Data Engineer Turkey

Our client is a global jewelry manufacturer transforming its data and analytics footprint and moving 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 data value and drive business change as a result.

Your primary focus will be building and implementing scalable data products on the global data platform, alongside other smart engineers in the organization.

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

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 practices 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

Relevant education in Computer Science, Mathematics, Economics, Information Management, or Statistics

5+ 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 Python (not just scripting but programming)

DevOps and CI/CD are must-haves

Hands-on with git and coding best practices

Unit testing

Experience 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 with 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

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