Data Engineer
SGD 81K-88K (estimate) Entry-level Full Time
Tasks
- Architect scalable data pipelines
- Automate model and data deployments
- Build dashboards and scorecards
- Build dimensional semantic models
- Build prompt libraries and evaluation harnesses
- Create data quality tests
- Define data lineage drift and freshness observability
- Develop DAX measures and row level security
- Engineer batch streaming data pipelines
- Evaluate GenAI models with metrics
- Implement CI CD for data and ai
- Implement RAG features
- Implement privacy by design PII masking and purpose limitation
- Maintain SOX audit trails and documentation runbooks and data dictionaries
- Perform prompt engineering and agent workflows
Perks/Benefits
- N/A
Skills/Tech-stack
Apache Hive | Apache Spark | Audit trails | Azure | Azure DevOps | Azure Machine Learning | CI/CD | DAX | Data Drift | Data Lineage | Data Modeling | Data Quality | Data Quality Testing | Data Warehousing | Data dictionaries | Data orchestration | Deep learning | Dimensional Modeling | ER Data Modeling | ETL | Evaluation Frameworks | Fabric | Freshness Monitoring | Git | GitHub Actions | Great Expectations | Hadoop | LLM | Lakehouse | Langchain | MLOps | MLflow | Machine Learning | MapReduce | Model Cards | Observability | PII masking | Power BI | Prompt engineering | PySpark | Quality testing | RAG | Row Level Security | Runbooks | SOX | SQL | Semantic Modeling | Tableau | Text Chunking | Tez | Vector Stores | Vectorization
Roles
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