Data Engineer 3
Tasks
- Build data integrations
- Conduct root cause analysis
- Design ETL/ELT pipelines
- Ensure data governance compliance
- Identify data quality issues
- Implement security and privacy standards
- Improve observability and alerting
- Maintain production data pipelines
- Monitor pipeline reliability
- Optimize pipeline performance
- Own data domain and platform components
- Participate in design and code reviews
- Perform incident resolution
- Support production operations
- Troubleshoot pipeline failures
- Write clean, reusable, documented code
Perks/Benefits
- Collaborative culture
- Continuous learning
- Flexible working arrangements
- Formal career path
- Remote hybrid work arrangements
- Work-life balance
Skills/Tech-stack
AWS Kinesis | Airflow | Amazon Redshift | Apache Kafka | Avro | Azure Data | Azure Data Services | Azure Event | Azure Event Hubs | Azure Synapse | BigQuery | DBT | Data Lakes | Data Services | Data Warehousing | Databricks | ELT | ETL | Event Hubs | JSON | Lakehouse | Parquet | PySpark | Python | SQL | Snowflake | Spark
Education
N/A
Roles
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