[Remote] Data Engineer AI

Note: The job is a remote job and is open to candidates in USA. Sedgwick is a leading claims management services company that values a caring culture and work-life balance. They are seeking a Senior Data Engineer AI to architect the data supply chain for advanced initiatives, focusing on building pipelines that support Data Science models and AI applications with high-fidelity data.ResponsibilitiesHybrid Data Pipeline Execution: Design and implement robust ETL/ELT pipelines to ingest data from legacy on-prem sources, AWS (S3/RDS), and Azure (Blob/SQL), centralizing it for consumption in Snowflake and AI servicesEngineering for Data Science: Build and maintain Feature Stores and specialized datasets optimized for machine learning, ensuring Data Scientists have immediate access to clean, versioned, and statistically valid dataEngineering for AI (RAG & LLMs): Develop the data pipelines required for Generative AI, including the automated extraction, chunking, and loading of unstructured data into vector stores across AWS and AzureSnowflake Power-User Execution: Act as the technical lead for our Snowflake data warehouse, implementing sophisticated data modeling, Snowpipe automation, and compute optimization to support high-concurrency AI workloadsLegacy "Back-Reach" Engineering: Execute non-invasive data extraction patterns to unlock mission-critical data from decades-old on-premise systems without disrupting core business operationsMulti-Cloud Orchestration: Manage complex, cross-platform data workflows using Airflow, Step Functions, or Azure Data Factory, ensuring the synchronization of data across our multi-cloud AI postureIT & Security Diplomacy: Partner directly with central IT, Database Administrators, and Security teams to solve connectivity hurdles (PrivateLink, IAM, firewalls) and secure "license to operate" for new data flowsData Quality for Model Integrity: Implement automated validation and observability layers to detect data drift and quality issues that could compromise the accuracy of production AI and Data Science modelsCost & Performance Management: Drive the efficiency of our data stack by optimizing storage and query performance in Snowflake, AWS, and Azure to manage the ROI of the Transformation OfficeDirect Stakeholder Collaboration: Work as a dedicated engineering partner to MLOps and Data Science teams to rapidly iterate on data requirements for evolving AI use casesSkillsBachelor's degree in Computer Science, Data Engineering, or a related field is required6+ years of hands-on data engineering experience, with a track record of building production-grade pipelines for Data Science and AI in multi-cloud environmentsExpert-level proficiency in Snowflake architecture, including data sharing, performance tuning, and the integration of Snowflake with external cloud AI servicesAdvanced, hands-on knowledge of AWS (S3, Glue, Lambda) and Azure (Data Factory, Synapse) data servicesMastery of Python, SQL, and PySparkDeep experience with data orchestration and containerization (Docker)Proven ability to interface with 'old world' tech (on-premise SQL, Mainframe extracts, flat files) and transform it for modern cloud consumptionA strong understanding of the specific data needs for Machine Learning (feature engineering) and Generative AI (vectorization and embedding pipelines)A 'get-it-done' attitude, capable of navigating enterprise bureaucracy and technical debt to ship code at the speed required by a Transformation OfficeA Master's degree is highly desirableCompany OverviewSedgwick is the world’s leading risk and claims administration partner, helping clients thrive by navigating the unexpected. It was founded in 1969, and is headquartered in Memphis, Tennessee, USA, with a workforce of 10001+ employees. Its website is http://www.sedgwick.com.Company H1B SponsorshipSedgwick has a track record of offering H1B sponsorships, with 2 in 2026, 11 in 2025, 10 in 2024, 4 in 2023, 9 in 2022, 14 in 2021, 10 in 2020. Please note that this does not guarantee sponsorship for this specific role.