Job Description Job Purpose ICE Data Services (an Intercontinental Exchange company) is seeking strong candidates to join its Spatial Intelligence team
This hire will be an immediate contributor to an ambitious roadmap in US mortgage and real estate data
We re looking for someone who is highly motivated; capable of cleaning, modeling, and extracting value from datasets in new content areas; and excited to support prototyping, early commercialization, and go-to-market efforts in novel product categories
Responsibilities
You will collaborate with engineers, subject matter experts, and customers in the full-stack implementation of data products for mortgage capital markets applications
You will touch every part of the product development process
You will pitch in on exploratory analysis of our data inputs, help lead data modeling and management for internal platforms, and shape end products for our customers
You will take a substantial role in early prototyping and implementation of these products
The principal product focus will be in US mortgage and real estate markets
You should be comfortable wading into messy geospatial datasets, and bring some existing expertise on how mortgage and/or residential real estate markets work
You will need to build a deep understanding of our sources upstream generation processes to evaluate data quality, accuracy, and feature representations
You will help define and maintain derived data layers that support a collection of related analytics products
This roadmap will be built up on a common platform of core data assets and technologies, where the efficient ordering of data acquisition, data integration, and product iteration will be critical to keeping outputs maintainable with a lean team
Every member of the team shares in QA and testing responsibilities, across all levels of the data warehouse and analytical workflows
You will identify key failure points in these workflows and think about tests and strategies to mitigate them
You will learn every unique way that a source dataset might mangle a ZIP code (and why it matters for product integrity)
Knowledge and Experience Candidates should have experience in the following areas, with demonstrably deep expertise in a few: Experience analyzing US mortgage and residential real estate data
We care about the combination of subject-matter knowledge and clear understanding of the privacy and security requirements involved
Strong exploratory data analysis skills in SQL and at least one of R, Python, or JavaScript
Familiarity with databases and analytical tools that use SQL as a data manipulation language (especially Google BigQuery)
It will be helpful to have working knowledge of DBT (Data Build Tool) or similar SQL templating systems, as well as DAG orchestration tools like Airflow
Experience with projecting, measuring, and controlling cloud computing costs for product workflows is important
Designing products with cost considerations in mind is crucial because of the size and complexity of our product data pipelines
How to collaborate with engineering teams across the lifecycle of product ideation, prototyping, and productionizing
Some prior experience as a software/data engineer or machine learning engineer is strongly preferred
You must be comfortable using git version control in a collaborative working environment
Building your own ETL pipelines will not be a routine responsibility, but be ready to roll up your sleeves in a pinch
Critical thinking about ETL requirements for time series data and backtesting requirements (what did we know, when, and can we reproduce that state of knowledge) is an important skill
Some prior experience with data visualization and statistical or ML modeling will help you succeed
If you do not have experience, you should be excited to learn this on the job
Candidates should have excellent written and verbal communication skills to collaborate effectively with in-person and remote technical colleagues, business stakeholders, and client end-users
Schedule This role offers work from home flexibility of one day per week