Neuberger's Private Markets Technology group is seeking a Senior Data Engineer to design and scale the data infrastructure supporting our private equity and private debt strategies. This role sits at the intersection of data engineering and investment operations — you will work directly with fund administration, operations, and analytics teams to model, move, and govern data across a complex, multi-administrator environment spanning multiple fund structures and jurisdictions. Our data landscape is operationally driven and non-standard by nature — sourced from GP notices, fund administrators, data rooms, and bespoke operational workflows rather than exchange feeds or market data vendors. We need someone who understands that distinction and can build for it.
Key Responsibilities:
Develop and optimize data models in the data warehouse for analytics, reporting, and operational workloads — translating private markets workflows such as capital calls, distributions, and co-investment closings into well-governed, reusable datasets
Design, build, and maintain scalable ETL/ELT data pipelines that ingest and normalize large volumes of structured and unstructured data from multiple fund administrators with inconsistent booking conventions across diverse fund structures and jurisdictions
Implement data quality checks, monitoring, and alerting to ensure the reliability and accuracy of data across the platform.
Collaborate with users and development teams to understand data requirements and deliver well-modeled, accessible datasets.
Optimize query performance, pipeline throughput, and storage costs across the data platform.
Contribute to data governance practices including documentation, lineage tracking, cataloging, and access controls — with a focus on golden record ownership and how upstream data quality propagates through downstream investment and reporting systems
Leverage AI to drive efficient coding and process design
Required Qualifications
Bachelor’s degree in Computer Science, Data Engineering, Information Systems, or a related field.
7+ years of professional experience in data engineering, building and maintaining production data pipelines.
Financial markets data domain experience required with Private Markets data experience a plus
Demonstrated fluency with AI tools — co-pilot tools, LLM-assisted development, or AI-augmented data workflows
Advanced SQL skills and experience designing dimensional data models (star schema, snowflake schema).
Proficiency in Python and experience with data processing frameworks such as Apache Spark, Pandas, or Polars.
Hands-on experience with orchestration tools such as Apache Airflow
Experience with Snowflake and cloud services (AWS or Azure).
Familiarity with data transformation tools like dbt and version-controlled analytics workflows.
Solid understanding of software engineering best practices including Git, CI/CD, testing, and containerization.
Preferred Qualifications
Experience with streaming data architecture using Kafka
Experience implementing data contracts and schema evolution strategies.
Experience with OpenShift platform
Experience normalizing data across similar data sets
Experience private markets data context
Work model
Location: New York City; hybrid with a minimum of two days per week in office.
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Applicants must be authorized and have the right to work in the country where the role is located without the need for current or future sponsorship.Compensation Details
The salary range for this role is $110,000-$150,000. This is the lowest to highest salary we in good faith believe we would pay for this role at the time of this posting. We may ultimately pay more or less than the posted range, and the range may be modified in the future. This range is only applicable for jobs to be performed in the job posting location. An employee’s pay position within the salary range will be based on several factors including, but limited to, relevant education, qualifications, certifications, experience, skills, seniority, geographic location, business sector, performance, shift, travel requirements, sales or revenue-based metrics, market benchmarking data, any collective bargaining agreements, and business or organizational needs. This job is also eligible for a discretionary bonus, which, along with base salary and retirement contributions, is part of our total comprehensive package. We offer a comprehensive package of benefits including paid time off, medical/dental/vision insurance, retirement, life insurance and other benefits to eligible employees.Note: No amount of pay is considered to be wages or compensation until such amount is earned, vested, and determinable. The amount and availability of any bonus, commission, production, or any other form of compensation that are allocable to a particular employee remains in the Company's sole discretion unless and until paid and may be modified at the Company’s sole discretion, consistent with the law.Neuberger is an equal opportunity employer. The Firm and its affiliates do not discriminate in employment because of race, creed, national origin, religion, age, color, sex, marital status, sexual orientation, gender identity, disability, citizenship status or protected veteran status, or any other characteristic protected by local, state, or federal laws, rules, or regulations. If you would like to contact us regarding the accessibility of our website or need assistance completing the application process, please contact [email protected].
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Skills Required
- Bachelor's degree in Computer Science, Data Engineering, Information Systems, or a related field.
- 7+ years of professional experience in data engineering, building and maintaining production data pipelines.
- Financial markets data domain experience required with Private Markets data experience a plus
- Demonstrated fluency with AI tools
- Advanced SQL skills and experience designing dimensional data models.
- Proficiency in Python and experience with data processing frameworks such as Apache Spark, Pandas, or Polars.
- Hands-on experience with orchestration tools such as Apache Airflow
- Experience with Snowflake and cloud services (AWS or Azure).
- Familiarity with data transformation tools like dbt and version-controlled analytics workflows.
- Solid understanding of software engineering best practices including Git, CI/CD, testing, and containerization.
Neuberger Berman Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Neuberger Berman and has not been reviewed or approved by Neuberger Berman.
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Retirement Support — Employer-funded retirement contributions are widely highlighted as a standout perk that materially strengthens total rewards. Feedback suggests this benefit often offsets concerns about lower cash compensation.
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Healthcare Strength — Comprehensive medical, dental, and vision coverage is characterized as solid and reliable. Feedback suggests health benefits are a stable pillar of the package.
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Leave & Time Off Breadth — PTO and paid leave are commonly viewed as supportive within the industry context. Feedback suggests time-off policies contribute meaningfully to perceived overall value.
Neuberger Berman Insights
What We Do
Neuberger Berman, founded in 1939, is a private, independent, employee-owned investment manager. The firm manages a range of strategies—including equity, fixed income, quantitative and multi-asset class, private equity, real estate and hedge funds—on behalf of institutions, advisors and individual investors globally. With offices in 25 countries, Neuberger Berman’s diverse team has over 2,400 professionals. For eight consecutive years, the company has been named first or second in Pensions & Investments Best Places to Work in Money Management survey (among those with 1,000 employees or more). In 2020, the PRI named Neuberger Berman a Leader, a designation awarded to fewer than 1% of investment firms for excellence in Environmental, Social and Governance (ESG) practices. The PRI also awarded Neuberger Berman an A+ in every eligible category for our approach to ESG integration across asset classes. For important disclosures: http://www.nb.com/linkedin


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