Data Engineer
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Job Description
Data Engineer building secure analytical pipelines, semantic models, and data governance for CodeRoad’s US technology clients. Supporting AI querying, RAG architectures, and Agentic AI workflows.
Responsibilities:
- Design and implement modern semantic models, including facts, dimensions, and metrics stores using tools like dbt, for AI querying and analytical consumption
- Build curated, high-performance analytical views and production ELT/ETL pipelines
- Optimize database query performance, indexing, and schema definitions through systematic query log analysis
- Implement data governance frameworks including RBAC, RLS, and dynamic data masking for PII protection
- Establish data quality, pipeline monitoring, and anonymization standards across analytical layers
- Collaborate with cross-functional AI engineering teams to align data structures with RAG architectures and Agentic AI workflows
Requirements:
- 3+ years of dedicated Data Engineering experience
- Strong, production-grade command of SQL across Azure SQL, PostgreSQL, or modern cloud data warehouses
- Proven production track record building and maintaining resilient ETL/ELT data pipelines and optimized analytical structures
- Demonstrated experience in database security, including RBAC, RLS, and dynamic data masking for PII protection
- Hands-on expertise tuning complex queries for low-latency analytical workloads
- Strong foundation in dimensional modeling (Kimball) and semantic layers (dbt)
- Strong ownership mindset and proactive problem-solving abilities within collaborative nearshore team environments
- Advanced English fluency, written and spoken, strictly required
- Bonus exposure to orchestration platforms (Airflow/Prefect), vector databases, or RAG frameworks
Benefits:
- USA Contractor / 100% Remote
- Competitive Pay (USD)
- Holidays Off & Paid Time Off
- Health insurance assistance program
- Opportunity to work with high-growth US-based companies and cutting-edge tech stacks
- Agentic AI tools and training
- Coursera Enterprise
- Studio practice labs
- High-touch onboarding
- Transparent leadership communication
- Community recognition
- Psychological safety
- Continuous multi-project pipeline
- L1-L7 Career Framework
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