Submitting more applications increases your chances of landing a job.

Here’s how busy the average job seeker was last month:

Opportunities viewed

Applications submitted

Keep exploring and applying to maximize your chances!

Looking for employers with a proven track record of hiring women?

Click here to explore opportunities now!
We Value Your Feedback

You are invited to participate in a survey designed to help researchers understand how best to match workers to the types of jobs they are searching for

Would You Be Likely to Participate?

If selected, we will contact you via email with further instructions and details about your participation.

You will receive a $7 payout for answering the survey.


User unblocked successfully
https://bayt.page.link/k9cSnhY8pbVXLuwf6
Back to the job results
Other Business Support Services
Create a job alert for similar positions
Job alert turned off. You won’t receive updates for this search anymore.

Job description

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 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. Apply now to join One team, One Kroll.


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


About Kroll


In a world of disruption and increasingly complex business challenges, our professionals bring truth into focus with the Kroll Lens. Our sharp analytical skills, paired with the latest technology, allow us to give our clients clarity, not just answering all areas of business. We value the diverse backgrounds and perspectives that enable us to think globally. As part of One team, One Kroll, you’ll contribute to a supportive and collaborative work environment that empowers you to excel.


Kroll is the premier global valuation and corporate finance advisor with expertise in complex valuation, disputes and investigations, M&A, restructuring, and compliance and regulatory consulting. Our professionals balance analytical skills, deep market insight and independence to help our clients make sound decisions. As an organization, we think globally and encourage our people to do the same.


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


In order to be considered for a position, you must formally apply via careers.kroll.com.


#LI-Hybrid


#LI-TL1



This job post has been translated by AI and may contain minor differences or errors.

You’ve reached the maximum limit of 15 job alerts. To create a new alert, please delete an existing one first.
Job alert created for this search. You’ll receive updates when new jobs match.
Are you sure you want to unapply?

You'll no longer be considered for this role and your application will be removed from the employer's inbox.