Senior Developer I - Data Engineer at Neuberger Berman Europe Ltd

New York, New York, United States -

Full Time

Start Date

Immediate

Expiry Date

02 Sep, 26

Salary

150000.0

Posted On

04 Jun, 26

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

SQL, Python, Apache Spark, Pandas, Polars, Apache Airflow, Snowflake, AWS, Azure, dbt, Git, CI/CD, Containerization, Dimensional Data Modeling, ETL/ELT, AI Tools

Industry

Financial Services

Description

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. #LI-DD2 #LI-Hybrid 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 onlineaccommodations@nb.com. Learn about the Applicant Privacy Notice.

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Responsibilities

Design and scale data infrastructure to support private equity and private debt strategies by building scalable ETL/ELT pipelines. Develop optimized data models and implement data quality monitoring to ensure reliable reporting across complex fund structures.