About the Role
As a Senior Data Engineer, you will become part of a cross-functional development team focused on engineering the data experiences of tomorrow. This role is ideal for someone passionate about scalable data systems, eager to solve complex problems, and ready to work in a dynamic environment.
Responsibilities
- Build and prototype scalable data pipelines to handle increasing data volume and complexity.
- Develop and maintain API integrations for efficient data ingestion and transformation.
- Write reusable, testable, and efficient Python code for data integration tasks.
- Use SQL and Python to extract insights from data in collaboration with business stakeholders.
- Manage multiple concurrent projects, adapting to shifting priorities in a fast-paced setting.
- Solve complex challenges creatively to continuously improve data strategies and systems.
- Contribute to the design, codebase, configurations, and documentation for components handling data ingestion, real-time streaming, batch processing, ETL, and storage.
- Continuously enhance engineering infrastructure by identifying gaps and improving platform robustness, maintainability, and speed.
- Collaborate with engineering teams to ensure that solutions meet customer expectations in functionality, performance, scalability, and reliability.
- Take end-to-end responsibility, contributing across development, QA, and DevOps roles.
- Partner with business analysts and data scientists to understand their use cases and support them effectively.
- Participate in unit activities and community-building initiatives, contribute to conferences, and promote best practices.
- Support sales efforts by participating in customer meetings and providing technical insights on digital services.
- Demonstrate understanding and hands-on application of cloud infrastructure design and implementation.
Requirements
- Proven experience as a Data Engineer or in a similar role with a focus on data integration and management.
- Strong programming skills in Python, particularly in API interactions and automation.
- Solid foundation in SQL and relational database design.
- Strong algorithmic thinking and problem-solving skills.
- Effective communication and collaboration abilities in a team environment.
- Hands-on experience with designing and maintaining data ingestion, transformation, and loading pipelines across various storage systems.
- Exposure to data streaming tools and batch processing frameworks.
- Ability to troubleshoot and improve engineering infrastructure and deployment environments.
- End-to-end ownership mindset, including development, testing, and DevOps.
- Experience working with stakeholders across business and technical functions.
- Active contribution to team knowledge sharing, technical community engagement, and continuous learning.
- Understanding of cloud infrastructure and its components (e.g., storage, compute, networking).
Desirable
- Experience with cloud platforms such as AWS, Google Cloud Platform, or Azure.
- Familiarity with data warehousing and ETL techniques.
- Proficiency with version control systems like Git.
