Data Quality Engineer

Jobtailor; Deutschland; Remote; EUR 70.000 - 110.000; Vollzeit

Zusammenfassung

Jobtailor is seeking a data engineer to own data pipeline integrity and quality validation for our product. You will design QA frameworks, collaborate with cross-functional teams, and validate feeds for product launches and financial models. You will also manage external data vendors and monitor data quality post-launch.

The role is data-centric, requires 3+ years of experience in data engineering or analytics, and emphasizes Python, SQL, and AWS S3 expertise in a fast-paced environment.

Qualifikationen

• Bachelor’s degree or equivalent practical experience in a relevant field.
• 3+ years of experience in data engineering, data quality, or analytics engineering.
• Experience coordinating with external data vendors and data quality troubleshooting.
• Experience working in fast-paced, cross-functional environments.

Aufgaben

• Own integrity, validation, and reliability of data pipelines powering the product.
• Design and implement data quality assurance and validation frameworks.
• Collaborate across the organization to implement features and improve data infrastructure.
• Validate data for product and financial models with senior engineers and architects.
• Establish post-launch data quality monitoring and documentation.
• Manage external data vendor relationships and ongoing data quality validation.

Kenntnisse

Python

Git

Docker

Data validation

Data quality

SQL

Pandas

Prefect

AWS S3

Data exploration

Ausbildung

Bachelor's degree in CS/related field

Tools

Prefect

Docker

AWS S3

Pandas

Jobbeschreibung

• 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