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The Azure Databricks Data Engineering Lead will design and manage large-scale data pipelines and infrastructure using Azure, Databricks, PySpark, and Python. The role involves leading cross-functional teams, defining data governance policies, and building automation frameworks to support business analytics.
Senior Python developer builds and optimizes enterprise-grade financial automation systems, integrating trading platforms and market data while ensuring regulatory compliance.
Develops AI-powered audience analytics and media intelligence solutions using real-time data; builds production ML/PySpark pipelines on Databricks with MLOps best practices.
Build and deploy ML models for risk and intelligence products at scale, focusing on fraud detection and network analysis using Python, TensorFlow/PyTorch, and BigQuery.
Lead the delivery of multiple AI and Data Engineering engagements — managing pods, reviewing architectures, and engaging clients — with deep hands-on knowledge of LLMs, RAG, Agentic AI, data pipelines, and cloud platforms.
Чем предстоит заниматься: Внедрение моделей машинного обучения; Сопровождение полного цикла сборки модели; Обработка и анализ данных; Поддержание коммуникаций с разработчиками моделей; Проработка архитектуры моделей;…
Senior Data Engineer to design, build, and optimize enterprise scale data platforms using Databricks, Python, and PySpark. This role focuses on developing high-performance batch and real-time data pipelines, implementing modern data engineering frameworks, and delivering reliable, governed data solutions.
Data Analyst in SberAds builds and maintains compliant, high-quality data pipelines between the ad platform, Sber, and ecosystem services, using SQL, Python, and Spark to ensure clean, reliable data flows.
Зарплата: до 300000 RUR (на руки) Ищем Middle+/Senior Data Scientist. Команда специализируется на разработке моделей машинного обучения для сегмента физических лиц и предоставлении модельных сервисов для…
A Data Engineer at VTB Bank responsible for evaluating model risk and validating models, focusing on data quality analysis, data warehouse preparation, automation of validation processes, and working on data lakes and MLOps, using SQL, PySpark, and Python.
до 520к gross (до ~452к net) Внедрять модели машинного обучения Сопровождать полный цикл сборки модели Обрабатывать и анализировать данные Поддерживать коммуникацию с разработчиками моделей Прорабатывать архитектуру…
Lead a distributed data engineering team managing client implementations and ETL workflows for healthcare data using Python, PySpark, AWS, and Snowflake.
Python/ETL Developer building and maintaining scalable batch and real-time data pipelines for enterprise financial services applications, using Python, PySpark, Apache Airflow, DBT, and SQL.
Lead Data Scientist developing and refining data processing pipelines and analytical methodologies using Python and PySpark on large datasets at a consumer intelligence company.
Designs, builds, and operates scalable data platforms/ETL pipelines for analytics and AI, working in hybrid/cloud environments (GCC/MCC) using PySpark, Spark SQL, Talend, and supporting GenAI/LLM workloads.
Lead Data Engineer responsible for designing, developing, and managing modern data platforms using Microsoft Fabric. The role involves building ETL/ELT pipelines, implementing Lakehouse structures, ensuring data governance, and mentoring junior engineers.
MS Fabric Architect responsible for strategic solution architecting, data architecture design, and migration of enterprise data environments to Microsoft Fabric. Core technologies include MS Fabric, SQL, Python, and PySpark for large-scale data processing and integration.
A Fabric Solution Architect designs, implements, and governs end-to-end data and analytics solutions using Microsoft Fabric. This role bridges business requirements with technical architecture, ensuring scalable, secure, and high-performing data platforms leveraging Fabric components such as Lakehouse, Data Warehouse, Data Engineering, Data Science, Real-Time Intelligence, and Power BI.
Designs and maintains scalable data pipelines and ETL processes using PySpark, SQL, and Python, with a focus on Azure Databricks for large-scale data processing and ensuring data quality and performance.
Design and scale enterprise-grade Databricks Lakehouse platforms using Spark, Delta Lake, and cloud ecosystems. Drive architecture strategy and data modernization initiatives.
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