#4 Data Engineer Semi Senior - Feature Engineering - Databricks

Role overview Build and govern reusable data features that support a credit risk scoring model. You’ll work with modeling and platform teams to turn transactional and credit behavior data into reliable, traceable signals, with attention to consistent use in model training and production.

Responsibilities - Design features that capture patterns such as transaction frequency, recency, amounts, digital engagement, and delinquency. - Document features with ownership, lineage, keys, descriptions, tags, lifecycle details, and time context so other teams can reuse them. - Follow the feature deployment process, including validation, schema changes, production release, and job monitoring. - Apply data quality and cost management practices, and help maintain a consistent source of truth for model inputs.

Requirements - Experience in data engineering or feature engineering using Databricks and Unity Catalog. - Advanced SQL and Python skills. - Understanding of data governance, lineage, and data quality practices. - Care with metadata and naming standards, and a mindset oriented toward reuse.

Nice to have - Feature Store certification or experience working with financial data. - Experience building AI agents or agent orchestration systems.

Benefits and work setup The role is described as remote-first. Benefits include covered certifications across several cloud and data platforms, English lessons, additional time off, monthly benefits marketplace credits, referral rewards, a team trip, and childcare reimbursement.