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Mid LevelFull-timePythonAWSData ScienceCI/CDAIML
Salary Range
$102,000 - $138,000 /year
This salary is estimated based on similar roles. The actual salary may vary.
About the Role
We are seeking a Senior Data Engineer to join our Risk Data Team as a hands-on technical lead supporting Credit, Collections, and Fraud. This role blends deep production data engineering with formal technical and people leadership.
Key Responsibilities
- →Serve as technical lead for the Risk Data Engineering team
- →Own architectural decisions and data modeling strategy across the Risk domain
- →Design and build production-grade Snowflake data models
- →Develop scalable dbt projects, including reusable macros and testing frameworks
- →Manage Apache Airflow DAGs, including idempotency, retry logic, and failure handling
- →Implement CI/CD best practices for dbt and data pipelines
- →Design dimensional and relational models aligned to business definitions
- →Apply modeling best practices including grain declaration, SCD strategies, and surrogate key management
- →Own the dbt testing framework (schema tests, custom tests, generic tests)
- →Define and enforce freshness checks, SLA standards, and row-count validations
- →Implement monitoring and observability using DataDog
- →Participate in hiring, onboarding, and team building
- →Run regular 1:1s and provide structured performance feedback
- →Partner with Risk Data Product Managers, Data Science, ML, and business stakeholders
- →Maintain scalable, secure data systems aligned with enterprise governance standards
Requirements
- ✓Bachelor’s or Master’s degree in Computer Science, Engineering, Data Science, or related field (or equivalent work experience)
- ✓8+ years of hands-on data engineering experience
- ✓2+ years of experience serving as a tech lead or leading engineers formally
- ✓Deep expertise in dimensional and relational data modeling, including SCD strategies and grain design
- ✓Advanced dbt experience, including layered architecture, macros, advanced testing, and semantic layer concepts
- ✓Strong hands-on Snowflake experience, including modeling and performance optimization
- ✓Production-level experience managing Apache Airflow DAGs
- ✓Advanced SQL skills, including query optimization and performance tuning
- ✓Strong Python skills for data pipeline development and automation
- ✓Demonstrated ownership of a data quality and monitoring framework
- ✓Experience working in regulated or high-accuracy environments
- ✓Experience participating in hiring, onboarding, and performance management
- ✓Strong communication skills and ability to influence cross-functional stakeholders
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