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Data Engineer at Zoolatech (вакансія неактивна)

Rakuten

Zoolatech Всі вакансії (184)

4.8 ★ Based on
Founded in 2017
Miami, US (4 Locations)
501 to 1000 Employees

Деталі

Дата публікації

February 17, 2026

Локація

Istanbul, Turkey

Кар'єрний рівень

Middle

Освіта

Bachelor

Досвід

1-2 роки


ABOUT THE PROJECT
Our client is a global jewelry manufacturer that is transforming its data and analytics footprint and is also on a journey from IaaS-based Microsoft/QV solutions to Azure PaaS.As a Data Engineer, you will collaborate with product owners, architects, and other key profiles across the global organisation. You will help business verticals and clusters maximize the value of the data and drive business change as a result.Your primary focus will be building and implementing scalable data products on the global data platform together with other smart engineers in the organization.
REQUIREMENTS
– Relevant education within Computer Science, Mathematics, Economics, Information Management, or Statistics
– 3+ years of experience as a Data Engineer or in a Software engineering role with a focus on data
– Proven experience with ADF, Data Lake, Synapse, T/U-SQL, Databricks, MDS, DAX, SSIS, and SQL Server
– Experience with at least one object-oriented or functional/scripting language – Java, Scala, Python, etc.
– DevOps and CI/CD focus
– Hands-on with git and coding best practices
– Unit testing
– Experience in working with relational data sets using SQL
– Experience with data warehousing, dimensional modelling, and cubes
– Experience in building and optimizing data pipelines, architectures, and datasets
– Experience in working with Azure, AWS, or other cloud providers
– Designed, built, and delivered production-ready data products at an enterprise level
– Highly proficient in English and able to communicate with all levels
– Agile mindset and experience of Scrum
– It’s a plus if you have worked with: Big data: Spark, Hadoop Data pipeline and workflow tools: Airflow Infrastructure: Kubernetes and Helm; we’re using Airflow running on Kubernetes Stream-processing systems: Kafka or Spark Streaming
RESPONSIBILITIES
– Work closely with your colleagues within a product team to design scalable, efficient, and stable products
– Work closely with product owners to build and deliver features designed to drive commercial business cases and efficiencies within reporting and analytics, and other data-driven use cases
– Create and maintain a high-quality data pipeline architecture
– Obtain relevant business and system knowledge to convert requirements efficiently to technical design documentation and conceptual data modelling
– Ingest large, complex data sets, automate manual processes, optimize data delivery, improve data quality, etc.
– Own your data products and track continuous stability and benefits
– Live and breathe “build -once-consume-many” culture in which we enable others to use our data products for maximum value-add
– Work with stakeholders and teams to assist with data-related technical challenges
– Follow best practice and existing guidelines, but also push the limits
– Thrive in a fast-paced environment, and you get motivated by challenges as a true problem solver.
WHAT WE OFFER
– Paid Vacation
– Hybrid Work (home/office)
– Sick Days
– Sport/Insurance Compensation
– Holidays Day Off
– English Classes
– Training Compensation
– Transportation compensation
COMPENSATION & BENEFITS
– Discover what it’s like to work with us

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