This role bridges business needs and technical solutions by translating requirements into detailed solution designs, data flows, and actionable work packages for big data engineers. The role involves working on the Friction Finder project, which is based on a process mining tool and requires setting up a framework and structure for event logs.
Responsibilities:
Work closely with Data Product Manager (DPM) & (Business) stakeholders to understand business requirements and data needs and use them to design end-to-end data flows.
Conduct source-to-target analyses (S2T) by analyzing the data in depth and documenting data transformations.
Follow-up application evolutions with DPM to assess data product impact.
Review overall (data model) designs and implementation in the context of scalability and applicability for the company's context. Align on cost optimizations with Tech Lead and Data Product Manager.
Design fit-for-purpose logical data models and data flows that match business reality with a focus on quality by design principles and consolidate into Epic Solution Design.
Define user acceptance testing and semantic quality checks.
Be available for questions and perform intermediate reviews of the delivery of the Data Engineers and support Data Engineers in complex bugs & incidents.
Provide 3rd line of support for datasets and coordinate with DPM and Data Engineers to resolve incidents or problems.
Collaborate with external data engineers for the execution of tasks, including source-to-target analyses and code reviews.
Ensure the framework is robust, scalable, and cost-efficient.
Present solution designs to data architects and other technical stakeholders.
Requirements & Qualifications:
A Master’s or Bachelor’s in Computer Science or related education/experience.
Profound experience in production-level data environments.
Excellent knowledge of Snowflake and SQL.
Experience with modern schedulers: Dagster, Airflow, etc.
Experience with DBT (Data Build Tool).
Strong communication skills to effectively present insights and recommendations to (business) stakeholders. Comfortable challenging others.
Strong statistical and analytical skills to interpret complex data relations.
Problem-solving mindset.
Experience in designing frameworks for data models and combining assets from different products.