Jenkins | Kafka | Kinesis | Kubernetes | Luigi | MongoDB | Node.js | Python | SQL | Terraform
Education
Bachelor of Engineering | Bachelor of Science | Master of Science
Roles
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