Data Engineer

About the Position

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 organization. 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, alongside other smart engineers in the organization.

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 modeling
• 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 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

Requirements

• Relevant education within 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 modeling, 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

Nice to Have

• 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

We Offer

• Paid Vacation
• Sick Days
• Floating Holidays
• Sport/Insurance Compensation
• English Classes
• Charity
• Training Compensation

About the Company

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.