Senior Data Engineer (Hybrid)
Tasks
- Build and maintain data stack from ingestion to consumption
- Build data pipelines and infrastructure
- Collaborate with DevOps to deploy and maintain data solutions
- Define standardized metrics and semantic alignment
- Develop data warehouse and data modeling
- Enable customer-facing dashboards and self-serve analytics
- Enable internal reporting and analytics use cases
- Establish data quality and data security framework
- Implement next best action analytics
- Lead data engineering architecture and technical vision
Perks/Benefits
- Catered lunch
- Employee resource groups
- Flexible time off
- Hybrid work schedule
- Meal reimbursement
- Paid Holidays
- Relocation bonus
- Wellbeing days
- Work from home stipend
Skills/Tech-stack
APIs | AWS | Airbyte | Airflow | DAG | DBT | Data Modeling | Dimensional Modeling | Docker | ELT | Enterprise dimensional modeling | Fivetran | JSON | Kafka | Looker | ORC | Parquet | Power BI | Prefect | Python | RDS | Redshift | S3 | SQL | Schema on read | Semantic Modeling | Semantic layer | Snowflake | Tableau | Terraform | Unix/Linux
Education
Roles
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