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Data engineer

Berlin
SAIZ
Data Engineer
Inserat online seit: 15 Juni
Beschreibung

Data Engineer (f/m/x)

Location: Berlin, Germany

Company: Innovative AI Startup; B2B SaaS

About Us:

Join our dynamic and rapidly growing B2B SaaS startup, SAIZ, based in the heart of Berlin! Just two years into our journey, we're on a mission to revolutionize the way apparel businesses operate. Powered by advanced analytics and artificial intelligence, we provide cutting-edge software solutions that empower apparel brands to reduce returns, enhance customer satisfaction, and embrace sustainability. Our team thrives on innovation, collaboration, and a startup culture that encourages independence and creativity.

Role Overview:

We are seeking a talented and motivated Data Engineer (f/m/x) to join our team. In this role, you will be instrumental in designing, developing, and maintaining our data infrastructure, ensuring the smooth integration and processing of data. You will work closely with various teams, including data analysts and clients, to support data-driven decision-making and enhance our product offerings. As a team, we plan our tasks on Jira and include them in our sprints. You will have the freedom to develop your own ideas

Key Responsibilities:

* Data Pipeline Development: Design, implement, and maintain efficient data pipelines to facilitate seamless data integration and processing.
* Data Infrastructure: Build and optimize data infrastructure to ensure reliability, scalability, and performance of our data systems.
* Client Collaboration: Work with clients to understand their data requirements and provide technical support for data-related issues.
* Data Management: Ensure data quality, consistency, and security across various data sources and systems.
* Problem Solving: Address and resolve complex data-related challenges, using your technical skills to devise effective solutions.
* Continuous Improvement: Stay updated with the latest industry trends and best practices to enhance our data processes and technologies.

Qualifications:

* Technical Proficiency: Strong skills in Python and SQL are essential. Familiarity with data visualization tools (e.g., Tableau, Power BI), as well as building and maintaining data pipelines for reading, structuring, cleaning, and testing data, is highly desirable.
* Analytical Mindset: A solid understanding of data structures, algorithms, and data modeling.
* Educational Background: Degree in Computer Science, Engineering, or a related field.
* Experience: Previous experience in a data engineering role, particularly in a startup or fast-paced environment, is preferred.
* Independence: Ability to work independently and manage multiple tasks effectively.
* Fast Learner: Eagerness to learn and adapt quickly in a dynamic startup environment.
* Communication Skills: Excellent verbal and written communication skills to collaborate with technical and non-technical stakeholders.

Why Join Us?

* Startup Culture: Be part of an energetic and innovative startup environment.
* Impact: Directly influence our product development and business strategies with your insights.
* Growth Opportunities: Expand your skills and grow with our company as we continue to scale.
* Collaborative Team: Work alongside a passionate and driven team that values creativity and independence.
* The job is full-time and remote

How to apply:

If you are enthusiastic about working in a startup environment and passionate about data engineering, we would love to hear from you! Please apply via the Easy Apply function or email careers@saiz.io, including your resume and answers to a few questions

At SAIZ, we are committed to creating an inclusive and supportive environment where all individuals can thrive. We warmly welcome candidates of all different backgrounds and identities to apply, valuing the unique perspectives each individual brings. Our ongoing dedication is to further diversify our team, enriching our collective experiences and driving innovation.

* Join us in our mission to transform the apparel industry and digitize production in fashion with innovative data-driven solutions

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