Manager, Discovery Solutions

Kroll

New York (NY)

On-site

USD 90,000 - 200,000

Full time

9 hours ago
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Benefits offered by this job

Healthcare Coverage
PTO & Holidays
Insurance (life / disability)
Merit-based compensation reviews
401(k) with company match

Job summary

Kroll seeks a Manager-level Complex Data Extraction Specialist to lead technically demanding extraction and transformation workflows involving large datasets and non-standard source formats. You will develop defensible technical approaches and support solution design for complex litigation, investigations, and sensitive data engagements.

You will partner with eDiscovery, analytics, forensics, and client-facing teams to translate matter requirements into practical workflows while mentoring junior

Qualifications

  • Bachelor’s degree or equivalent in a related field; 6–8 years in eDiscovery, data engineering, or complex data extraction.
  • Strong scripting and data transformation skills; experience with large datasets and non-standard formats.
  • Ability to scope technical work, communicate risks, and document workflows clearly.

Responsibilities

  • Lead complex data extraction and transformation workflows across large, heterogeneous datasets.
  • Define extraction strategies, assumptions, validation requirements, and defensible technical approaches.
  • Collaborate with eDiscovery, analytics, forensics, and client teams to translate requirements into executable workflows.
  • Troubleshoot data conditions like inconsistent metadata, malformed files, and unusual containers.
  • Design reusable extraction methods, quality controls, and documentation for reuse across matters.
  • Estimate effort, identify dependencies and risks, and contribute to scoping and pricing.
  • Provide technical guidance to project teams and junior staff; escalate issues when needed.
  • Evaluate need for specialized tools or external support and help transition repeatable work to scalable workflows.

Skills

Scripting
Data transformation
Troubleshooting
Validation
Workflow documentation

Education

Bachelor’s degree or equivalent in information technology / computer science / data engineering

Job description

Kroll is seeking a Manager-level Complex Data Extraction Specialist to join its Discovery & Analytics Solutions practice. This role will lead technically demanding extraction and transformation workflows involving large datasets and non-standard source formats, develop defensible technical approaches, and support solution design for complex litigation, investigations, regulatory matters, and sensitive data engagements.

Day To Day Responsibilities
  • Lead complex data extraction and transformation workflows across large, heterogeneous datasets and non-standard source formats.
  • Assess source systems and data structures; define extraction strategies, assumptions, and validation requirements; and develop defensible technical approaches.
  • Partner with eDiscovery, analytics, forensics, sensitive data review, and client-facing teams to translate matter requirements into practical, executable workflows.
  • Troubleshoot difficult data conditions, including inconsistent metadata, malformed files, unusual containers, incomplete exports, and other non-standard data sources.
  • Design reusable extraction methods, quality controls, and technical documentation that can be applied consistently across matters.
  • Estimate effort, identify dependencies and risks, and provide technical input for scoping, pricing, and solution design.
  • Serve as an escalation point for extraction-related issues and provide technical guidance to project teams and junior staff.
  • Evaluate when specialized tools or external support are required and help transition repeatable work into scalable Kroll-delivered workflows.
Essential Traits
  • Bachelor’s degree in information technology, computer science, data engineering, digital forensics, or a related field; equivalent relevant experience will be considered.
  • Typically 6–8 years of experience in eDiscovery, data engineering, digital forensics, litigation support, or complex data extraction.
  • Demonstrated experience working with large datasets, structured and unstructured data, and non-standard source formats.
  • Strong scripting, data transformation, troubleshooting, validation, and workflow-documentation skills.
  • Working knowledge of eDiscovery processing, Relativity, data privacy, chain of custody, and defensibility considerations.
  • Ability to independently scope technical work, communicate constraints and risks clearly, manage competing priorities, and operate effectively across multiple concurrent matters.
  • Healthcare Coverage: Comprehensive medical, dental, and vision plans.
  • Time Off and Leave Policies: Generous paid time off (PTO), paid company holidays, generous parental and family leave.
  • Protective Insurances: Life insurance, short- and long-term disability coverage, and accident protection.
  • Compensation and Rewards: Competitive salary structures, performance-based incentives, and merit-based compensation reviews.
  • Retirement Plans: 401(k) plans with company matching.

Please note that benefits may vary by region, department and role. We encourage you to speak with your recruiter to learn more about the specific benefits available for your position.

About Kroll

Join the global leader in risk and financial advisory solutions—Kroll. With a nearly century-long legacy, we blend trusted expertise with cutting-edge technology to navigate and redefine industry complexities. As a part of One Team, One Kroll, you'll contribute to a collaborative and empowering environment, propelling your career to new heights. Ready to build, protect, restore and maximize our clients’ value? Your journey begins with Kroll.

We are proud to be an equal opportunity employer and will consider all qualified applicants regardless of gender, gender identity, race, religion, color, nationality, ethnic origin, sexual orientation, marital status, veteran status, age or disability.

The current salary range for this position is $90,000 to $200,000

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