Resilient Co - AWS Data Engineer
Requirements
• 6-9 years of hands-on experience in data engineering. • Hands-on experience with databases and related AWS services. • Hands-on experience with Snowflake, including Snowflake AI components (Cortex, Cortex Code, AI functions). • Strong fundamentals in data marts, data warehouses, data lake design, data modeling, and process flow. • Proven ability to produce initial architecture drafts independently for architectural review. • Profile scope: senior-level data engineering experience (not application/app development). • Engagement & Logistics • Engagement Length: 6 months or less • Holiday Calendar: Client holidays • Selection process • Meeting with Resilient Co. team. • Client technical interview • Vetting Process • Client interview • We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.
Responsibilities
• Design AWS data engineering components including Lambda, S3, and database integrations. • Build and operate data pipelines that integrate AWS systems with Snowflake. • Implement Snowflake features including Snowflake AI components (Cortex, Cortex Code, AI functions). • Own design and implementation of data marts, data warehouses, and data lakes. • Develop data models and define process flows for end-to-end data integration. • Produce initial architecture drafts independently for review by the architecture team. • Collaborate with architects and stakeholders to refine designs and ensure alignment with project goals. • Focus on senior-level delivery of data engineering solutions and handoff to operational teams.
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