Data Engineer
Tasks
- Build and maintain ETL/ELT pipelines
- Build real-time streaming pipelines
- Collaborate with analysts data scientists and BI teams
- Create curated datasets for analytics and machine learning
- Deploy services with Docker and Kubernetes
- Design and optimize cloud data warehouses
- Implement CI/CD workflows
- Implement data quality validation and anomaly detection
- Ingest data from APIs SaaS and databases
- Maintain documentation for pipelines schemas and workflows
- Manage cloud infrastructure with Infrastructure as Code
- Model star schemas and analytics ready data models
- Monitor pipeline health and failed jobs
- Optimize SQL query performance and partitioning
- Orchestrate workflows and automate retries alerting
- Set up logging and lineage tracking
Perks/Benefits
Skills/Tech-stack
AWS CloudFormation | AWS Glue | Amazon Kinesis | Amazon Redshift | Apache Airflow | Azure Data | Azure Data Factory | BigQuery | Cloud Pub/Sub | Clustering | DBT | Dagster | Data Factory | Data Governance | Data Lineage | Data Modeling | Data Quality | Data Warehousing | Docker | ELT | ETL | GCP Dataflow | GDPR | GitHub Actions | GitLab CI | Google Cloud | Google Cloud Pub/Sub | Great Expectations | HIPAA | Jenkins | Kafka | Kubernetes | Luigi | Partitioning | Prefect | Pub/Sub | Python | SQL | Scala | Snowflake | Streaming Analytics | Terraform
Education
N/A
Roles
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