Data Engineer

This is a fully remote position, open to applicants in United States.

📋 Description

• Create and execute contemporary semantic models, which encompass facts, dimensions, and metrics stores utilizing tools like dbt for AI querying and analytical usage.

• Develop curated, high-performance analytical views and production ELT/ETL pipelines.

• Enhance database query performance, indexing, and schema definitions through thorough analysis of query logs.

• Implement data governance frameworks that include RBAC, RLS, and dynamic data masking to safeguard PII.

• Set standards for data quality, pipeline monitoring, and anonymization across analytical layers.

• Work in collaboration with cross-functional AI engineering teams to ensure data structures are aligned with RAG architectures and Agentic AI workflows.

⛳️ Requirements

• A minimum of 3 years of focused Data Engineering experience.

• Proficient, production-grade knowledge of SQL across Azure SQL, PostgreSQL, or contemporary cloud data warehouses.

• Proven experience in building and maintaining robust ETL/ELT data pipelines and optimized analytical frameworks.

• Demonstrated expertise in database security, including RBAC, RLS, and dynamic data masking for PII protection.

• Practical experience in fine-tuning complex queries for low-latency analytical workloads.

• Solid foundation in dimensional modeling (Kimball) and semantic layers (dbt).

• Strong ownership mentality and proactive problem-solving skills in collaborative nearshore team settings.

• Advanced fluency in English, both written and spoken, is strictly required.

• Bonus: Familiarity with 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 engage with high-growth US-based companies and state-of-the-art tech stacks.

• Access to Agentic AI tools and training.

• Coursera Enterprise.

• Studio practice labs.

• High-touch onboarding experience.

• Transparent communication from leadership.

• Community recognition.

• Psychological safety in the workplace.

• Continuous multi-project pipeline.

• L1-L7 Career Framework.