Senior Data Engineer for AI Initiatives

Join Sedgwick and become part of a meaningful mission where our 33,000 colleagues support individuals facing the unexpected every day. Grow your career in a caring culture that values work-life balance and offers limitless opportunities for achievement.

Recognized by Newsweek as one of America's Greatest Workplaces, Sedgwick is proud to be certified as a Great Place to Work® and acknowledged by Fortune as one of the Best Workplaces in Financial Services & Insurance.

Your Role

As a Senior Data Engineer in the Transformation Office, you will architect and build the data supply chain that powers our innovative projects. You will ensure that Data Science models and AI applications thrive on high-fidelity data by designing the pipelines that connect our legacy on-prem systems (Mainframes, SQL Server, DB2) to our modern Snowflake environment and cloud AI stacks through AWS and Azure. Your role as a builder is integral in engineering data to meet model training and operational needs.

Key Responsibilities • Develop and implement robust ETL/ELT pipelines that efficiently ingest data from legacy on-prem sources, AWS (S3/RDS), and Azure (Blob/SQL) into Snowflake and AI platforms. • Create and manage Feature Stores and datasets optimized for machine learning, ensuring Data Scientists have access to clean and versioned data. • Design data pipelines for Generative AI, automating the extraction and processing of unstructured data for use in vector storage on AWS and Azure. • Serve as the technical lead for our Snowflake data warehouse, focusing on advanced data modeling, Snowpipe automation, and compute optimization for AI workloads. • Employ non-invasive extraction techniques to access critical data from legacy systems without disrupting ongoing operations. • Oversee multi-cloud data workflows using orchestration tools like Airflow, Step Functions, or Azure Data Factory to synchronize data effectively. • Collaborate with IT, Database Administrators, and Security teams to address connectivity and security challenges for new data initiatives. • Implement automated validation and observability to monitor data quality and integrity, ensuring the reliability of AI and Data Science models. • Enhance cost and performance efficiency by optimizing storage and query activities in Snowflake, AWS, and Azure. • Work closely with MLOps and Data Science teams to rapidly address evolving data requirements for AI applications.

Qualifications • Bachelor's degree in Computer Science, Data Engineering, or a related field is required; a Master's degree is preferred. • 6+ years of hands-on data engineering experience, with a strong record of building production-grade pipelines for Data Science and AI in multi-cloud environments. • Expertise in Snowflake architecture, performance tuning, data sharing, and integration with cloud AI services. • Proficient in advanced AWS (S3, Glue, Lambda) and Azure (Data Factory, Synapse) data services. • Strong command of Python, SQL, and PySpark with experience in data orchestration and containerization (Docker). • Ability to work with legacy technologies (on-premise SQL, Mainframe extracts) and transform them for modern cloud applications. • In-depth understanding of the data needs for machine learning and Generative AI. • Proactive mindset with a determination to navigate organizational challenges and deliver results.

#LI-TS1 #remote

Sedgwick is committed to fostering a diverse, equitable, and inclusive workplace. If this role excites you but your experience doesn't match every qualification, we encourage you to apply anyway!

As the world's leading risk and claims administration partner, Sedgwick helps clients navigate the unexpected. With advanced AI-enabled technology and a dedicated team of over 33,000 colleagues serving 10,000 clients in 80 countries, we offer unmatched insights and solutions for today's complex risk landscape. To learn more, visit sedgwick.com.