3 days ago
Toronto, CanadaMid Level
Responsibilities
- Design, develop, and operate robust real-time and batch data pipelines using Kafka, Spark, and Flink.
- Build and manage complex data workflows with Airflow.
- Implement automated data-quality and validation frameworks using tools such as Monte Carlo and Great Expectations.
- Develop scalable cloud-native data platforms and services with Databricks and AWS.
- Create maintainable data transformation workflows using dbt.
- Own data engineering projects from architecture and design through implementation, testing, deployment, monitoring, and production support.
- Identify technical risks, performance bottlenecks, and scalability challenges and recommend architectural improvements.
- Collaborate with Data Science, Product, Analytics, and Engineering teams on data requirements and technical roadmaps.
- Develop reusable libraries, engineering patterns, documentation, and improvements to data architecture and tooling.
Requirements
- At least 3 years of professional software engineering or data engineering experience focused on data pipelines, distributed systems, or backend services.
- Bachelor’s or master’s degree in Computer Science or a related technical discipline, or equivalent practical experience.
- Strong programming experience with Python, Java, and/or Scala and solid computer science fundamentals.
- Strong understanding of data structures, algorithms, concurrency, and multithreaded programming.
- Hands-on experience building distributed data processing systems with Kafka, Spark, and Flink.
- Experience developing and operating production data workloads with Databricks.
- Experience designing and deploying solutions in AWS or a comparable cloud environment.
- Experience building and managing workflows with Apache Airflow and data transformations with dbt or similar frameworks.
- Familiarity with data observability, quality, and reliability tools such as Monte Carlo and Great Expectations.
- Understanding of distributed-systems architecture, relational databases, data modeling, and NoSQL technologies.
- Strong software engineering fundamentals, including object-oriented design, design patterns, testing, and production support.
- Strong problem-solving, communication, and cross-functional collaboration skills.
- Preferred experience with high-volume, low-latency streaming platforms, reusable libraries and frameworks, distributed-workload optimization, ecommerce or marketplace domains, Agile/Scrum environments, JIRA, MVC architecture, and influencing technical architecture.
Benefits
- Base compensation may include a target bonus, restricted stock units, medical and financial benefits, RRSP eligibility, PTO, and parental leave.
- Benefits participation details are provided if an employee receives an offer.
Tech Stack
Categories
Data Engineering
About TCGplayer
TCGplayer operates an online marketplace and software tools for buying and selling trading card games and related collectibles, serving hobby shops and individual sellers. It generates revenue through marketplace fees, seller subscriptions, and fulfillment programs such as TCGplayer Direct. An eBay subsidiary, the company provides authentication and logistics services that help stores list inventory at scale and reach buyers across the U.S. and internationally.