Вакансия из Hirify Global, списка международных tech-компаний Для мэтча и отклика нужен Plus
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Чёткая зона ответственности и современный стек Databricks, PySpark и AWS делают вакансию привлекательной, но без зарплаты сложнее оценить условия, а акцент на скорости может означать высокий темп работы.
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Зарплата не указанаВысокий темпСовременный стекПонятная зона ответственностиБюджет на обучение
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Описание вакансии
Текст:
Hirify AI/Оригинал
TL;DR
Senior Data Engineer (Databricks) (Data Engineering): Building and scaling the Databricks data foundation, ETL pipelines, and DataLakehouse for mobile gaming products and marketing data with an accent on reliable near-real-time processing, PySpark transformations, and high-performance data integration. Focus on migrating legacy data products, monitoring complex pipelines, and applying AI-assisted engineering to production systems.
Location: Hamburg, Germany; flexible hybrid model with remote work on Mondays and Fridays and office attendance on Tuesdays, Wednesdays, and Thursdays.
Company
hirify.global operates a rewarded user engagement and acquisition platform for mobile gaming that helps players discover and engage with games.
What you will do
Design, develop, and maintain scalable ETL pipelines on Databricks integrating app, web, and marketing partner data.
Build and manage the Databricks DataLakehouse, including migration of legacy data products.
Implement data transformations and processing logic with Databricks and PySpark.
Monitor, troubleshoot, and optimise nightly and near-real-time data processing and in-house tracking solutions.
Collaborate with product, engineering, and cross-functional teams on data integration and provide Tableau support to analysts.
Evaluate data engineering best practices and emerging technologies.
Requirements
Degree in Computer Science, Engineering, or Information Systems, or bootcamp experience with at least 4 years of professional data engineering experience.
Professional experience designing, implementing, and optimising ETL processes and orchestrating production ETL workflows.
Hands-on experience with Databricks and AWS services such as S3, Kinesis, and Lambda, or similar technologies.
High proficiency in Python, SQL, and PySpark, with the ability to write clean, maintainable, production-ready code.
Use of AI tools in planning and building work.
Excellent problem-solving skills, strong attention to detail, and the ability to work independently and collaboratively.
Fluent English, both verbally and in writing.
Nice to have
Experience with GitLab CI/CD pipelines.
Familiarity with PostgreSQL.
Culture & Benefits
Fast-paced, ownership-driven environment focused on practical results and direct communication.
Collaborative culture based on respect, accountability, and solving problems proactively.
Transport subsidy, learning budget, wellness and gym benefits.
Workation, bi-weekly team lunches, and flexible hybrid work.
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