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Привет! Это команда Возвраты ML. Мы ищем талантливого Data Scientist/ML Engineer в новую ML-команду отдела «Возвраты маркетплейса». Отдел занимается обработкой и модерацией возвратов покупателя и продавца, аннуляциями,…
Обязанности: Разработка и поддержка ETL/ELT-процессов, пайплайнов и витрин данных. Интеграция разнородных источников: ERP, MES, PMIS, Excel, внешние системы. Работа с Apache Airflow, Spark, Kafka; при необходимости —…
Data Engineer at SIXT building and maintaining the central Data Platform and Data Catalogue (SIXT Data Shop), processing tens of millions of daily events using AWS (Redshift, S3, Glue, Lambda), dbt, Apache Airflow, Python, and SQL.
Data engineer at Sberbank designing data marts, building and optimizing ETL processes in a DWH, and setting up data quality monitoring—using Python, SQL, Airflow, Spark, Kafka, and PostgreSQL.
Senior Data Science Engineer at dunnhumby in Gurgaon automates Python/PySpark workflows, builds AI-driven data pipelines, and deploys scalable solutions using cloud and orchestration tools.
Principal engineer owning the architecture of Apple's data platform in China, designing and operating large-scale distributed systems that power data, analytics, and AI workloads while meeting regional regulatory and data residency requirements.
Xebia is seeking a Mid/Senior Data Engineer to build scalable data solutions on AWS for international clients. The role requires expertise in Python, SQL, dbt, and Apache Airflow to manage production-scale data pipelines and warehouses.
Чем предстоит заниматься: Контроль и обеспечение валидности транспортных метрик Формирование и визуализация операционных метрик по транспортному блоку Построение дашбордов (Power BI, Tableau, Superset) для…
The Data Engineer will build and refine data pipeline architectures to optimize logistics and fulfillment operations at Tesco. The role involves working with technologies like Apache Spark, Airflow, and various data lakehouse tools to support cross-functional analytics teams.
Build and maintain scalable data pipelines and ML workflows on GCP, deploying models from notebooks to production using orchestration tools like Airflow.
The Forward-Deployed Data Scientist designs and builds end-to-end machine learning solutions for clients, managing the full ML pipeline from data transformation to model deployment. This role involves direct customer collaboration to drive business value and partnering with product teams to advance reinforcement learning algorithms.
Leads architecture and long-term strategy for Coupang’s core eCommerce backend platform, designing scalable, secure systems for global markets while mentoring engineers and enforcing technical standards.
The Data Engineer will join the Preventimmo team to build a robust, scalable data platform by developing and industrializing data pipelines. The role involves working with Python, SQL, AWS, and orchestration tools like Airflow to transform complex data into reliable, actionable insights.
Lead a team of ~10 data platform engineers to build scalable data infrastructure for AI research and production, using Spark, Flink, Airflow, Kafka, and lakehouse formats like Iceberg.
Analyst-developer on VK's search team, designing data marts, running A/B tests, and building metrics using Python, SQL, and YTsaurus (Hadoop) on-prem.
Стажер Data Engineer будет разрабатывать ETL-процессы и поддерживать пайплайны для системы динамического ценообразования, используя Python, PySpark, Hadoop и Airflow.
Lead the enterprise-scale Customer Data Platform at MTS, managing data architecture, engineering processes (Hadoop, Spark, Kafka, Airflow), data governance, and SLA for batch/streaming delivery to thousands of data consumers.
Builds and deploys end-to-end ML/GenAI solutions for financial services clients, including data pipelines, model training, GenAI workflows, and production monitoring in regulated environments.
Build and lead the next-generation e-commerce backend platform handling millions of user requests daily using Java/Kotlin, microservices, and cloud-native tools like Kubernetes and AWS.
Designs and builds large-scale data pipelines in Scala, Spark, and Java to process 80–90 million records daily for financial services clients.
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