Senior Data Engineer
Tasks
- Build MCP servers for data and workflows
- Build backend ingestion workflows
- Define and enforce data engineering standards and best practices
- Design build and operate Spark and PySpark workflows
- Design data platforms as products
- Develop end-to-end data pipelines
- Evaluate and adopt AI native tooling for data engineering
- Implement data monitoring observability and data availability
- Improve data architecture and data quality
- Integrate agentic workflows into data engineering lifecycle
- Lead end-to-end projects with stakeholders
- Optimize spark job performance
- Perform data integration and transformation
- Provide mentorship and technical guidance
- Write SQL and Python data transformations
Perks/Benefits
Skills/Tech-stack
API Gateway | AWS | AWS CloudWatch | AWS Lambda | AWS S3 | Amazon RDS | Apache Iceberg | Azure | DBT | Databricks | ETL | Fivetran | GCP | Google BigQuery | MS SQL | MS SQL Server | MySQL | Oracle | PostgreSQL | PySpark | Python | SQL | SQL Server | Snowflake | Spark
Education
Roles
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