Data Engineer
Our client is building a high-impact, data-driven technology platform used at scale by internal teams worldwide. The Technology organization focuses on creating robust infrastructure, intuitive systems, and reliable data foundations that enable fast, informed decision-making.
As a Data Engineer, you’ll be responsible for designing, building, and maintaining scalable data platforms and pipelines. You’ll collaborate with cross-functional teams to translate complex business and analytical needs into practical, production-ready data solutions. The role combines strong engineering fundamentals with a passion for clean data architecture, automation, and continuous improvement.
You’ll play a key role in shaping data standards, enabling self-service analytics, and ensuring data reliability and transparency across the organization.
Requirements
- Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field (or equivalent practical experience)
- Strong proficiency in Python and SQL
- Experience working in Unix/Linux environments and writing shell scripts
- Solid understanding of agile software development practices (TDD, refactoring, CI/CD, XP)
- Hands-on experience designing, building, and maintaining custom ETL pipelines
- Experience with workflow orchestration tools (e.g. Airflow or similar)
- Strong knowledge of distributed data processing and query engines
Nice to have
- Experience building large-scale infrastructure or platform-level applications
- Ability to write clean, maintainable code in multiple programming languages
- Cloud experience (AWS and/or GCP)
- Hands-on experience with containerization and infrastructure as code
- Familiarity with modern data architectures and data mesh principles
- Experience working with notebook-based data science workflows
- Knowledge of monitoring, logging, and observability tools
Responsibilities
- Design, build, and maintain scalable, reliable data platforms and pipelines
- Streamline end-to-end data workflows and automate data processing tasks
- Collaborate with Product, Engineering, and Data Science teams to deliver practical data solutions
- Define and enforce data standards, documentation, and governance practices
- Maintain and contribute to a centralized data registry and metadata management
- Support and train internal users on data tools, dashboards, and platform capabilities
- Communicate platform updates, improvements, and insights via dashboards, bots, and internal channels
- Plan and execute platform-wide changes, ensuring best practices for development, testing, deployment, and maintenance
- Use data and metrics to guide engineering decisions and continuous improvement
Data Engineer
What will be your next steps?
Quick non-technical conversation
Our initial conversation is a brief, non-technical discussion to understand your background and career aspirations. We're keen to learn about your communication style and how you approach teamwork and decision-making.
60 to 90 minutes technical interview
This in-depth technical assessment, lasting 60 to 90 minutes, is designed to evaluate your specific skills and expertise. We will present you with challenges relevant to our client's requirements.
Client interview
In this stage, you will meet directly with the client for a final technical discussion. This interview will be similar in format to our internal technical assessment, allowing the client to see firsthand how your expertise aligns with their specific project needs and team.
Offer
Congratulations on successfully completing our rigorous evaluation process. We are pleased to extend an offer and recommend you to our clients.