Data Engineer

About the role

This Data Engineer position focuses on building and maintaining the data infrastructure that supports TradingView's financial analysis tools. The work includes optimizing SQL queries for data marts, developing and evolving Airflow DAGs, and migrating existing data marts to dbt models. A key aspect of the role is designing, developing, and testing ETL/ELT processes to ensure data integrity and accessibility for millions of users.

The role involves actively participating in architectural decisions for the data platform and running proof-of-concept projects through to production. Success in this position means contributing to a scalable and robust data environment, ensuring that the platform can handle increasing data volumes and user demands. The engineer will document technical solutions and collaborate within a global, distributed team.

The team values product quality and ownership, aiming to build systems used by a global audience. This role is suited for someone who can clearly formulate technical specifications and defend their technical decisions, contributing to the continuous improvement of the data platform. The company offers a hybrid work format and supports learning and career growth.

The salary for this position ranges from $55,000 to $85,000 USD annually.

Skills that matter here

• Python: This role requires strong proficiency in Python, specifically for writing and managing Airflow DAGs.
• SQL: The position demands strong SQL skills, including query optimization and understanding execution plans to improve performance.
• AWS: Experience with AWS is necessary as the data platform infrastructure likely leverages AWS services.
• Apache Airflow: Hands-on experience with Apache Airflow is crucial for maintaining and developing data pipelines.
• dbt: The role involves working with dbt, including developing new models and migrating existing data marts to dbt.
• Linux: A confident understanding of Linux is required for navigating and managing the technical environment.

Who this role suits

• A person with 4-5 years of data engineering experience who enjoys optimizing complex data queries and ETL/ELT processes.
• Someone who takes ownership of their work and is committed to building high-quality, scalable data systems.
• An individual who can clearly articulate technical specifications and defend architectural decisions within a team.
• A professional comfortable with a hybrid work format and collaborating with a distributed global team.

From the employer

• Maintain and develop Airflow DAGs
• Optimize and develop SQL queries for data marts
• Maintain and evolve the data platform infrastructure
• Develop dbt models and migrate existing data marts to dbt
• Design, develop, and test ETL/ELT processes
• Run proof-of-concept projects, present results, and bring them to production
• Participate in architectural decision-making for the data platform
• Document technical parts of delivered solutions

• 4–5 years of experience as a Data Engineer
• Strong proficiency in Python, including writing Airflow DAGs
• Strong SQL skills, including query optimization, reading query execution plans, and improving query performance
• Experience with AWS
• Hands-on experience with Apache Airflow and pipeline design principles
• Experience working with dbt
• Understanding of MPP (Massive Parallel Processing) databases and hands-on experience with systems such as Redshift, Greenplum, or Vertica
• Confident Linux user
• Ability to clearly formulate technical specifications and defend technical decisions
• Skilled at selecting the right technologies for specific tasks

• Flexible working hours and a hybrid work format
• Well-equipped offices for focused and collaborative work
• A global, distributed team of 500+ professionals
• Learning, mentorship, and long-term career growth
• Relocation support and private health insurance
• Performance-based bonuses
• TradingView Premium access
• Regular team events and company-wide meetups