Description:
The Team: Our team is responsible for the design, architecture, and development of data products using a variety of tools that are regularly updated as modern technologies emerge. Every day you will have the opportunity to work with people from a wide variety of backgrounds and will be able to develop a close team dynamic with coworkers from around the globe.
Responsibilities And Impact
- Implement robust software components for data-driven systems, ensuring efficiency and maintainability.
- Conduct technical analysis and articulate solutions, designing engineering patterns that can be leveraged across multiple product offerings with a high volume of end-users.
- Optimize and enhance existing solutions, proactively identifying and resolving complex technical challenges while weighing trade-offs in cost, performance, and scalability.
- Develop reusable components and services, adhering to corporate engineering standards, best practices, and modern development frameworks.
- Apply software engineering best practices, leveraging automation in testing, deployment, and monitoring to ensure reliable and efficient solution delivery.
- Collaborate cross-functionally with technical and non-technical stakeholders, effectively communicating complex concepts through documentation, diagrams, and code comments.
What We’re Looking For
Basic Required Qualifications:
- Bachelor's or master's degree in computer science, Information Systems, or a related field.
- 5+ years of hands-on experience in backend development, building scalable and high-performance systems using C# / .NET Core
- Advanced SQL programming skills with experience in database performance tuning for large datasets.
- Proficiency in relational database management systems (MS SQL, PostgreSQL, or similar).
- Exposure to Big Data technologies such as Hadoop, Databricks, Spark/Scala, Nifi.
- Understanding of cloud computing environments such as AWS, Azure, or GCP.
- Working knowledge of Docker and containerized deployments.
- Familiarity with large-scale messaging systems like Kafka, RabbitMQ, or commercial equivalents.