Senior Data Engineer

Munkaidő, foglalkoztatás jellege
- Alkalmazotti jogviszony
- Általános munkarend
Elvárt technológiák
- DATABASES SQL PYTHON MACHINE LEARNING APACHE SPARK DEVOPS PANDAS
Elvárások
- Angol középfok
- 5-10 év tapasztalat
- Középiskola

Állás elmentve

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Development and optimization of large-scale data processing workflows using Apache Spark, PySpark, and SQL
Building and enhancing multi-stage ETL pipelines with idempotency and failure recovery
Implementation and configuration of pipeline orchestration using Airflow, Dagster, or Prefect
Working with OLAP databases and optimizing bulk data loading and batch processing
Integration of data from internal and external sources
Supporting the transition of the solution into production including automation, monitoring, and collaboration with ML and DevOps teams

At least 5 years of experience as a Data Engineer
Minimum 3 years of hands-on production experience with Apache Spark and PySpark
At least 2 years of experience working with large volumes of customer data in banking, fintech, or telecommunications
Expert-level SQL skills including optimization of complex analytical queries, window functions, partitioning, and batch processing of large datasets
Strong Python skills and practical experience with pandas, pyarrow, and Parquet
Experience building fault-tolerant multi-stage ETL pipelines including idempotency, failure recovery, and memory consumption control
Hands-on experience with OLAP databases, bulk data loading, and orchestration tools such as Airflow, Dagster, or Prefect

Opportunity to participate in a large-scale technology project in the financial sector
Work with high-load systems and large volumes of data
One-year contract
Office-based work in Uzbekistan
Final offer determined based on interview results, candidate’s experience, and technical expertise
Work within an experienced team of Data Engineering, Machine Learning, and DevOps specialists