Data Engineer

1 Day ago • 5 Years +

Job Summary

Job Description

The Data Engineer role at JetBrains involves developing, maintaining, and enhancing data workloads for internal customers. Responsibilities include designing and implementing data sources and pipelines, maintaining existing pipelines, and implementing testing and monitoring automation. The role requires collaboration with colleagues, participation in projects, and contributions to the company's data processing culture. The ideal candidate will have experience with data processing technologies, data modeling, pipeline optimization, and coding in SQL and Python or Scala. The candidate should also possess strong attention to detail and the ability to independently solve problems within deadlines.

Must have:

5+ years of data processing experience.
Experience with data modeling.
Experience optimizing data pipelines.
Proficient in SQL and Python/Scala.
Experience with data quality and monitoring.
Experience with an orchestration tool.

Good to have:

Experience with cloud service platforms.
Experience with multi-level data quality assurance.
DevOps experience.
Experience with big data processing technologies.
Experience selecting technologies to address business needs.
Experience developing infrastructure for collecting raw data.
Experience with BI tools.

12 skills required

12 skills required for this role

Add these skills to join the top 1% applicants for this job

scala

spark

metabase

python

sql

tableau

hadoop

power-bi

data-analytics

growth-strategy

quality-control

team-management

Job Details

At JetBrains, code is our passion. Ever since we started back in 2000, we have been striving to make the strongest, most effective developer tools on earth. By automating routine checks and corrections, our tools speed up production, freeing developers to grow, discover, and create. The Data Office department is responsible for the data associated with products, AI tools, marketing, financials, sales, and all other domains at JetBrains. Our department provides up-to-date, transparent, and reliable data, as well as data services. As part of our exciting growth strategy, we are seeking experienced, detail-focused, and self-motivated data engineers to develop, maintain, and enhance data workloads for our internal customers.

As part of our team, you will:

Design, implement, and maintain data sources and transformation pipelines that fit the purposes of a diverse set of data consumers.
Maintain and develop the existing data collection and processing pipelines.
Implement test and monitoring automation to ensure reliability, quality, and consistency of data.
Develop and optimize ETL pipelines and SQL queries.
Contribute to the company’s data processing culture.
Continuously engage with other colleagues at JetBrains, including developers, data partners, BI engineers, and data analysts, to collect and clarify business requirements.
Participate in both business-driven and technical projects.

We’ll be happy to have you on our team if you:

Have at least 5 years’ experience with data processing technologies as a data engineer or in an equivalent role.
Have experience working with data modeling to meet a diverse set of requirements.
Have implemented and optimized complex data processing pipelines.
Can write high-quality code in SQL and with at least one programming language, preferably Python or Scala.
Have improved the data quality of sources via data testing and monitoring.
Have worked with an orchestration tool.
Show great attention to detail in your work and can identify small but significant changes in data.
Can independently take over a task, analyze the problem, and deliver solutions within agreed deadlines.
Have a proactive mindset.
Value sharing knowledge and cross-team collaboration.

We’ll be especially thrilled if you have:

Previously worked with cloud service platforms.
Previously developed a multi-level data quality assurance system.
DevOps experience.
Worked with big data processing technologies, such as Spark, MapReduce, and Hadoop.
Experience selecting technologies to address specific business needs.
Previously developed infrastructure for collecting raw data from various sources.
Experience with BI tools, such as Tableau, Power BI, and Metabase.