Rzeszów, Rzeszow, Podkarpackie Voivodeship, Polska
Reply Polska Sp. z o.o.
22. 10. 2024
Informacje o stanowisku
technologies-expected :
Hadoop
Kafka
AWS
Java
Kotlin
Scala
about-project :
You will lead the design and development of advanced data models and scalable data management systems, utilizing big data technologies such as Hadoop, Spark, and Kafka across cloud platforms like AWS, Azure, or Google Cloud. You will manage complex data integration projects, mentor junior engineers, and collaborate with business teams to enhance data accessibility and support data-driven decision-making. Additionally, you will oversee data infrastructure projects, ensuring they meet business goals and industry best practices.
responsibilities :
Architecture Design: Architect and develop advanced data models and database management systems that support scalable, efficient, and robust data operations.
Data Pipeline Management: Design, construct, install, test, and maintain highly scalable data management systems. Ensure systems meet business requirements and industry practices.
Data Integration Leadership: Develop and manage a team to implement complex data projects involving multiple data sources and high volumes of data.
Advanced Analytics Infrastructure: Build infrastructure required for optimal extraction, transformation, and loading of data from a wide variety of data sources using SQL and AWS, Azure, or Google Cloud big data technologies.
Technical Mentoring: Guide and mentor junior data engineers in their roles. Encourage continuous learning and development of the team.
Stakeholder Engagement: Collaborate with business teams to improve data models that feed business intelligence tools, increasing data accessibility and fostering data-driven decision making across the organization.
Project Management: Oversee the timeline and deliverables for data infrastructure projects, ensuring they align with business goals.
Innovation and Strategy: Evaluate new technologies and analytics tools to improve and optimize the performance of data handling and processing.
requirements-expected :
Educational Background: Bachelor’s or master’s degree in CS, Engineering, Data Science, or a related field.
Significant Experience: Proven experience in a data engineering role, with scaling and managing data pipelines.
Expertise in Programming: Proficiency in programming languages such as Java Kotlin or Scala.
Big Data Technologies: Expert knowledge of big data technologies (e.g., Hadoop, Spark, Kafka) and data modeling.
Cloud Platforms: Strong experience with cloud services like AWS, Azure, or Google Cloud, including the design and deployment of scalable cloud-based data systems.
Data Lakes: Knowledge and understanding of Data Lakes building tradeoffs and optimization.
Analytical Skills: Strong ability to analyze data and enhance data quality and efficiency.
Leadership Qualities: Demonstrated leadership skills with the ability to drive projects, mentor teams, and manage stakeholders.
Communication Skills: Excellent communication skills to effectively collaborate with cross-functional teams and explain complex technical details in a clear, understandable manner.
Language: proficient English.
Availability to work in a hybrid mode or remotely with at least 1 visit in the office per quarter.
offered :
Motivizer Benefits Platform to choose and manage all your benefits in one place. You receive a budget (550 PLN monthly). You can choose medical care package, meal tickets, sports cards (we have Multisport and on preferential terms, we have membership cards to one of the most popular Gyms), cinema tickets, shop vouchers, discounts and many more.
Language Courses – youll have access to a multi-language learning platform enabling you to practice you language skills and learn new ones!
Regular and systematic further training opportunities - both internally and from external providers. We support your ongoing learning and development.
Cooperation within an internal community is our everyday reality. We have networking events, coding challenges, and company parties for different occasions.
benefits :
private medical care
sharing the costs of foreign language classes
sharing the costs of professional training & courses