Data Engineer - Financial Engineering
September 4
🔄 Hybrid – London
Description
• Develop a deep understanding of how our financial data is used by different consumer bases, tailoring our core data products to meet diverse needs • Build sources of truth for financial transactions and enrich business decisions with foundational financial context • Design, prototype, and build data pipelines that process billions of data points • Advocate for and implement standard processes around data quality and engineering • Apply product thinking to data: manage the data product lifecycle from sourcing to documentation and exposition, always prioritizing consumers’ success and experience • Partner with engineers, data scientists, finance and business teams to build flexible and intuitive data products supporting Spotify globally • Define data models that serve as interfaces to financial domains for the rest of the company • Leverage mentorship and constructive feedback to drive accountability and growth within the team
Requirements
• You are experienced with Data Processing Frameworks: You have experience with one or more higher-level JVM-based frameworks such as Flink, Beam, Dataflow, or Spark • You are comfortable with Ambiguity: You are adept at solving loosely defined problems, particularly when working within a team that has autonomy in its day-to-day decisions. • You are skilled in Cloud-based Environments: You have performed analysis of large datasets in a cloud-based environment, preferably with an understanding of Google Cloud Platform • You have strong analytical skills: You possess strong analytical and problem-solving abilities, coupled with written and verbal communication skills • You are knowledgeable about Data Modeling: You treat data as a product and know how to use data modeling • You are passionate about Clean Code: You care about crafting clean code and have a solid foundation in coding and building data pipelines • You are curious and inquisitive: You have a natural curiosity and love exploring and understanding data, never leaving questions unanswered • You are skilled in large-scale data processing: You are comfortable working with large datasets using SQL and data analytics platforms such as BigQuery • You are an excellent collaborator: You value teamwork and have experience building relationships with diverse customers
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