Data Engineer
New York, NY
- Pay
$150,000–200,000/year · BaseAnnual period assumed — pay source
Benefits/Compensation The compensation range for this role is specific to New York, NY and takes into account a wide range of factors including but not limited to the skill sets required/preferred; prior experience and training; licenses and/or certifications. The anticipated base salary range for this role is $150,000 to $200,000. In addition to the base salary, the hired professional will enjoy a comprehensive benefits package spanning retirement benefits, health insurance, life insurance and disability, paid time off, paid holidays, family planning benefits and various wellness programs. Additionally, the hired professional may also be eligible to participate in an annual discretionary incentive program, the award of which will be dependent on various factors, including, without limitation, individual and organizational performance.
Read the full posting- Work setup
- Unconfirmed
- Employment
- Unconfirmed
What you’ll work on
Full postingWe are seeking a highly skilled Data Engineer to join our dynamic team.
Build, scale, and maintain robust data solutions to support the firm's objectives.
Lead software development projects end to end involving large language models (LLMs), retrieval-augmented generation (RAG) frameworks, and other AI technologies.
Collaborate closely with business stakeholders to transform use cases into production-ready services and solutions, owning the system from concept to production.
From the employer’s posting
We are seeking a highly skilled Data Engineer to join our dynamic team. The ideal candidate will be responsible for creating robust data pipelines from various data vendors to gold tables, primarily for our Machine Learning (ML) team, utilizing Snowflake and Databricks platforms. The role demands expertise in Python, deep familiarity with financial data sources, and the ability to deploy complex data pipelines efficiently. This position requires a proactive approach to analyzing, aggregating, and enriching financial data from both private and public companies.
Primary Responsibilities Build, scale, and maintain robust data solutions to support the firm's objectives. Implement and optimize high-performance data pipelines -- extraction, loading, transformation, and orchestration – that are designed for scalability, reliability, maintainability, and speed.
Implement and optimize high-performance data pipelines -- extraction, loading, transformation, and orchestration – that are designed for scalability, reliability, maintainability, and speed. Lead software development projects end to end involving large language models (LLMs), retrieval-augmented generation (RAG) frameworks, and other AI technologies. Champion modern software engineering practices as CI/CD, infrastructure-as-code, containerization, and cloud-native deployments
Champion modern software engineering practices as CI/CD, infrastructure-as-code, containerization, and cloud-native deployments Collaborate closely with business stakeholders to transform use cases into production-ready services and solutions, owning the system from concept to production. Implement rigorous testing and monitoring practices to maintain superior data quality and integrity.
What you’ll bring
All qualificationsCore experience
- Expertise in Python and SQL, with a strong foundation in data manipulation and analysis.
- Proficient with Databricks/PySpark and dbt for data warehousing and data transformation tasks.
- Experience with workflow orchestration tools e.g.
- Experience working with large language models (LLMs) especially prompt engineering, retrieval-augmented generation (RAG)s, and/or vector databases.
- Knowledge of fundamental principles of machine learning, feature engineering, and knowledge graphs are pluses.
- Demonstrated experience in designing and implementing complex data systems from the ground up.
Preferred experience
- Experience in the financial services or private equity industry, preferred
Qualification wording
Expertise in Python and SQL, with a strong foundation in data manipulation and analysis.
Proficient with Databricks/PySpark and dbt for data warehousing and data transformation tasks.
Experience with workflow orchestration tools e.g. Airflow, Temporal
Experience working with large language models (LLMs) especially prompt engineering, retrieval-augmented generation (RAG)s, and/or vector databases.
Knowledge of fundamental principles of machine learning, feature engineering, and knowledge graphs are pluses.
Demonstrated experience in designing and implementing complex data systems from the ground up.
Experience in the financial services or private equity industry, preferred
Tools in this posting
- Python
- SQL
- Databricks
- dbt
- Snowflake
- Airflow
- PySpark
Source — Tool mentions in context
Position Summary We are seeking a highly skilled Data Engineer to join our dynamic team. The ideal candidate will be responsible for creating robust data pipelines from various data vendors to gold tables, primarily for our Machine Learning (ML) team, utilizing Snowflake and Databricks platforms. The role demands expertise in Python, deep familiarity with financial data sources, and the ability to deploy complex data pipelines efficiently. This position requires a proactive approach to analyzing, aggregating, and enriching financial data from both private and public companies. Primary Responsibilities
Competencies & Attributes - Expertise in Python and SQL, with a strong foundation in data manipulation and analysis. - Proficient with Databricks/PySpark and dbt for data warehousing and data transformation tasks.
- Expertise in Python and SQL, with a strong foundation in data manipulation and analysis. - Proficient with Databricks/PySpark and dbt for data warehousing and data transformation tasks. - Experience with workflow orchestration tools e.g. Airflow, Temporal
- Proficient with Databricks/PySpark and dbt for data warehousing and data transformation tasks. - Experience with workflow orchestration tools e.g. Airflow, Temporal - Experience working with large language models (LLMs) especially prompt engineering, retrieval-augmented generation (RAG)s, and/or vector databases.
About Carlyle
When people, ideas, and capital come together, opportunity expands across private markets.
In the employer’s words · Read in context
Job description
Position Summary
We are seeking a highly skilled Data Engineer to join our dynamic team. The ideal candidate will be responsible for creating robust data pipelines from various data vendors to gold tables, primarily for our Machine Learning (ML) team, utilizing Snowflake and Databricks platforms. The role demands expertise in Python, deep familiarity with financial data sources, and the ability to deploy complex data pipelines efficiently. This position requires a proactive approach to analyzing, aggregating, and enriching financial data from both private and public companies.
Primary Responsibilities
- Build, scale, and maintain robust data solutions to support the firm's objectives.
- Implement and optimize high-performance data pipelines -- extraction, loading, transformation, and orchestration – that are designed for scalability, reliability, maintainability, and speed.
- Lead software development projects end to end involving large language models (LLMs), retrieval-augmented generation (RAG) frameworks, and other AI technologies.
- Champion modern software engineering practices as CI/CD, infrastructure-as-code, containerization, and cloud-native deployments
- Collaborate closely with business stakeholders to transform use cases into production-ready services and solutions, owning the system from concept to production.
- Implement rigorous testing and monitoring practices to maintain superior data quality and integrity.
- Mentor and develop junior team members, fostering a culture of excellence and continuous learning within the team.
- Be willing to travel up to 20% of the time to collaborate with distributed team members across locations.
Requirements
Education & Certificates
- A bachelor's degree, required
- Concentration in Computer Science, Math, Physics, STEM or other engineering related field, preferred
Professional Experience
- At least 6 years of experience in data engineering or a related discipline, with a proven track record of success, required
- Experience in the financial services or private equity industry, preferred
Competencies & Attributes
- Expertise in Python and SQL, with a strong foundation in data manipulation and analysis.
- Proficient with Databricks/PySpark and dbt for data warehousing and data transformation tasks.
- Experience with workflow orchestration tools e.g. Airflow, Temporal
- Experience working with large language models (LLMs) especially prompt engineering, retrieval-augmented generation (RAG)s, and/or vector databases.
- Knowledge of fundamental principles of machine learning, feature engineering, and knowledge graphs are pluses.
- Demonstrated experience in designing and implementing complex data systems from the ground up.
- Proficient in handling large-scale data projects, including data cleaning, ETL, and information retrieval.
- Previous experience in a product development or financial services environment is highly desirable.
- Excellent communication skills required, both verbal and written.
Benefits/Compensation
The compensation range for this role is specific to New York, NY and takes into account a wide range of factors including but not limited to the skill sets required/preferred; prior experience and training; licenses and/or certifications.
The anticipated base salary range for this role is $150,000 to $200,000.
In addition to the base salary, the hired professional will enjoy a comprehensive benefits package spanning retirement benefits, health insurance, life insurance and disability, paid time off, paid holidays, family planning benefits and various wellness programs. Additionally, the hired professional may also be eligible to participate in an annual discretionary incentive program, the award of which will be dependent on various factors, including, without limitation, individual and organizational performance.
Due to the high volume of candidates, please be advised that only candidates selected to interview will be contacted by Carlyle.
Who We Are
When people, ideas, and capital come together, opportunity expands across private markets. At Carlyle, this belief has shaped how we invest for decades, fueling growth for companies and delivering performance for investors.
Visit our website to learn more about our firm and the ways our platform is shaping private markets.
Your next step
- Have your CV and examples of relevant work ready.
- Check the listed location, eligibility and core experience before starting.
Complete your application on carlyle.wd1.myworkdayjobs.com. The employer’s form will show what is required.
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Source & posting history
Source notes
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- Pay
Benefits/Compensation The compensation range for this role is specific to New York, NY and takes into account a wide range of factors including but not limited to the skill sets required/preferred; prior experience and training; licenses and/or certifications. The anticipated base salary range for this role is $150,000 to $200,000. In addition to the base salary, the hired professional will enjoy a comprehensive benefits package spanning retirement benefits, health insurance, life insurance and disability, paid time off, paid holidays, family planning benefits and various wellness programs. Additionally, the hired professional may also be eligible to participate in an annual discretionary incentive program, the award of which will be dependent on various factors, including, without limitation, individual and organizational performance.
- Location & working pattern
New York, NY
Working pattern and location restrictions need checking in the full posting.
- Work authorization
No clear work-authorization passage found. Eligibility is unconfirmed.
- Status in our records
- Active
- First seen by us
- Sep 16, 2026
- Recorded sightings
- 7
- Last seen by us
- Oct 7, 2026
- Employer says posted
- Sep 10, 2026
These dates show when we found the listing. Check the employer’s website to confirm it is still accepting applications.
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