Senior Data Engineer

Kroll is a global leader in Risk and Financial Advisory services, operating at the intersection of data, technology, and complex decision-making. We are seeking a high-performing Senior Data Engineer to help build and scale the data infrastructure that powers analytics, automation, and AI across the firm. This role is for candidates who want real engineering responsibility, not shadow work. You will design and implement production-grade data pipelines, work with cloud-native tooling, and partner with senior engineers and data scientists on systems that matter.

At Kroll, your work will help deliver clarity to our clients’ most complex governance, risk, and transparency challenges.

RESPONSIBILITIES:

• Design and build scalable organizational data infrastructure and Medallion architecture within a Lakehouse environment
• Develop robust, fault-tolerant ETL/ELT applications for seamless data ingestion, transformation, and distribution to enable analytics, reporting, and AI workloads
• Work with different stakeholders and teams to assist with data related technical solutions and support their data infrastructure needs
• Explore and experiment with new use cases, frameworks, and tools to enhance AI capabilities, ensuring data integrity, quality, and reliability
• Identify and implement infrastructure re-designs to improve scalability, optimize data delivery, and automate manual workflows
• Choose the best tools/services/resources to build robust data pipelines
• Collaborate with cross-functional teams to understand data requirements, create robust data models, and deliver actionable insights
• Monitor, troubleshoot, and optimize jobs for performance, addressing data pipeline bottlenecks and ensuring cost efficiency
• Continuously improve engineering processes, balancing speed, quality, and business impact
• Coach, mentor, and provide technical guidance to junior engineers, fostering a culture of continuous learning and development
• Stay updated on emerging technologies and trends in data engineering, recommending and implementing innovative solutions

REQUIREMENTS:

• Bachelor’s or master’s degree in computer science, engineering, or a related field
• 5+ years of proven experience in data engineering, delivering business-critical software solutions for large enterprises with a consistent track record of success
• Experience writing ETL/ELT jobs
• Experience with Azure and Databricks Platform
• Experience with Python, SQL, and REST APIs
• Excellent communication and the ability to reason about trade-offs
• Ability to work with an international team

DESIRED SKILLS:

• Cloud architecture principles: compute, storage, networks, security, cost
• Proficiency in using open-source tools, frameworks like FastAPI, Pydantic, Polars, Pandas, Delta Lake, Docker, Kubernetes
• Knowledge of CI/CD, Git, or infrastructure-as-code concepts
• Strong project management skills, with the ability to prioritize tasks and manage multiple projects simultaneously in an Agile environment
• Understanding of how data engineering feeds into Business Intelligence and reporting tools (Power BI/Tableau)
• Strong problem-solving and analytical skills
• Strategic thinker and strong execution orientation
• Ability to work in cross-functional teams
• Attention to detail and data quality

WHY THIS ROLE?

• Work on real systems in production, not toy problems
• Learn how enterprise-scale data platforms are designed, operated, and evolved
• Direct mentorship from senior engineers and data leaders
• Meaningful impact on firm-wide analytics and automation initiatives
• A high-bar engineering environment focused on quality, scale, and long-term thinking

and recruits people based on merit.