Head of Common Data Warehouse @ Data & Tech

Head of Common Data Warehouse @ Data & Tech

Here’s your opportunity to work with data both wide and long!

Schibsted Analytics

Analytics is about connecting people to data. In Schibsted Analytics we want to do exactly that. Our vision is to “Enable all the people in Schibsted to leverage any data in Schibsted” and we will head towards that vision by removing friction between data and people throughout the 45+ Brands that make up Schibsted.

The Common Data Warehouse

In Schibsted practically all of our products are digital and as such a vast source of behavioural, user, content and transactional data. In addition large quantities of data related to finance, operations, HR, CRM, products and many other areas are generated every day. Combined these two super domains put data at the core of our business every day. In the Common Data Warehouse we will provide structured, highly accessible, interconnected and privacy compliant datasets spanning all of these foundational business domains allowing the people that drive our business to make data informed decisions and strategies.

The Role

To lead the effort of modelling and engineering the Common Data Warehouse we are looking for an unicorn among unicorns. The role will be running a team of data engineers working on the core cross business data models while also initiating and driving collaborative efforts with data engineers and BI teams across the organization. We want to see business specific, non-redundant contributions to the data model be made in other teams based on a common architecture and data accessibility concept. Head of Common Data Warehouse will also need to understand our business inside out in order to design and deliver relevant and flexible data structures to abstract user groups often without the aid of explicit requirements.

The role will report directly to the Director of Analytics and be part of the Schibsted Analytics leadership team. You will be expected to contribute both strategically and cross-functionally in that context, but also tactically and operationally in the team employing agile approaches while balancing data model coherency.

Responsibilities

• Lead the development of large scale ELT pipelines leveraging AWS, Snowflake, Airflow, Matillion and many other state of the art data and analytics technologies
• Develop and lead a modern, high performing and people oriented data engineering team that will design and implement the common core data model of our Common Data Warehouse (CDW)
• Ensure overall data model coherency and interconnectedness across the Schibsted CDW
• Ensure a long term CDW technical architecture that allows local BI teams to contribute to DWH in an autonomous but compliant manner
• Be the lead data warehouse architect across the teams contributing to the CDW both in terms of data model and technical architecture
• Own, develop and execute on implementation roadmap for CDW within direct reports as well as adjacent contributors
• Ensure data privacy regulations are solidly, effectively and efficiently adhered to in all our data engineering work by design supported by strong processes
• Be the primary point of contact for requirements and collaborations with our internal partners such as the Data Platform team and Integrations team
• Proactively survey the technical architecture, tooling and solution landscape seeking opportunities to optimize time to data, data quality and model agility
• Ensure a service minded team culture that promotes data-driven decisions and ensure excellent data quality in collaboration with Data Quality Managers
• Support the Data Quality Manager in populating the corporate data catalog with metadata and designing data governance workflows

Key Skills/Technologies

• Data modelling and ETL/ELT both for batch and streaming
• Event Driven Architecture for data warehousing
• Kimball and Data Vault modelling techniques
• Airflow, Matillion, dbt, AWS (EMR), Athena, Kinesis,SQL, Python, Spark, Scala, Java, S3, Glue, Lambda, SSO

Who you are

• Experienced Data Engineering manager with a forward leaning stance towards leveraging new technology to provide awesome data experiences
• Emphatic but decisive leader highly adept at prioritizing and focusing efforts under pressure while being able to balance short and long term goals
• Strong collaborative 360 approach balancing complexity and pragmatism
• Engaging communicator with the ability to clearly provide the two way narrative bridge between data and business
• Able to operate comfortably in an agile large scale corporate environment
• Have a strategic mindset and a natural ability to translate into tactics
• Able to balance long vs. short perspectives well
• Thrive on enabling others to deliver value
• English language written and spoken fluency is required