- Own the integrity, validation, and reliability of data pipelines powering the product
- Design and execute data quality assurance and validation frameworks
- Collaborate across the organization to implement new features, support internal stakeholders, and improve data infrastructure
- Partner with the Senior Engineer, Quantitative Modeler, and Solutions Architect to validate data feeding the product and financial models and ensure launch readiness
- Participate in stand-ups and milestone meetings
- Serve as the data quality checkpoint between vendor data ingestion and product delivery
- Establish post-launch data quality monitoring and documentation
- Surface data quality risks and vendor issues to the Director of Engineering
- Manage external data vendor relationships and ongoing data quality validation
Requirements
- Python coding for production systems using modular code rather than Jupyter notebooks
- Git workflow and collaborative code review
- Docker images and container build tooling
- Data validation and verification pipeline design, including automated testing
- Data quality assessment and solution feasibility analysis
- Data exploration and engineering tools, including pandas and SQL
- DAG-based ETL orchestration using Prefect or similar
- AWS, especially S3
- 3+ years of experience in data engineering, data quality, or analytics engineering roles
- Bachelor's degree in computer science, statistics, or a related field; equivalent practical experience also considered
- Experience managing or coordinating with external data vendors, including data quality troubleshooting
- Experience working in a fast-paced, cross-functional environment, ideally supporting a product launch or similar high-stakes delivery
- Experience partnering with quantitative or financial roles, such as financial modeling or data science, or experience in climate tech strongly considered
- Must be authorized to work in the US
Core Competencies
Demonstrates expertise in data pipeline integrity, validation, and quality assurance, with a strong focus on Python coding, data engineering tools, and collaboration across cross-functional teams. Proven ability to manage external data vendor relationships and ensure data quality throughout the product lifecycle.
Highest-signal resume keywords
- Python Coding for Production Systems
- Data Validation and Verification Pipeline Design
- DAG-Based ETL Orchestration Using Prefect
- AWS, Especially S3
- Data Quality Assessment and Solution Feasibility Analysis
Hard Skills
- Data Quality Assurance
- Data Pipeline Design
- Automated Testing
- Data Exploration Tools
- SQL
- Pandas
- Git Workflow
- Docker
- Data Quality Troubleshooting
- Data Engineering
Soft Skills
- Collaboration
- Communication
- Problem-Solving
- Cross-Functional Teamwork
- Stakeholder Support
Industry Keywords
- Data Engineering
- Analytics Engineering
- Financial Modeling
- Climate Tech
- Vendor Management
Tools & Technologies
- Prefect
- Docker Images
- Container Build Tooling
- Data Quality Monitoring
- Data Documentation
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Data Quality Engineer Arbeitgeber: Jobtailor
Als Front Office Supervisor in unserem dynamischen Team bieten wir Ihnen die Möglichkeit, in einem unterstützenden und freundlichen Arbeitsumfeld zu wachsen. Wir legen großen Wert auf die berufliche Entwicklung unserer Mitarbeiter und bieten regelmäßige Schulungen sowie die Chance, Verantwortung zu übernehmen. Unsere Lage ermöglicht es Ihnen, Teil einer lebendigen Gemeinschaft zu sein, während Sie gleichzeitig die Standards unseres Franchise-Partners einhalten und unseren Gästen einen unvergesslichen Aufenthalt bieten.
