Data Engineer
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What you'll do
•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
What makes you the perfect fit
•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
Nice to have
•Experience with Lakehouse architecture using Parquet, AWS Athena, and other AWS technologies
•Experience with monitoring systems (Prometheus + Grafana, Zabbix)
•Experience with Postgres, ClickHouse
•Experience with Apache NiFi
•Experience building and maintaining Docker containers
What we offer you
•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
Team description
The Data Engineering team is the foundation on which the entire company operates. We build scalable infrastructure that transforms massive volumes of information into clear and trustworthy insights. The role assumes a high degree of autonomy and independence, while also requiring close collaboration with colleagues, analysts, ML engineers, and developers.
Who you are
Not explicitly listed as a separate section beyond qualifications, but includes: 4–5 years of Data Engineer experience, strong Python and SQL skills, AWS and Airflow experience, dbt experience, knowledge of MPP databases, Linux proficiency, and strong technical communication skills.