Forward Deployed Engineer

About this role

About the role: - You'll serve as a technical specialist embedded with U.S.-based customers, owning data engineering and analytics implementations from start to finish - Your work bridges the gap between customer needs and Skypoint's platform capabilities, requiring you to design, build, and optimize data solutions that drive business impact - You'll take full technical responsibility for deliverables in a customer-facing environment where your decisions directly shape project success What you'll work on: - Designing and building ETL/ELT pipelines using cloud and Lakehouse platforms like Databricks, Azure, Snowflake, or Microsoft Fabric - Creating data models using star and snowflake schemas, semantic models, and dimensional modeling approaches - Developing Power BI solutions including DAX expressions, Power Query transformations, semantic layers, dashboards, and configurations within Power BI Service - Writing production Python and SQL code for data transformation, integration, validation, and quality assurance - Integrating data from multiple systems via APIs and building connectors for diverse data sources - Building executive dashboards and KPI reporting solutions tailored to customer strategy and decision-making - Troubleshooting data pipeline failures, performance issues, and integration problems independently What we're looking for: - Bachelor's degree in Computer Science, Data Science, Information Systems, Engineering, or a related discipline - 2–5 years of hands-on work in data engineering, analytics engineering, BI, implementation engineering, or comparable technical roles - Demonstrated expertise in Python and SQL for data work, with proven ability to write clean, maintainable code - 2+ years of direct, hands-on experience with Power BI, including DAX, Power Query, semantic models, and dashboard development - Solid grasp of data modeling principles and architectural patterns used in analytical systems - Experience consuming and building APIs to connect disparate data sources - Strong troubleshooting mindset with the ability to diagnose root causes and resolve complex technical issues - Clear communication skills and comfort building relationships with customers and external partners - Willingness to work during PST/PDT business hours to align with U.S. customer schedules Good to know: - Prior exposure to healthcare data, healthcare analytics systems, or other regulated data environments is valuable - Familiarity with Lakehouse architectures and modern cloud data platforms strengthens your fit - Experience with AWS, Azure, Databricks, Snowflake, or Microsoft Fabric is a plus - Background in a similar customer-facing role such as Forward Deployed Engineer, Solutions Engineer, Implementation Engineer, Analytics Engineer, or Data Engineer helps - Hands-on work with Generative AI, AI agents, LLMs, or AI-assisted development tools is increasingly relevant