Data Engineer

Job Title: Data Engineer Location: Remote Position Type: Contract About the Role This role is responsible for designing, developing, and optimizing end‑to‑end data infrastructure with a focus on marketing and engagement data. You will enable analytics, machine learning (ML), generative AI, and agentic AI initiatives by building scalable pipelines and ensuring data accuracy and availability. Success in this role looks like delivering robust, reliable data systems that empower advanced analytics and AI-driven product development. Key Responsibilities • Architect, implement, and maintain scalable data pipelines and transformations using Snowflake, dbt, and Keboola. • Develop and enforce data modeling standards and governance best practices. • Identify and resolve performance bottlenecks in ETL/ELT processes for improved speed and reliability. • Support ML/AI initiatives by preparing data for model training, feature pipelines, and integrating with AI frameworks. • Collaborate with data analysts, data scientists, and business stakeholders to translate requirements into actionable data solutions. • Maintain and improve processes by following standards while recommending enhancements. Required Qualifications • 4–7 years of hands‑on data engineering experience, ideally with cloud data warehouses (Snowflake preferred). • Proficiency in SQL and experience with dbt or similar transformation frameworks. • Experience working with Keboola. • Experience working with ML or LLM frameworks and systems. • Strong understanding of data modeling, ETL/ELT methodologies, and data governance. • Excellent organizational, interpersonal, analytical, and quantitative skills. • Ability to work independently in a fast-paced, deadline‑driven environment. • Advanced computer skills in Microsoft Office, Salesforce, and marketing automation tools. • Bachelor’s degree preferred. Preferred Qualifications • Experience in the healthcare industry, especially telemedicine, advocacy, or wellness. • Marketing and engagement data experience. • Background working with scalable, multi-source data environments.