Data Engineering Intern

Summary

Quanvers is seeking a Data Engineering Intern to join their data engineering team. In this role, you will help build data infrastructure for systematic trading strategies, working on data pipelines and collaborating with researchers and software engineers.

Responsibilities

• Build and maintain data pipelines for ingesting market data from multiple sources (exchanges, data vendors, alternative data providers)
• Implement data quality checks and monitoring systems to ensure data integrity
• Work with time-series databases and data warehouses to optimize storage and retrieval
• Develop ETL processes for cleaning, transforming, and aggregating financial data
• Create tools and APIs for researchers to access and query data efficiently
• Assist in migrating legacy data systems to modern cloud infrastructure
• Document data schemas, pipelines, and best practices for the team

Skills

• Currently pursuing a Bachelor's or Master's degree in Computer Science, Data Science, Information Systems, or related technical field
• Proficiency in Python and SQL
• Understanding of data structures, algorithms, and software engineering fundamentals
• Experience working with databases (PostgreSQL, MySQL, or similar)
• Familiarity with data processing libraries (Pandas, NumPy) and data workflows
• Strong problem-solving skills and attention to detail
• Ability to write clean, maintainable, and well-documented code
• Experience with distributed systems or stream processing frameworks (Kafka, Spark, Flink)
• Knowledge of time-series databases (InfluxDB, TimescaleDB, KDB+)
• Familiarity with cloud platforms (AWS, GCP, Azure) and infrastructure as code
• Experience with containerization (Docker) and orchestration (Kubernetes)
• Understanding of API design and microservices architecture
• Prior exposure to financial data or trading systems
• Experience with monitoring and observability tools (Prometheus, Grafana)

Qualifications

Must Haves

• Currently pursuing a Bachelor's or Master's degree in Computer Science, Data Science, Information Systems, or related technical field
• Proficiency in Python and SQL
• Understanding of data structures, algorithms, and software engineering fundamentals
• Experience working with databases (PostgreSQL, MySQL, or similar)
• Familiarity with data processing libraries (Pandas, NumPy) and data workflows
• Strong problem-solving skills and attention to detail
• Ability to write clean, maintainable, and well-documented code

Nice to Haves

• Experience with distributed systems or stream processing frameworks (Kafka, Spark, Flink)
• Knowledge of time-series databases (InfluxDB, TimescaleDB, KDB+)
• Familiarity with cloud platforms (AWS, GCP, Azure) and infrastructure as code
• Experience with containerization (Docker) and orchestration (Kubernetes)
• Understanding of API design and microservices architecture
• Prior exposure to financial data or trading systems
• Experience with monitoring and observability tools (Prometheus, Grafana)