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Data Engineer

Gitmax — Uzbekistan · Posted ~21 hours ago

Senior Full-time

Skills

Data Engineering SQL Python PySpark pandas pyarrow Parquet OLAP databases ETL Airflow Dagster Prefect pipeline monitoring failure recovery idempotent processing OLAP

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Summary ✨ AI‑Generated

Work as an experienced Data Engineer on a large-scale technology initiative in the financial domain. You will operate production data pipelines, investigate failures, support model retraining, prepare operational reporting, and process high volumes of customer and analytical data. Strong SQL and Python skills are essential, along with experience in modern distributed processing, ETL orchestration, OLAP databases, and reliable pipeline design.

Highlights

Experienced data engineering role working with high-volume customer and analytical data, production pipelines, operational reliability, and collaboration across data, machine learning, and infrastructure teams.

Description

We are looking for an experienced Data Engineer to join a large-scale technology project in the financial sector. What you’ll do Run and maintain production data pipelines on a regular basis;Monitor pipeline stability and investigate failures;Support scheduled model retraining processes;Prepare and maintain operational reporting;Work with large volumes of customer and analytical data;Collaborate with Data Engineering, Machine Learning, and DevOps teams. Requirements 4+ years of experience in Data Engineering;Experience working with large volumes of customer data in banking, fintech or telecom (must have); Strong SQL skills, including complex query optimization, window functions, partitioning, and batch processing;Experience with OLAP databases and high-volume data loading;Strong Python skills: PySpark, pandas, pyarrow, Parquet;Experience with multi-stage ETL pipelines, failure recovery, and idempotent processing;Hands-on experience with Airflow, Dagster, Prefect, or similar orchestration tools;Experience integrating external data sources would be a plus. What we offer Opportunity to work on a large-scale financial technology project;Complex technical challenges involving high-load systems and large datasets;Experienced Data Engineering, Machine Learning, and DevOps team;Competitive compensation based on experience and technical expertise. If this sounds relevant, feel free to reach out or apply directly.