4 days ago
New York, NY, USAMid Level
Base Salary
$125k - $139k/yr
Responsibilities
- Maintain the merchant data configuration layer, including automated tagging, transformation, and filtering.
- Develop tailored technical and data solutions for onboarding merchants and assess merchant websites, business models, and data flows.
- Create JSON and CSV templates to guide merchant developers and data teams in building API and file-transfer integrations.
- Write queries and scripts using Python, SQL, Spark, Databricks, or R to test, validate, and identify data issues in sandbox and production environments.
- Transform and upload large historical data files to Riskified APIs and perform data wrangling and sanitization.
- Monitor automated data alerts and communicate merchant data issues and irregularities to internal and external stakeholders.
- Collaborate with analysts, research, data science, client-facing teams, R&D, product management, integrations engineering, account management, and sales.
- Identify and research recurring data issues and propose system-wide solutions.
Requirements
- 4+ years of experience in a data-centric industry role such as analytics, data engineering, ETL, database administration, or consulting.
- Solid expertise with SQL or NoSQL databases.
- Experience with data wrangling and data processing using Python or R.
- Experience optimizing technical processes.
- Strong analytical, communication, and attention-to-detail skills.
- Preferred experience designing, constructing, and maintaining efficient data pipelines using dbt or Python.
- Must be currently authorized to work full-time in the United States without employer visa sponsorship.
Benefits
- Hybrid remote and in-office work arrangement for NYC team members.
- Fully covered medical, dental, and vision insurance from the first day.
- Equity, 401(k) with matching, and commuter benefits.
- Catered lunch, stocked kitchen, team events, wellness activities, and employee celebrations.
- Professional development programs, global onboarding, skills-based courses, Udemy access, and lunch-and-learns.
Tech Stack
Categories
Data Engineering
