Senior Data Engineer, Data Science Infrastructure

Liberty Mutual Insurance is seeking experienced data engineers to join their Data Solutions job family. The role involves designing and developing data solutions for pricing programs, supporting analytics, and collaborating with cross-functional teams to ensure data quality and efficiency.

Responsibilities:

• Lead the design, development, and maintenance of scalable and efficient data pipelines and ETL/ELT processes to support analytics and pricing models
• Architect and implement high performance data integration solutions using modern tools and cloud services (AWS preferred) with attention to latency, throughput and cost
• Implement and maintain automated data quality and testing frameworks (unit, integration, regression, anomaly detection) to ensure data correctness and trust for downstream analytics
• Collaborate with cross functional teams, including data scientists, product analysts, software engineers, to gather requirements, design solutions, and provide technical guidance for production launches
• Optimize and tune data infrastructure for performance, scalability, reliability and cost-efficiency (query tuning, partitioning, resource configuration, storage formats such as Parquet/Delta)
• Mentor and guide junior data engineers, promoting engineering best practices, code review and thoughtful design
• Stay up-to-date with advancements in data engineering, evaluate new tools and recommend adoption where appropriate
• Identify opportunities to apply Gen AI for data discovery, lineage summarization, automated documentation, query generation and developer productivity (prompt engineering and code generation)
• Incorporate Gen AI capabilities into data workflows and developer tooling and help operationalize safe, cost-effective Gen AI integrations

Requirements:

• Strong technical aptitude with data extraction and data engineering platforms (Python, Spark/PySpark, SQL, cloud computing: AWS and Snowflake)
• 5+ years of experience building production data pipelines and platforms, with both batch and streaming experience
• Hands-on experience with data quality testing frameworks and practices, and experience implementing automated data tests and validation
• Practical experience collaborating in Agile teams and applying Agile best practices (sprint planning, refinement, retrospective)
• Excellent communication skills and the ability to work with technical and non-technical stakeholders
• Strong written and oral communication skills required
• Bachelor's Degree in Computer Science, Computer Engineering, or related discipline preferred
• 3-5 years experience in coding for data management, data warehousing, or other data environments, including, but not limited to, working in Python, SQL, ETL, Spark, Snowflake
• Familiarity with ML pipelines and supporting feature stores or feature engineering workflows (Databricks)
• Prior mentoring or technical leadership experience
• Master's in same or related disciplines strongly preferred