Middle Databricks Developer with Azure (Data Platform)
Контакты
Формат работы
remote (только Europe)
Тип работы
fulltime
Грейд
middle/senior
Английский
b2
Страна
Serbia/Ukraine/Poland +4 еще
pythonsqldata engineeringazuresparkdatabricksazure data factorypysparkdelta lakelakehouse architecture
Вакансия из Hirify RU Global, списка компаний с восточно-европейскими корнями Для мэтча и отклика нужен Plus
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Роль четко сфокусирована на инженерии данных в Azure и опирается на востребованный современный стек, но в аутсорсинге продолжительность проекта может зависеть от потребностей клиента.
Аутсорсинговый проект
Современный стек
Понятные задачи
Мэтч & Сопровод
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Текст:
Hirify AI/Оригинал
TL;DR
Middle Databricks Developer with Azure (Data Platform): Building scalable cloud data platforms and reliable pipelines in the Microsoft Azure ecosystem with an accent on Databricks, Spark, PySpark, and Lakehouse architecture. Focus on designing end-to-end ETL/ELT workflows, optimizing Spark workloads, integrating diverse data sources, and ensuring data quality, governance, security, and monitoring.
Location: Remote from Bulgaria, Cyprus, Latvia, Poland, Romania, Serbia, or Ukraine; listed locations include Belgrade, Cluj-Napoca, Dnipro, Kharkiv, Krakow, Kyiv, Larnaca, Lodz, Lublin, Lviv, Odesa, Riga, Sofia, Varna, Warsaw, Wroclaw, and remote options in Bulgaria and Poland.
Company
hirify.global is delivering a cloud-based data engineering project for a London-based international private equity investor.
What you will do
Design data solutions and scalable data platforms using Databricks, Spark, and Azure services.
Develop pipelines and ETL/ELT workflows for structured and unstructured data.
Build Lakehouse architectures with Delta Lake and integrate databases, APIs, cloud services, and streaming platforms.
Develop and optimize high-performance PySpark and Spark SQL solutions for scalability and cost efficiency.
Ensure data quality, governance, security, and monitoring standards.
Collaborate with data engineers, architects, analytics teams, business stakeholders, and the client’s technical team; participate in architecture, technical decisions, CI/CD, and infrastructure automation.
Requirements
4+ years of experience in Data Engineering, including 3+ years of hands-on experience with Azure Databricks.
Experience with Apache Spark and PySpark.
Knowledge of Python and SQL.
Experience with Azure Data Factory and Azure Data Lake Storage Gen2.
Experience with Delta Lake, Lakehouse architecture, and end-to-end data pipelines in Azure.
Understanding of data modeling principles and best practices.
Experience working with large-scale datasets in cloud environments.
Experience with Git-based version control systems.
Upper Intermediate or higher English level required.
Nice to have
Experience optimizing Spark workloads.
Experience collaborating with cross-functional technical and business teams.
Experience supporting CI/CD processes and infrastructure automation.
Culture & Benefits
Remote work is available from the listed countries and locations.
Small project team of 8 people working with a client-side technical team of more than 20 specialists.
SCRUM-based workflow with weekly sprints.
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