Kroll, a global leader in Risk and Financial Advisory services, is seeking a high‑performing Data Engineer to build and scale the data infrastructure that powers analytics, automation, and AI across the firm. The role offers real engineering responsibility, designing and implementing production‑grade data pipelines, working with cloud‑native tooling, and partnering with senior engineers and data scientists on systems that matter, while helping deliver clarity to 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 redesigns 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
Nice to have
- Understanding of cloud architecture principles: compute, storage, networks, security, cost
- Ability to develop REST APIs, Python SDKs or Libraries, Spark Jobs
- Proficiency with open‑source tools and frameworks such as 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
Benefits
- 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
- Supportive and collaborative work environment that empowers you to excel
Additional details
- Kroll operates at the intersection of data, technology, and complex decision‑making.
- Kroll’s mission is to bring truth into focus with the Kroll Lens, delivering clarity to clients across valuation, disputes, investigations, M&A, restructuring, and regulatory consulting.
- The company values diverse backgrounds and perspectives, encouraging a global outlook.
- Kroll is committed to equal opportunity and diversity, recruiting people based on merit.
- To be considered for the position, candidates must formally apply via careers.kroll.com.
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