Principal Data Engineer

Role Overview

• Design, develop, and optimize ETL/ELT pipelines for both structured and unstructured data
• Mentor junior team members and engage in communities of practice to deliver high-quality data and AI solutions while promoting best practices, standards, and adoption of reusable patterns
• Partner with architects and stakeholders to influence and implement the vision of the AI and data pipelines while safeguarding the integrity and scalability of the environment
• Ingest and process large-scale datasets (e.g. telematics data) into the Enterprise Data Lake and downstream systems
• Curate and publish Data Products to support analytics, visualization, and machine learning use cases
• Collaborate with data analysts, data scientists, and BI teams to build data models and pipelines for research, reporting, and advanced analytics
• Apply best practices for data modeling, governance, and security across all solutions
• Partner with cross-functional teams to ensure alignment and delivery of high-value outcomes
• Monitor and fine-tune data pipelines for performance, scalability, and reliability
• Automate auditing, balance, reconciliation, and data quality checks to maintain high data integrity
• Develop self-healing pipelines with robust re-startability mechanisms for resilience
• Schedule and orchestrate complex, dependent workflows using tools like MWAA, Autosys, or Control-M
• Leverage CI/CD pipelines to enable automated integration, testing, and deployment processes
• Lead Proof of Concepts (POCs) and technology evaluations to drive innovation
• Develop AI-driven systems to improve data capabilities, ensuring compliance with industry best practices
• Implement efficient Retrieval-Augmented Generation (RAG) architectures and integrate with enterprise data infrastructure
• Implement data observability practices to proactively monitor data health, lineage, and quality across pipelines, ensuring transparency and trust in data assets

Requirements

• Bachelor’s or master’s degree in computer science or a related discipline
• 5+ years of experience in data analysis, transformation, and development, with ideally 2+ years in the insurance industry
• Experience and demostrated expertise in event-level and trip-level telematics driving data data
• 3+ years of experience developing and deploying large-scale data and analytics applications on cloud platforms such as AWS and Snowflake
• Strong proficiency in SQL, Python, and ETL tools such as Informatica IDMC for data integration and transformation (3+ years)
• Experience designing and optimizing data models for Data Warehouses, Data Marts, and Data Fabric, including dimensional modeling, semantic layers, metadata management, and integration for scalable, governed, and high-performance analytics (3+ years)
• 3+ years of hands-on experience in processing large-scale structured and unstructured data in both batch and near-real-time environments, leveraging distributed computing frameworks and streaming technologies for high-performance data pipelines.
• Strong technical knowledge (AI solution leveraging Cloud and modern solutions)
• 3+ years of experience in Agile methodologies, including Scrum and Kanban frameworks
• 2+ years of experience in leveraging DevOps pipelines for automated testing and deployment, ensuring continuous integration and delivery of data solutions
• Proficient in data visualization tools such as Tableau and Power BI, with expertise in creating interactive dashboards, reports, and visual analytics to support data-driven decision-making
• Ability to analyze source systems, provide business solutions, and translate these solutions into actionable steps
• Candidate must be authorized to work in the US without company sponsorship

Tech Stack

• AWS
• Cloud
• ETL
• Informatica
• Python
• SQL
• Tableau

Benefits

• Other rewards may include short-term or annual bonuses
• long-term incentives
• and on-the-spot recognition