Senior Data Engineer
Tasks
- Build MCP servers for data assets and workflows
- Build backend ingestion workflows
- Define data engineering standards and best practices
- Design data platforms as products
- Develop end-to-end data pipelines
- Implement data monitoring observability and data availability
- Improve data architecture and data quality
- Integrate agentic workflows into data engineering lifecycle
- Lead end-to-end data engineering projects
- Mentor team members and provide technical guidance
- Optimize Spark batch and streaming workflows
- Transform data for analytics and operational use
- Tune Spark performance and reliability
Perks/Benefits
Skills/Tech-stack
API Gateway | AWS Aurora | AWS CloudWatch | AWS Lambda | AWS RDS | AWS SNS | AWS SQS | AWS Secrets | AWS Secrets Manager | Amazon S3 | Amazon Web Services | Apache Iceberg | Apache Spark | Cloud Data | Cloud Data Warehouse | Cloud data lakehouse | Cloud platform | DBT | Data Lakehouse | Data Modeling | Data Monitoring | Data Quality | Data Transformation | Data Warehouse | Databricks | Datadog | ETL | Fivetran | Google BigQuery | Google Cloud | Google Cloud Platform | Microsoft Azure | Microsoft SQL | Microsoft SQL Server | MySQL | Observability | Oracle | PostgreSQL | PySpark | Python | REST APIs | SQL | SQL Server | Secrets Manager | Snowflake | Splunk | Web Services
Education
Roles
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