Back to jobs

Associate Engineer, Investment Data & Analytics

Pay
$155,000–165,000/year · BaseAnnual period assumed — pay source
Base Salary Range $155,000.00 - $165,000.00 This USD base salary range represents only one component of total compensation for this role and is provided in accordance with local requirements. This role is eligible for a discretionary annual bonus, which is determined based on individual and overall firm performance. In addition to salary and bonus eligibility, total compensation may include participation in long-term reward programs (typically for more senior-level roles). We also offer a comprehensive total rewards package that may include retirement contributions, health insurance, income protection, paid time off and leave benefits as well as well-being programs. Our total rewards offerings are influenced by several business factors, and eligibility for certain components will vary by position and geography. Please note the posted ranges do not apply outside the U.S. and should not be converted to other currencies as a proxy for compensation in other countries.
Read the full posting
Work setting
Hybrid — work setting source
HarbourVest is an equal opportunity employer. This position will be a hybrid work arrangement. You will receive 18 remote workdays per quarter to use at your discretion, subject to manager approval. For example, you may choose to work in the office 4 days per week and take one remote day weekly (typically 13 weeks per quarter), leaving 5 additional remote days to be used as needed. About Investment Data and Analytics
Read the full posting
Employment
Full-time — employment source
Employment type in the employer’s posting: Full time
From the employer’s posting

What you’ll work on

Full posting
  • Build, test and deploy data pipelines and transformations on financial datasets

  • Run and monitor production data workflows and troubleshoot failures

  • Build validation and reconciliation checks and own root-cause analysis for data issues

  • Partner with engineering and investment teams to clarify requirements and document solutions

  • Analyze data for investment model research and find manual processes to automate

From the employer’s posting
build, test, and deploy pipelines and transformations across financial/economic datasets
run and monitor production data workflows, troubleshoot failures
develop validation and reconciliation checks, monitor pipeline health through KPIs, and own root-cause analysis for data issues
partner with data engineering, DevOps, application, and investment teams to clarify requirements and deliver well-documented solutions
perform deep data analysis to support investment model research and identify manual processes worth automating

What you’ll bring

All qualifications

Core experience

  • Demonstrated ability in data engineering and analysis, including data-centric testing and deployment of FinTech applications.
  • Bachelor of Science (B.S) or equivalent in Computer Science
  • Proficiency in SQL (MSSQL or equivalent RDBMS) and Python, with experience building ETL pipelines for large datasets.
  • Master of Science (M.S) or equivalent in Computer Science

Preferred experience

  • Experience with DBT and Azure Data Factory and Pipelines; exposure to Snowflake, MS Synapse, or Power BI a plus.
  • 3-5 Years of Data Engineering or Data Operations experience preferred
Qualification wording
Demonstrated ability in data engineering and analysis, including data-centric testing and deployment of FinTech applications.
Bachelor of Science (B.S) or equivalent in Computer Science
Proficiency in SQL (MSSQL or equivalent RDBMS) and Python, with experience building ETL pipelines for large datasets.
Master of Science (M.S) or equivalent in Computer Science
Experience with DBT and Azure Data Factory and Pipelines; exposure to Snowflake, MS Synapse, or Power BI a plus.
3-5 Years of Data Engineering or Data Operations experience preferred
Education & alternatives
Education Preferred - Bachelor of Science (B.S) or equivalent in Computer Science - Master of Science (M.S) or equivalent in Computer Science
- Bachelor of Science (B.S) or equivalent in Computer Science - Master of Science (M.S) or equivalent in Computer Science Experience

About Harbourvest

Our organization’s mission is to build technology that lets the firm systematize and scale its understanding of private markets and management of our funds.

In the employer’s words · Read in context

Apply at Harbourvest

Posting record

Report an error
Status in our records
Live
First seen by us
Aug 27, 202669 days ago
Recorded sightings
22
Last seen by us
Nov 4, 2026

These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.

How this job compares

Pay

In line with similar jobs

$155K–$165K against $127K–$190K, the middle half of what similar US postings state.

From 2,133 postings in the last year. Stated ranges, not salaries paid.

Time since we first saw it

Day 69

Up longer than most. Similar jobs usually come down between day 6 and day 54.

At Harbourvest, jobs usually come down by about day 56.

From 10,957 similar postings that came down, and 5 of Harbourvest’s. Coming down is not always a hire.

Harbourvest is hiring

4 open jobs

Open jobs by the week we first saw them, last 12 weeks.

  • Hiring is picking up
  • Takes jobs down at a usual pace
  • 25% of open jobs were reposted
Hiring record

See how this role fits your experience

Add your resume and we’ll mark which of these tools you already use, and point out anything in the posting that could rule you out.

  • Python
  • SQL
  • Azure
  • dbt
  • Power BI
  • Snowflake
Where the posting names them
- Demonstrated ability in data engineering and analysis, including data-centric testing and deployment of FinTech applications. - Proficiency in SQL (MSSQL or equivalent RDBMS) and Python, with experience building ETL pipelines for large datasets. - Experience with DBT and Azure Data Factory and Pipelines; exposure to Snowflake, MS Synapse, or Power BI a plus.
- Proficiency in SQL (MSSQL or equivalent RDBMS) and Python, with experience building ETL pipelines for large datasets. - Experience with DBT and Azure Data Factory and Pipelines; exposure to Snowflake, MS Synapse, or Power BI a plus. - Strong analytical, organizational, and problem-solving skills with outstanding attention to detail, a genuine interest in financial markets, and comfort working in a scrum/agile SDLC environment.

Your next step

Complete your application on harbourvest.wd5.myworkdayjobs.com. The employer’s form will show what is required.

Applying through Workday

  • You create an account with each employer before you can upload anything. Every Workday employer has its own account, so one sign-up doesn’t carry over.
  • “Autofill with Resume” comes right after sign-in, before the My Information and My Experience steps. Check every field it fills in those steps, since that’s what recruiters see.
  • Your application status lives in that employer’s Candidate Home, under the same sign-in.

Already applied? Track this application

About the role

We file this job under Data Engineer, by the work the posting describes.

Data engineers build and run the pipelines that copy data out of apps and outside services into a warehouse or lake, and fix them when a source changes or a load fails.

Expect SQL, Python, a cloud platform, a scheduler such as Airflow, and often tools for large data such as Spark or Kafka.

An analytics engineer works one step later, turning the raw data a data engineer lands into clean tables people can query.

US government figures for database architects

Median yearly pay, May 2025
$139,500
Expected change, 2025 to 2035
9.4% more jobsagainst 3.5% for all jobs

The government has no code for data engineers, so these figures are for the closest group, database architects, which includes data integration and data warehousing specialists.

Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-1243.

Job description

View original posting ↗

Job Description Summary

For over forty years, HarbourVest has been home to a committed team of professionals with an entrepreneurial spirit and a desire to deliver impactful solutions to our clients and investing partners. As our global firm grows, we continue to add individuals who seek a collaborative, open-door culture that values diversity and innovative thinking.  

In our collegial environment that’s marked by low turnover and high energy, you’ll be inspired to grow and thrive. Here, you will be encouraged to build on your strengths and acquire new skills and experiences.  

We are committed to fostering an environment of inclusion that promotes mutual respect among all employees. Understanding and valuing these differences optimizes the potential of both the individual and the firm. 

HarbourVest is an equal opportunity employer. 

This position will be a hybrid work arrangement. You will receive 18 remote workdays per quarter to use at your discretion, subject to manager approval. For example, you may choose to work in the office 4 days per week and take one remote day weekly (typically 13 weeks per quarter), leaving 5 additional remote days to be used as needed. 

About Investment Data and Analytics 

Our organization’s mission is to build technology that lets the firm systematize and scale its understanding of private markets and management of our funds. Our team works side-by-side with investors and quantitative researchers to innovate technology-driven investment processes; solve broad industry problems ranging from AI driven digitization of unstructured data to systematic monitoring of private equity portfolios.  

The Associate role combines hands-on engineering execution with the opportunity to build deep expertise in private markets data. Working under the guidance of senior engineers, you will develop, test, and operate the pipelines and datasets our investment and research teams rely on — taking on progressively more complex ownership as your technical and domain judgment grows. 

What you will do: 

  • Data engineering — build, test, and deploy pipelines and transformations across financial/economic datasets using modern data stacks. 
  • Infrastructure/platform engineering — run and monitor production data workflows, troubleshoot failures, and implement alerting, logging, and automated testing within CI/CD. 
  • Data Quality — develop validation and reconciliation checks, monitor pipeline health through KPIs, and own root-cause analysis for data issues. 
  • Collaboration — partner with data engineering, DevOps, application, and investment teams to clarify requirements and deliver well-documented solutions. 
  • And ... Problem solving — perform deep data analysis to support investment model research and identify manual processes worth automating. 

What you bring: 

  • Demonstrated ability in data engineering and analysis, including data-centric testing and deployment of FinTech applications. 
  • Proficiency in SQL (MSSQL or equivalent RDBMS) and Python, with experience building ETL pipelines for large datasets. 
  • Experience with DBT and Azure Data Factory and Pipelines; exposure to Snowflake, MS Synapse, or Power BI a plus. 
  • Strong analytical, organizational, and problem-solving skills with outstanding attention to detail, a genuine interest in financial markets, and comfort working in a scrum/agile SDLC environment. 

Education Preferred 

  • Bachelor of Science (B.S) or equivalent in Computer Science 
  • Master of Science (M.S) or equivalent in Computer Science 

Experience 

  • 3-5 Years of Data Engineering or Data Operations experience preferred 
  • Exposure to private equity or investment management data, partnering with product, application, and operations teams 

#LI-Hybrid

Base Salary Range

$155,000.00 - $165,000.00

This USD base salary range represents only one component of total compensation for this role and is provided in accordance with local requirements. This role is eligible for a discretionary annual bonus, which is determined based on individual and overall firm performance. In addition to salary and bonus eligibility, total compensation may include participation in long-term reward programs (typically for more senior-level roles). We also offer a comprehensive total rewards package that may include retirement contributions, health insurance, income protection, paid time off and leave benefits as well as well-being programs. Our total rewards offerings are influenced by several business factors, and eligibility for certain components will vary by position and geography. Please note the posted ranges do not apply outside the U.S. and should not be converted to other currencies as a proxy for compensation in other countries.

Source details

View original posting ↗

Source notes

Source excerpts

Selected passages from the saved posting. Check the full description for conditions and exceptions.

Pay
Base Salary Range $155,000.00 - $165,000.00 This USD base salary range represents only one component of total compensation for this role and is provided in accordance with local requirements. This role is eligible for a discretionary annual bonus, which is determined based on individual and overall firm performance. In addition to salary and bonus eligibility, total compensation may include participation in long-term reward programs (typically for more senior-level roles). We also offer a comprehensive total rewards package that may include retirement contributions, health insurance, income protection, paid time off and leave benefits as well as well-being programs. Our total rewards offerings are influenced by several business factors, and eligibility for certain components will vary by position and geography. Please note the posted ranges do not apply outside the U.S. and should not be converted to other currencies as a proxy for compensation in other countries.
Location & working pattern

Boston

HarbourVest is an equal opportunity employer. This position will be a hybrid work arrangement. You will receive 18 remote workdays per quarter to use at your discretion, subject to manager approval. For example, you may choose to work in the office 4 days per week and take one remote day weekly (typically 13 weeks per quarter), leaving 5 additional remote days to be used as needed. About Investment Data and Analytics
More source context
- Exposure to private equity or investment management data, partnering with product, application, and operations teams #LI-Hybrid Base Salary Range
Work authorization

No clear work-authorization passage found. Eligibility is unconfirmed.

Find answers in the posting

AI
How answers work

AI selects complete passages from this posting. Check them for conditions and exceptions.

Uses this posting and your question. No profile needed.