Tech Stack
AirflowAmazon RedshiftApacheAWSDockerETLGrafanaGreenplumLinuxPostgresPrometheusPythonSQL
About the role
- 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
- Work with a high degree of autonomy and independence and collaborate closely with colleagues, analysts, ML engineers, and developers
Requirements
- 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
- Nice to have: Experience with monitoring systems (Prometheus + Grafana, Zabbix)
- Nice to have: Experience with Postgres, ClickHouse
- Nice to have: Experience with Apache NiFi
- Nice to have: Experience building and maintaining Docker containers