Staff Data Engineer

Asurion helps people protect, connect, and enjoy the latest tech—making life a little easier. The Staff Data Engineer leads the design and delivery of scalable data solutions that power analytics and reporting, focusing on optimizing data infrastructure and ensuring data quality.

Responsibilities:

• Lead the design and development of scalable data pipelines and data products using Databricks, Spark, and Delta Lake
• Develop and optimize data transformations and ELT workflows using SQL and Python
• Design and implement data models and curated datasets to support analytics and reporting use cases
• Ensure data quality, consistency, and reliability through validation, monitoring, and testing practices
• Optimize pipeline performance, scalability, and cost efficiency within AWS environments
• Apply best practices for data partitioning, storage optimization, and query performance tuning
• Collaborate with product, analytics, and business teams to translate requirements into efficient data solutions
• Provide technical leadership and mentorship to engineers, including code reviews and design guidance
• Leverage AI tools for coding, validation, and documentation assistance to enhance productivity and code quality
• Troubleshoot and resolve data pipeline failures, latency issues, and data inconsistencies
• Continuously evaluate and improve data engineering workflows and tooling

Requirements:

• 8+ years of experience in data engineering or data pipeline development
• Strong hands-on experience with Databricks, Apache Spark, and Delta Lake
• Advanced proficiency in SQL and Python for building and optimizing data pipelines
• Experience developing robust ETL/ELT pipelines and handling complex data transformations
• Hands-on experience with AWS cloud services (e.g., S3, EMR, Lambda, Glue, Redshift, Kinesis)
• Strong understanding of data modeling and data warehousing concepts
• Experience working with large-scale datasets (TB+ or greater) in distributed environments
• Knowledge of data quality frameworks, validation techniques, and monitoring practices
• Familiarity with CI/CD pipelines and modern development workflows
• Experience using AI-assisted development tools for code generation, validation, or documentation
• Strong problem-solving skills with the ability to debug complex data issues
• Bachelor's degree in Computer Science, Engineering, or related field
• 8+ years of relevant experience in data engineering
• Proven experience leading technical initiatives or large-scale data pipeline projects
• Master's degree in a technical field
• Experience in large-scale, enterprise data environments
• Cloud certifications (AWS, Databricks)