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Intercontinental Exchange

Runs exchanges, data and mortgage technology

Senior Data Engineer

Data EngineeringPosted on Nov 11
Full-timeNew York, NY, USA$145k - $185kIn-person

About the Job

Requirements

  • A bachelor's degree in computer science, data science, finance, or mathematics, or equivalent experience.
  • At least 5 years of professional software development experience.
  • Strong programming skills in Python, including commonly used data science libraries such as pandas, NumPy, and PySpark.
  • Strong SQL skills, including query tuning and query plan management.
  • Experience working in cloud environments such as AWS.
  • Experience with cloud data platforms and warehouses such as Snowflake, Databricks, BigQuery, or Redshift.
  • Experience applying statistical analysis and modeling to financial market data, or familiarity with market structure, trading data, or regulatory compliance analytics.
  • Experience writing complex programs and implementing custom algorithms, including adapting open-source frameworks to specific needs.
  • Proficiency with Git and experience working in Agile teams of 5 to 8 engineers.
  • Written and verbal communication skills sufficient to explain complex solutions to stakeholders in different disciplines.

Responsibilities

  • Design, write, and optimize SQL to develop and maintain data science and analytics solutions in partnership with business teams.
  • Build frameworks and tools that automate data collection.
  • Convert data formats to support analysis and maintain the databases and data systems behind it.
  • Optimize SQL queries and review query plans to improve performance.
  • Search large data sets for meaningful patterns and apply statistical methods to interpret trends and support diagnosis and prediction.
  • Create reports and presentations for business stakeholders.
  • Analyze requirements and propose technical solutions that balance cost, time, and quality.
  • Collaborate with project managers to break deliverables into tasks and provide realistic estimates.
  • Develop and unit test code following software development best practices.
  • Collaborate with developers and quality assurance engineers on integration, functional, and regression testing.
  • Collaborate with business and operations teams to resolve design and operational challenges.
  • Prototype new algorithms and machine learning, artificial intelligence, natural language processing, and large language model solutions for quantitative analysis and market monitoring to improve automation, insight, and decision-making.
  • Continuously improve system performance and propose better approaches.

Desired Qualifications

  • Experience with other languages used in data and quantitative work, such as Java, Scala, R, or Julia.
  • Experience with Spark SQL and Parquet.
  • Experience with time series databases and engines such as Deephaven, kdb+, InfluxDB, or TimescaleDB.
  • Experience with data visualization and analytics tools such as Tableau, Power BI, or Alteryx.
  • Scripting experience in bash or AWK.
  • Experience in data management, analytics middleware, or platform infrastructure.
  • Experience in an applied research and development or innovation lab setting.

About the Company

Intercontinental Exchange

Runs exchanges, data and mortgage technology

Intercontinental Exchange runs financial marketplaces, clearing houses and data services for banks, investors and businesses that trade or finance assets. Its New York Stock Exchange lets companies raise capital and gives investors a place to buy and sell listed shares. ICE also sells market pricing and analytics, while its mortgage software supports lenders from loan applications through closing and servicing. Trading fees, listing fees and subscriptions pay for these services, and clearing houses manage the risk that one side of a trade fails to pay. Founded in 2000 to digitize energy trading, Intercontinental Exchange is headquartered in Atlanta, Georgia.

Company size
10,001+
Company stage
IPO
Headquarters
Atlanta, GA
Founded
2000

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