ZipRecruiter

Log In

2

Part Time Data Engineering Jobs in New York (NOW HIRING)

NEW YORK EDGE, INC

Data Entry Specialist

Brooklyn, NY · On-site

$20 - $25/hr

Schedule: * Part-Time * Up to 20 hours per week while school is in session * Up to 25 hours per ... programming through the use of Data Reporting. * Create systems which serve to keep track of all ...

Envista

Intern - Process Engineering

Mahwah, NJ · On-site

$25/hr

... data collection, process documentation, and continuous improvement activities. You'll provide hands ... Schedule: Full-time during summer; part-time options available during the academic year

NEW YORK EDGE, INC

Data Entry Specialist Bronx

Bronx, NY · On-site

$20 - $25/hr

Schedule: * Part-Time * Up to 20 hours per week while school is in session * Up to 25 hours per ... programming through the use of Data Reporting. * Create systems which serve to keep track of all ...

previous pagenext page

Showing results 21-40

All JobsData Engineering JobsPart Time Data Engineering JobsPart Time Data Engineering Jobs in New York

Part Time Data Engineering information

What is a part time data engineering job?

A part-time data engineering job involves working fewer hours than a full-time position, typically focusing on building and managing data pipelines, organizing data storage, and ensuring data quality for organizations. Part-time data engineers may work on specific projects or provide support to larger teams, often with flexible schedules. They use programming languages and tools like Python, SQL, and cloud platforms to move, transform, and optimize data. This role is ideal for those seeking work-life balance, students, or professionals looking to gain experience or supplement their income.

How does a part time data engineering role typically balance project responsibilities with limited working hours?

In a part-time data engineering position, tasks are often scoped to fit within your available hours, focusing on specific projects or maintenance work rather than broader, ongoing initiatives. You’ll likely collaborate closely with full-time engineers to ensure hand-offs are smooth and that you’re aligned on priorities. Clear communication and proactive time management are essential, as you may need to coordinate across teams or adjust your workload to meet deadlines. Many organizations also provide flexible scheduling and clear documentation practices to help part-time team members stay integrated and productive.

What are the key skills and qualifications needed to thrive as a part time data engineer, and why are they important?

To thrive as a Part Time Data Engineer, you need proficiency in programming languages like Python or SQL, knowledge of database management, and a degree in computer science or a related field. Familiarity with data warehousing tools, ETL processes, and platforms such as AWS, Google Cloud, or Apache Spark is typically required. Strong problem-solving abilities, attention to detail, and effective communication help individuals excel in this flexible role. These skills ensure accurate data pipelines, efficient data processing, and successful collaboration with cross-functional teams, even in a part-time capacity.

What is the difference between Part Time Data Engineering vs Part Time Data Analysis?

AspectPart Time Data EngineeringPart Time Data Analysis
Required CredentialsTypically requires knowledge of SQL, Python, ETL tools, and cloud platformsRequires skills in SQL, Excel, data visualization tools, and basic statistical knowledge
Work EnvironmentOften involves building data pipelines, managing databases, and working with data infrastructureFocuses on interpreting data, creating reports, and providing insights
Employer & Industry UsageUsed in tech companies, finance, and e-commerce for data infrastructure rolesCommon in marketing, consulting, and business intelligence roles across industries

Part Time Data Engineering involves developing and maintaining data pipelines and infrastructure, requiring technical skills in programming and cloud platforms. In contrast, Part Time Data Analysis centers on interpreting data, creating reports, and providing insights, often using visualization tools. Both roles are essential in data-driven organizations but differ in technical complexity and focus.

Are part time data engineers still in demand?

Part-time data engineers are still in demand as organizations seek flexible staffing for data pipeline development, maintenance, and analytics projects. Skills in SQL, Python, cloud platforms, and data tools remain valuable, and remote or flexible roles are increasingly available in the industry.

Can I work remotely as a part time data engineer?

Part time data engineering roles can often be performed remotely, especially when the work involves tasks like data pipeline development, database management, and cloud-based tools. Employers may require familiarity with tools such as SQL, Python, and cloud platforms, and remote work arrangements depend on the company's policies and project needs.

What are the most commonly searched types of Data Engineering jobs in New York?

The most popular types of Data Engineering jobs in New York are:

What are popular job titles related to Part Time Data Engineering jobs in New York?

For Part Time Data Engineering jobs in New York, the most frequently searched job titles are:

What job categories do people searching Part Time Data Engineering jobs in New York look for?

The top searched job categories for Part Time Data Engineering jobs in New York are:

What cities in New York are hiring for Part Time Data Engineering jobs?

Cities in New York with the most Part Time Data Engineering job openings:

Part Time Data Engineering jobs near you
Infographic showing various Part Time Data Engineering job openings in New York as of August 2026, with employment types broken down into 100% Part Time. Highlights an 74% In-person, and 26% Remote job distribution.

GBM - Quantitative Dev/Strat - Systematic Rates Trading, New York

Goldman Sachs

New York, NY • On-site

Full-time, Part-time

Re-posted 28 days ago

Goldman Sachs rating

7.8

Company rating: 7.8 out of 10

Based on 28 frontline employees who took The Breakroom Quiz

88th of 174 rated banks

Job description

Quant Dev/Strat - Systematic Rates Trading

Desk Overview

The Systematic Rates Trading desk sits at the intersection of quantitative research, technology, and market-making execution. The team is responsible for overseeing the systematic trading, pricing, and risk management frameworks for global Rates products (including government bonds, interest rate swaps, and futures). We design, build, and manage real-time pricing engines, algorithmic hedging systems, and execution platforms that operate at scale in highly liquid and volatile markets.

Role Description

This is a high-impact, front-office seat designed for a strong Quantitative Developer / Strat who is a self-driven, highly motivated independent thinker. In this role, you will not just implement pre-defined models; you will actively drive the end-to-end development of trading algorithms, market-making logic, and portfolio optimization tools. 

We are looking for an individual who takes a high amount of ownership over their work, from initial exploratory data analysis to production-grade deployment. You will collaborate closely with traders and quantitative researchers to optimize execution, analyze market microstructure, and build robust, high-performance systems where code quality directly impacts desk P&L.

Responsibilities

  • Algorithm Development: Design, develop, and optimize systematic trading algorithms, market-making logic, and real-time algorithmic hedging systems.
  • Exploratory Data Analysis (EDA): Conduct rigorous data analysis on massive, high-frequency market datasets to identify pricing anomalies, refine trading signals, and improve execution strategies.
  • Market Microstructure & TCA: Analyze Rates market microstructure and build sophisticated Transaction Cost Analysis (TCA) frameworks to minimize slippage, model market impact, and optimize execution performance.
  • Portfolio Optimization: Implement and refine mathematical models for portfolio optimization, risk allocation, and real-time risk management.
  • System Architecture & Performance: Design and maintain the high-performance, low-latency trading infrastructure and data pipelines powering the systematic Rates business.
  • End-to-End Ownership: Proactively identify technical bottlenecks, propose architectural improvements, and take full responsibility for the reliability and scalability of the trading stack.

Who We Look For

We are seeking an exceptional software engineer and quantitative thinker with a "builder" mindset. You should thrive in a fast-paced, collaborative trading floor environment where you are expected to work independently, think critically, and take complete ownership of your projects.

Basic Qualifications

  • Education: Bachelor's, Master's, or PhD in Computer Science, Computer Engineering, Financial Engineering, Mathematics, or a related quantitative field.
  • Core Languages: Expert-level proficiency in C++ or Java (for high-performance, low-latency systems) and Python (for data analysis, prototyping, and scripting).
  • CS Fundamentals: Strong foundation in data structures, algorithms, systems programming, and concurrent/multi-threaded application design.
  • Engineering Best Practices: Deep understanding of the software development lifecycle, including version control (Git), CI/CD pipelines, testing frameworks, and performance profiling.
  • Problem Solving: Exceptional debugging skills and the ability to navigate complex, distributed systems under time-sensitive, live-trading conditions.

Preferred Qualifications

  • Domain Knowledge: Strong understanding of Rates products (Treasuries, Swaps, Futures), yield curve modeling, and fixed-income analytics.
  • Industry Experience: Prior experience working as a Quant Developer, Strat, or Software Engineer on a systematic trading desk, market-making team, or high-frequency trading (HFT) firm.
  • Data Engineering: Experience building and maintaining large-scale time-series databases (e.g., KDB+/q, SQL) and ETL pipelines.
  • Quantitative Skills: Familiarity with statistical modeling, optimization techniques, and machine learning libraries in Python.

Salary Range
The expected base salary for this New York, NY, United States-based position is $150000-$225000. In addition, you may be eligible for a discretionary bonus if you are an active employee as of fiscal year-end.

Benefits
Goldman Sachs is committed to providing our people with valuable and competitive benefits and wellness offerings, as it is a core part of providing a strong overall employee experience. A summary of these offerings, which are generally available to active, non-temporary, full-time and part-time US employees who work at least 20 hours per week, can be found here.

What Goldman Sachs employees say

Pay

Benefits

Hours and flexibility

Workplace

Get the full story on Breakroom

Goldman Sachs logo

About Goldman Sachs

Sourced by ZipRecruiter

At Goldman Sachs, we commit our people, capital and ideas to help our clients, shareholders and the communities we serve to grow. Founded in 1869, we are a leading global investment banking, securities and investment management firm. Headquartered in New York, we maintain offices around the world. We believe who you are makes you better at what you do. We're committed to fostering and advancing diversity and inclusion in our own workplace and beyond by ensuring every individual within our firm has a number of opportunities to grow professionally and personally, from our training and development opportunities and firmwide networks to benefits, wellness and personal finance offerings and mindfulness programs.

Industry

Finance and insurance

Company size

10,000+ Employees

Headquarters location

New York, NY, US

Year founded

1869

View All Goldman Sachs Jobs

Apply