Data Engineer I

We are seeking a high-performing Data Engineer to help build and scale the data infrastructure that powers analytics, automation, and AI across the firm.

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
• Broader work or accountabilities may be assigned as needed
• Continuously improve engineering processes, balancing speed, quality, and business impact

Requirements

• Bachelor’s or master’s degree in computer science, engineering, or a related field
• 3+ 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, and SQL
• Excellent communication skills
• Ability to work with an international team

Desired Skills

• Cloud architecture principles: compute, storage, networks, security, cost
• Ability to develop REST APIs, Python SDKs or Libraries, Spark Jobs
• 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

Kroll is committed to equal opportunity and diversity, and recruits people based on merit.