Senior Developer I - Data Engineer
New York, NY
- Pay
$130,000–170,000/yearAnnual period assumed · Location-specific pay — pay source
Compensation Details The salary range for this role is $130,000-$170,000. 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.
Read the full posting- Work setting
Hybrid — work setting source
Work model Location: New York City; hybrid with a minimum of two days per week in office. #LI-DD2
Read the full posting- Employment
Full-time — employment source
Employment type in the employer’s posting: Full time
From the employer’s posting
Before you apply
- Sponsorship
Visa sponsorship not confirmed — sponsorship source

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.
Read the full posting
What you’ll work on
Full postingBuild and maintain ETL/ELT pipelines that normalize data from multiple fund administrators
Develop data warehouse models for private markets workflows like capital calls and distributions
Implement data quality checks, monitoring, and alerting across the platform
Contribute to governance: documentation, lineage, cataloging, and access controls
Optimize query performance, pipeline throughput, and storage costs
From the employer’s posting
Design, build, and maintain scalable ETL/ELT data pipelines that ingest and normalize large volumes of structured and unstructured data from multiple fund administrators
Develop and optimize data models in the data warehouse for analytics, reporting, and operational workloads
Implement data quality checks, monitoring, and alerting to ensure the reliability and accuracy of data across the platform.
Contribute to data governance practices including documentation, lineage tracking, cataloging, and access controls
Optimize query performance, pipeline throughput, and storage costs across the data platform.
What you’ll bring
All qualificationsCore experience
- 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.
- 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.
Preferred experience
- 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
Qualification wording
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.
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.
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
Education & alternatives
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.
Tools in this posting
- Python
- SQL
- AWS
- Azure
- dbt
- Kafka
- Snowflake
- Spark
- Airflow
- pandas
- Polars
Source — Tool mentions in context
- 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
- 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.
- 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.
- 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).
Posting record
Report an errorOpen 4 monthsWe first saw this posting 148 days ago and it is still up. Roles open this long are often slow to fill or kept open to collect applications.
- Status in our records
- Live
- First seen by us
- Jun 3, 2026 · 148 days ago
- Recorded sightings
- 170
- Last seen by us
- Oct 29, 2026
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.
Your next step
- Have your resume and examples of relevant work ready.
- Check the listed location, eligibility and core experience before starting.
Complete your application on nb.wd1.myworkdayjobs.com. The employer’s form will show what is required.
Already applied? Track this application
Job 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 $130,000-$170,000. 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.
Source details
Source notes
Source excerptsSelected passages from the saved posting. Check the full description for conditions and exceptions.
- Pay
This passage needs a closer read in the full description.
- Location & working pattern
New York, NY
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.
- Work authorization
#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
More source context
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.
See how this role fits your experience
Add your resume to compare the role’s scope, tools and requirements with your experience.