Junior Data Engineer at OneMarketData focusing on data quality and integrity in financial datasets. Collaborating with senior analysts and assisting in data management and analysis tasks.
About the role
- Staff Data Engineer at URBN developing AI-powered digital experiences by integrating algorithmic solutions with creative tools. Collaborating with cross-functional teams for impactful product evolution.
Responsibilities
- Collaborate with cross-functional teams to integrate AI solutions into digital products and workflows, partnering with engineers to translate prototypes into scalable features and services.
- Guide data exploration and feature engineering to support high-performing models.
- Analyze large-scale data sets to generate actionable insights and recommendations.
- Lead the technical evaluation of external AI/ML tools and vendors, influencing decisions for the technology stack.
- Conduct exploratory proof-of-concept studies to assess potential deployment architectures and evaluate new data engineering technologies.
- Propose, promote, and facilitate paved paths for algorithm integration and productization, laying foundations for feedback loops and data flywheels.
- Identify and execute opportunities to create leverage for scaling algorithm impact, managing algorithm dependencies, and expanding algorithm distribution.
- Collaborate with the team to implement and maintain the ML architecture, including data pipelines and applications that enable training and inference of ML models in production.
- Identify and execute opportunities to scale algorithm impact, manage algorithm dependencies, and expand algorithm distribution.
- Contribute to end-to-end algorithm projects across different domains
- Collaborate with the team to implement and maintain automated monitoring of deployed models to assess their performance, uptime, etc
- Foster strong cross-functional partnerships
- Champion best practices in full-stack algorithm engineering
Requirements
- Strong coding skills and software development experience.
- Proficiency in Python is required.
- Strong SQL skills - ability to both read and construct complex queries; ability to test complex queries for correctness
- Analytics skills - ability to understand requirements and translate them into solutions; ability to express the meaningful inputs and outputs, and foresee the nuances that make something more complicated than it appears
- Familiarity with dbt - ability to decompose a problem into data models, understanding of key concepts such as building models, data tests, macros, exposures and environments
- Proficiency in Airflow - ability to construct a DAG, understanding of how to divide tasks, ability to unit test and manually test DAGs to demonstrate they work.
- Experience with Cloud platforms (Google Cloud Platform, Amazon Web Services, Microsoft Azure, etc.).
- Proven track record of delivering high-impact, algorithm-driven software systems and solutions.
- Experience deploying machine learning models in production.
- Hands-on experience with large-scale data processing, data engineering, and automation.
- Excellent communicator.
- Comfortable with ambiguity; able to take ownership and thrive with minimal oversight and process.
Benefits
- medical
- dental
- vision
- PTO
- generous employee discounts
- retirement savings and much more!
Job title
Job type
Experience level
Salary
Not specified
Degree requirement
Tech skills
Location requirements
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