
Senior Data Engineer
Intercontinental Exchange (ICE)
New York, NYFull-time$145–185K/yrSeen todaySeen in employer's feed today
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Job overview
The New York Stock Exchange seeks a senior developer to build data analytics workflows for trading data. The role covers data ingestion and analysis, applying data science and machine learning to market microstructure, and ownership of delivery from requirements through production support. The successful candidate will work with large-scale trading data on a cloud data stack and collaborate with business, technology, project, development, and QA teams.
Skills & qualifications
Skills
Qualifications
Benefits
Full job description
The New York Stock Exchange is seeking a senior developer to join the team responsible for data analytics workflows for trading data. The successful candidate will be responsible for ingesting and analyzing large volumes of data, collaborating with business and technology teams across NYSE, and applying data science and machine learning to market microstructure. The role carries responsibility for every phase of delivery, from requirements through production support.
The position offers the opportunity to contribute to the data capabilities that support fair and orderly markets. The successful candidate will work with large-scale trading data on a modern cloud data stack, take ownership of work from design through production, and contribute to the application of ML and AI to market analytics.
Responsibilities
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Data engineering and analytics solutions
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Design, write and optimize SQL to develop and maintain data science and analytics solutions in partnership with business teams.
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Build frameworks and tools that automate data collection.
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Convert data formats to support analysis, and maintain the databases and data systems behind it.
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Optimize SQL queries and review query plans to improve performance.
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Analysis and reporting
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Search large data sets for meaningful patterns, and apply statistical methods to interpret trends and support diagnosis and prediction.
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Create reports and presentations for business stakeholders.
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Delivery and collaboration
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Analyze requirements and propose technical solutions that balance cost, time and quality.
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Collaborate with project managers to break deliverables into tasks and provide realistic estimates.
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Develop and unit test code following software development best practices.
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Collaborate with developers and QA engineers on integration, functional and regression testing.
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Collaborate with business and operations teams to resolve design and operational challenges.
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Innovation
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Prototype new algorithms and ML, AI, NLP and LLM solutions for quantitative analysis and market monitoring, with the aim of improving automation, insight and decision-making.
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Continuously improve system performance and propose better approaches.
Knowledge and Experience
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Bachelor's degree in computer science, data science, finance or mathematics, or equivalent experience.
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5+ years of professional software development experience.
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Strong programming skills in Python, including the libraries commonly used for data science (such as pandas, NumPy and PySpark).
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Strong SQL skills, including query tuning and query plan management.
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Experience working in cloud environments such as AWS.
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Experience with cloud data platforms and warehouses, such as Snowflake, Databricks, BigQuery or Redshift.
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Experience applying statistical analysis and modeling to financial market data, or familiarity with market structure, trading data or regulatory compliance analytics.
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Experience writing complex programs and implementing custom algorithms, including adapting open-source frameworks to specific needs.
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Proficiency with Git and experience working in Agile teams of 5 to 8 engineers.
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Demonstrated written and verbal communication skills, with the ability to explain complex solutions to stakeholders in different disciplines.
Preferred qualifications
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Experience with other languages used in data and quantitative work, such as Java, Scala, R or Julia.
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Experience with Spark SQL and Parquet.
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Experience with time series databases and engines, such as Deephaven, kdb+, InfluxDB or TimescaleDB.
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Experience with data visualization and analytics tools such as Tableau, Power BI or Alteryx.
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Scripting experience in bash or AWK.
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Experience in data management, analytics middleware or platform infrastructure.
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Experience in an applied R&D or innovation lab setting.
New York Base Salary Range
The expected base salary for this role, if located in New York, is between $145,000 - 185,000 USD. The base salary range does not include Intercontinental Exchange’s incentive compensation. While we provide this range as general guidance, at ICE we compensate employees based on the skillset and experience of the individual. Regular full-time ICE employees are eligible for a suite of competitive employee benefits, including healthcare coverage (medical, dental and vision), a 401(k) plan, life insurance, time off, and paid leave for qualifying circumstances.
#LI-MA1
Intercontinental Exchange, Inc. is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to legally protected characteristics.
How this job compares
Set against the 2,958 open Data Engineering jobs on Olive Jobs, counted November 12, 2026.
- Pay
- This posting$145–185K/yr
- New York median$141–220K/yr179 salary ranges
- US median$124–212K/yr2,365 salary ranges
This range's midpoint, $165K, is 10% below the New York median midpoint ($183K) — in the middle half of Data Engineering salary ranges in New York.
- Openings
- Olive Jobs lists 233 open Data Engineering jobs in New York and 2,958 across the US. 8% of them nationwide are listed as remote or flexible.
- Experience
- This posting asks for at least 5 years of experience; Data Engineering postings that state a minimum ask for 5 years at the median (2,528 postings).
- Education
- 1,177 of the 2,958 open Data Engineering jobs (40%) ask for a bachelor's degree or higher.
Counted across the open, public US postings on Olive Jobs on November 12, 2026. Pay medians are the middle values of the low ends and of the high ends of postings that list both ends of a range in the same cadence (a yearly salary or an hourly rate); a range's midpoint is halfway between its ends. Pay and experience figures resting on fewer than 20 postings are left out.
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