Senior Data Engineer, Product Analytics
Tasks
- Automate recurring reporting into data products
- Build and operate data pipelines
- Build ingestion to enterprise data lake
- Build self serve customer level reporting
- Create monitoring alerting and data quality testing
- Define data contracts and event definitions
- Design data models for analytics tables
- Document pipelines models and runbooks
- Implement event driven data collection
- Set up lineage and reliability practices
- Use AI tooling for pipeline and analysis work
Perks/Benefits
- Career development
- Flexibility and work-life balance
- Flexible vacation
- Headspace access
- Hybrid work model
- Mental health days
- Pro bono consulting opportunities
- Retirement savings
- Tuition reimbursement
- Two paid volunteer days off annually
- Work from anywhere up to 8 weeks per year
Skills/Tech-stack
AWS | Airflow | Alerting | Azure | Batch pipelines | Cloud Data | Cloud Data Platforms | Cloud platform | Code review | DBT | Data Contracts | Data Ingestion | Data Lake | Data Lineage | Data Modeling | Data Quality | Data orchestration | Data platforms | Enterprise Data | Enterprise Data Lake | Event Driven | Event design | Event-driven architecture | GDPR | GitHub Copilot | Google Cloud | Google Cloud Platform | Kafka | LLMs | Language Processing | Monitoring | Natural Language | Natural Language Processing | Python | SQL | Snowflake | Testing | Version control
Education
Bachelor of Engineering | Bachelor of Science | Bachelor of Science in Computer Science | Bachelor of Science in Data Science | Bachelor of Science in Engineering
Roles
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