• 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 support PANDORA to drive the business cases and efficiencies within reporting and analytics & AI and other data driven use cases
• Create and maintain 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.

• Relevant education in within Computer Science, Mathematics, Economics, Information Management, or Statistics.
• 3+ years of experience as a Data Engineer or in Software engineering role with focus on data.
• Proven experience with Data Bricks, ADF, Data Lake, Synapse, T/U-SQL, and SQL Server.
• Experience with at least one object oriented or functional/scripting languages – Py Spark, SQL, Python etc.
• Dev Ops and CI/CD focus
• Experience in working with relational data sets using SQL
• Experience with datawarehousing, dimensional modelling and cubes
• Experience in building, and optimizing data pipelines, architectures, and datasets
• Experience in working with Azure, AWS or other cloud providers
• Experience in working with Kafka or Streaming data processing.
• Designed, built and delivered production ready data products at an enterprise level
• Good cross-functional communication
• Agile mindset and experience of Scrum

• Big data: Spark, Data Bricks.
• Data pipeline and workflow tools: Airflow, ADF
• Stream-processing systems: Kafka or Spark Streaming