Lead Data Engineer (Hybrid)
Tasks
- Build and maintain data warehouses and transformations
- Build data pipelines and platform
- Build reporting transparency tools
- Define data architecture and technical vision
- Define data quality and data security frameworks
- Deploy and maintain data solutions on cloud
- Develop self serve analytics and customer dashboards
- Enable financial reporting and product analytics
- Implement data ingestion and orchestration
- Standardize company metrics and semantic layers
Perks/Benefits
- Employee resource groups
- Flexible time off
- Holiday bonus
- Hybrid work schedule
- Meal reimbursement
- Medical, dental & vision coverage
- Paid Holidays
- Relocation bonus
- Work from home stipend
Skills/Tech-stack
API Development | AWS | AWS Kinesis | Airbyte | Amazon RDS | Amazon Redshift | Amazon S3 | Apache Airflow | Apache Kafka | Containerization | Curl | DAG | DBT | Data Architecture | Data Engineering | Data Modeling | Data Pipelines | Dimensional Modeling | Docker | ELT | Enterprise Data | Enterprise Data Architecture | Fivetran | JSON | Kubernetes | Looker | ORC | Parquet | Performance optimization | Prefect | Python | Real Time | Real-time ETL | SQL | Schema on read | Semantic layer | Sisense | Snowflake | Tableau | Terraform | Unix/Linux
Education
Roles
Data Engineer | Engineer | Lead | Lead Data | Lead Data Engineer
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