Senior Data Engineer
Tasks
- Build Spark and PySpark batch workflows
- Build Spark and PySpark streaming workflows
- Build and maintain MCP servers
- Build backend ingestion workflows
- Collaborate with platform teams on agent workflows
- Define data engineering standards
- Design data platforms
- Develop data pipelines
- Evaluate AI native data engineering tooling
- Implement data monitoring and observability
- Improve data architecture and data quality
- Lead end-to-end projects with stakeholders
- Mentor junior team members
- Optimize spark job performance
- Perform data integration and transformation
- Write Python transformations
- Write SQL transformations
Perks/Benefits
- Flexible working model
- Health insurance
- Parental leave plans
- Professional development stipend
- Remote work
Skills/Tech-stack
API Gateway | AWS Lambda | AWS RDS | Amazon CloudWatch | Amazon S3 | Amazon SNS | Amazon SQS | Amazon Web Services | Apache Iceberg | Apache Spark | Aurora | DBT | Data Modeling | Data Quality | Databricks | ETL | Fivetran | Google BigQuery | Logging | Microsoft SQL | Microsoft SQL Server | Monitoring | MySQL | Observability | Oracle | PostgreSQL | PySpark | Python | RDBMS | REST APIs | SQL | SQL Server | Secrets Manager | Snowflake | Web Services
Education
Bachelor of Engineering | Bachelor of Science | Master of Science
Roles
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