Senior Data Engineer
Tasks
- Build data pipelines
- Build reporting datasets
- Develop ETL processes
- Establish data modeling best practices
- Improve data observability
- Improve data quality
- Improve data reliability
- Integrate data sources for analytics
- Integrate data tracking for new functionality
- Lead data architecture design
- Lead streaming data integration
- Mentor data engineers
- Mitigate data platform issues
- Model data and metadata for BI
- Optimize business query performance
- Prioritize engineering work
- Promote code review best practices
- Promote testing best practices
- Provide technical guidance for data access
- Scale data platform
Perks/Benefits
- Coursera access
- Employee referral rewards
- Flexible time off
- Paid public holidays
- Paid sick leave
- Parental leave
- Professional development
Skills/Tech-stack
AWS | Airflow | Amazon Redshift | Apache Spark | CI/CD | CloudFormation | Dagster | Data Modeling | Data Quality | Data Reliability | Data Warehousing | Document Databases | ETL | Google BigQuery | Infrastructure as Code | Kafka | Key-Value Databases | Key-value | Metadata | NoSQL | Observability | Prefect | PySpark | Python | Relational databases | SQL | Snowflake | Terraform | Third Party | Third-party APIs | “as-code”
Education
Bachelor of Engineering | Bachelor of Science | Master of Science | PhD
Roles
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