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Data Operations Jobs in New York (NOW HIRING)

Working closely with the Asset Domain Data Trustee and sub-domain trustees, and in collaboration with the investment operations, data governance and technology teams, you will build deep expertise in ...

Manager, Operations, Data & Reporting Department: SEO Career & Alternative Investments Report to: Assistant Director, Data & Reporting Compensation: $70,500 - $83,000 FLSA: Exempt Employee Type ...

As Sourcing Manager, Data Operations, you'll work closely with business and research teams across Meta and its affiliates to develop and execute sourcing, contracting, and purchasing strategies that ...

Data Product Operations Lead

New York, NY ยท On-site

$145K - $175K/yr

About our Data Operations team Our Data Operations team powers David AI's Data Factory, transforming raw audio into high-quality training datasets for leading AI labs. Our mandate is to spin up new ...

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Data Operations information

See New York salary details

$56.9K

$140.6K

$218.8K

How much do data operations jobs pay per year?

As of Aug 8, 2026, the average yearly pay for data operations in New York is $140,611.00, according to ZipRecruiter salary data. Most workers in this role earn between $102,800.00 and $178,900.00 per year, depending on experience, location, and employer.

What is a data operations?

A Data Operations job involves managing and optimizing the processes, tools, and workflows that ensure the efficient movement, storage, and accessibility of data. This includes data ingestion, transformation, quality assurance, and pipeline monitoring to support analytics and business intelligence. Data Operations professionals collaborate with engineers, analysts, and business teams to improve data reliability, scalability, and performance. Their role is critical in maintaining clean, accessible, and well-governed data for decision-making.

What is the role of data operations?

Data operations involve managing, processing, and maintaining data to ensure its accuracy, availability, and security for organizational use. Professionals in this role often work with data management tools, databases, and automation processes to support data-driven decision-making.

What types of teams and departments does data operations typically collaborate with?

Data Operations professionals often work closely with data engineering, business intelligence, IT, and analytics teams, as well as stakeholders from various business units such as marketing, finance, and operations. Their role frequently involves coordinating data pipelines, troubleshooting data quality issues, and ensuring smooth integration across systems. This cross-functional collaboration helps align data efforts with organizational goals and supports informed decision-making throughout the company. Being adaptable and communicative is key, as you'll regularly facilitate the flow of data and insights between technical teams and business users.

What are the key skills and qualifications needed to thrive in data operations, and why are they important?

To thrive in Data Operations, you need strong analytical skills, data management experience, and a background in fields like information systems, computer science, or statistics. Familiarity with data visualization tools (e.g., Tableau), database management systems (e.g., SQL), and data integration platforms, along with relevant certifications such as AWS or Microsoft Azure Data Engineer, are highly valuable. Exceptional attention to detail, problem-solving ability, and effective collaboration skills differentiate top performers in this role. These competencies ensure accurate data flow, system integrity, and seamless cross-team cooperation, all of which are critical for maintaining reliable business operations.

What are the most commonly searched types of Data Operations jobs in New York? The most popular types of Data Operations jobs in New York are:
What are popular job titles related to Data Operations jobs in New York? For Data Operations jobs in New York, the most frequently searched job titles are:
What cities in New York are hiring for Data Operations jobs? Cities in New York with the most Data Operations job openings:
Infographic showing various Data Operations job openings in New York as of August 2026, with employment types broken down into 84% Full Time, 13% Part Time, 1% Temporary, and 2% Contract. Highlights an 94% Physical, 2% Hybrid, and 4% Remote job distribution, with an average salary of $140,611 per year, or $67.6 per hour.

Data Operations - Distribution Data Enablement Lead

Careers at KKR

New York, NY โ€ข On-site

Full-time

Re-posted 20 days ago


Job description

COMPANY OVERVIEW
KKR is a leading global investment firm that offers alternative asset management as well as capital markets and insurance solutions. KKR aims to generate attractive investment returns by following a patient and disciplined investment approach, employing world-class people, and supporting growth in its portfolio companies and communities. KKR sponsors investment funds that invest in private equity, credit and real assets and has strategic partners that manage hedge funds. KKR's insurance subsidiaries offer retirement, life and reinsurance products under the management of Global Atlantic Financial Group. References to KKR's investments may include the activities of its sponsored funds and insurance subsidiaries.
TEAM OVERVIEW
KKR's Global Data Operations team is responsible for collecting, managing, governing, and harnessing data across the firm. Within Data Operations, the Data Operations Center of Excellence (CoE) operates as a hub-and-spoke data delivery engine, pairing functional spokes with deep business expertise and a central delivery hub with scalable data, analytics, governance, reporting, and core data management capabilities.
The Distribution Data Enablement team is the functional spoke supporting KKR's Distribution organization, delivering trusted data and analytics solutions across client and LP data management, operational controls and reconciliations, fund performance, LP outcomes, relationship economics, fundraising trends, and broader business performance across asset classes.
POSITION OVERVIEW
We are seeking a Principal-level Distribution Data Enablement Lead to serve as the primary data and analytics partner for Distribution business performance, fund performance analytics, LP-level insights, and cross-asset-class commercial intelligence.
This role will help define and build a quantitative, forward-looking, and solution-oriented data enablement capability for Distribution. The individual will be responsible for developing scalable analytics, models, tools/automation, and data solutions that support decision-making across fundraising, product strategy, investor engagement, fund performance, LP outcomes, relationship economics, and broader commercial performance.
The successful candidate will design, build and lead advanced analytical capabilities, including the Python-based models, applications, automation, and self-service tools required to operationalize the function. These capabilities will help Distribution answer complex questions such as how fund performance changes if specific deals are included or excluded, how outcomes compare across strategies, how co-investment participation affects investor outcomes, how LP relationships perform economically over time, where profitability is concentrated across the client base, and how fundraising, product, and investor trends are evolving across the platform.
This is a highly hands-on technical leadership role. The individual must be able to partner with senior Distribution, Product Strategy, Finance, Investment, and Data/Technology stakeholders while personally building models, prototyping analytical tools, automating workflows, and modernizing the firm's Distribution data and analytics environment. The role will require strong technical execution, commercial judgment, and the ability to influence strategic architecture decisions as the capability is built out.
RESPONSIBILITIES
  • Serve as the primary analytics partner for Distribution business performance, fund performance analytics, LP-level insights, and investor economics
  • Lead the evolution of the historical Performance Analytics function from a private markets-focused reporting capability into a broader cross-asset-class Distribution advanced analytics and data enablement function
  • Build analytical models, Python-based data applications, automation, and self-service tools that enable scalable insight generation rather than one-off analysis
  • Deliver high-quality ad-hoc analysis, performance insights, hypothetical scenarios, investor analytics, and business performance reporting for senior Distribution stakeholders
  • Build reusable models that evaluate fund performance under different hypothetical scenarios, including inclusion or exclusion of specific deals, co-investment participation, investment timing, cash flow assumptions, and portfolio composition changes
  • Develop LP-level analytics across asset classes, including investor performance, exposure, allocation, capital activity, product participation, and relationship-level economics
  • Build profitability and commercial performance analytics for LP relationships, including revenue, economics, resource intensity, product participation, and long-term relationship value
  • Support macro-Distribution business performance analysis, including fundraising trends, platform economics, investor segmentation, product performance, and concentration across LPs, channels, regions, and strategies
  • Integrate Distribution, fund, investor, deal, finance, and accounting data to create richer analytical views of investor outcomes and business performance
  • Modernize manual and Excel-heavy performance analytics processes through reusable models, governed datasets, standardized calculations, and automated workflows
  • Partner with Technology and Data Operations to productionize prototypes, improve data pipelines, and strengthen the broader Distribution analytics infrastructure
  • Translate complex fund, deal, LP, and commercial data into clear insights, executive-ready narratives, and decision-support materials
  • Establish quality controls, documentation, and governance standards for recurring analytics, scenario models, dashboards, and decision-support tools
  • Help define the long-term operating model for Distribution data enablement, including service model, toolset, prioritization framework, data standards, and partnership model with Product Strategy, Finance, Technology, and Distribution stakeholders

QUALIFICATIONS
  • 10+ years of experience in investment analytics, performance analytics, investor analytics, quantitative analytics, financial analysis/ engineering, business performance analytics, or related roles within asset management, alternatives, investment banking, or financial services
  • Deep understanding of private markets performance concepts/metrics, including fund structures, LP reporting, capital activity, valuations, fund cash flows, IRR, MOIC, TVPI, DPI, PME, benchmarking, performance attribution models, and deal-level contribution analysis
  • Strong cross-asset-class orientation, with the ability to extend fund, investor, and business performance analytics across private equity, credit, real estate, infrastructure, insurance-related strategies, and other investment products
  • Experience developing hypothetical and scenario-based analysis, including deal inclusion/exclusion, co-investment impact, cash flow projections, portfolio construction changes, and LP-specific performance scenarios
  • Strong understanding of LP-level analytics, including investor exposure, product participation, capital commitments, unfunded balances, subscriptions, redemptions, distributions, realized/unrealized performance, and relationship economics
  • Experience with business performance or profitability analytics, including client profitability, revenue attribution, relationship value, platform economics, segmentation, concentration, and commercial trend analysis
  • Familiarity with financial books and records, fund accounting, investment accounting, and performance data environments; experience with platforms such as Investran, Geneva, Salesforce, or similar systems preferred
  • Highly hands-on technical coding skills, including advanced Python capability and experience building analytical tools, applications, automation, reusable models, and scalable reporting solutions
  • Advanced SQL and database manipulation skills, with the ability to work directly with large, complex datasets across fund, deal, investor, performance, fundraising, revenue, and commercial domains (Snowflake or Databricks experience strongly preferred)
  • Experience with Sigma, Power BI, Tableau, or similar business intelligence platforms, including dashboard design, semantic data modeling, governed metrics, and self-service analytics
  • Demonstrated ability to reduce reliance on manual Excel-based workflows and replace them with scalable, controlled, automated, and transparent analytical processes
  • Strong commercial judgment, with the ability to connect analytical outputs to Distribution strategy, investor engagement, product decisions, and business performance outcomes
  • Ability to operate effectively with senior stakeholders while managing fast-moving ad hoc requests and longer-term capability-building priorities
  • Strong communication skills, with the ability to explain complex quantitative, data, performance, and profitability concepts clearly to technical and non-technical audiences
  • Advanced degrees in finance, economics, mathematics, statistics, engineering, computer science, operations research, or another quantitative discipline preferred
  • CFA, CAIA, FRM, or similar professional designation helpful but not required

PREFERRED PROFILE
The ideal candidate is a commercially oriented quant who can help Distribution understand fund performance, LP outcomes, relationship economics, and business performance at a deeper level than traditional reporting. This person should be able to frame the analytical question, source, structure, and validate the data, build the model or tool, pressure-test the results, and translate the output into clear business insights.
This is a hands-on builder and analytical leader, not simply a report producer. The right candidate will be comfortable moving between deal-level economics, fund performance, LP profitability, data architecture, Python-based modeling, dashboard/ visualization design, and senior stakeholder engagement.
#LI-ONSITE
This is the expected annual base salary range for this New York-based position. Actual salaries may vary based on factors, such as skill, experience, and qualification for the role. Employees may be eligible for a discretionary bonus, based on factors such as individual and team performance.
Base Salary Range
$195,000-$235,000 USD
KKR is an equal opportunity employer. Individuals seeking employment are considered without regard to race, color, religion, national origin, age, sex, marital status, ancestry, physical or mental disability, veteran status, sexual orientation, or any other category protected by applicable law.
KKR will provide reasonable accommodations as required by applicable federal, state, and/or local laws. Individuals seeking an accommodation for the application or interview process should email Benefits@kkr.com. Emails sent for unrelated issues, such as following up on an application, will not receive a response.
If you are a qualified individual with a disability or a disabled veteran, you may request a reasonable accommodation if you are unable or limited in your ability to use or access https://www.kkr.com/careers because of your disability. You can request reasonable accommodations by sending an email to Benefits@kkr.com. Only emails left for this purpose will be returned.
Massachusetts Applicants: It is unlawful in Massachusetts to require or administer a lie detector test as a condition of employment or continued employment. An employer who violates this law shall be subject to criminal penalties and civil liability. This notice applies only to applicants and employees who work or will work in Massachusetts, in accordance with applicable state law.