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.
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 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.
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
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