Data Engineer

Type of Employment:
Full-time
Location:
Lisbon

About the Role

As a Data Engineer, you will be responsible to build data products to enable data-driven decision making across the organization and promote strategic planning. You will also deliver an improved understanding of the company’s various metrics to allow for better short and long term forecasting and planning. You will develop close working relationships with various teams including Product, Analytics & Research, Finance, Sales, Marketing, and more.

What You'll Be Doing


  • Design and Model DWH, pipelines and data products


  • Create new ETL processes and optimize existing ones, ensuring quality data deliverables


  • Work with various teams to define key metrics (KPIs) and provide the methodologies to accurately measure Riskified’s performance


  • Create smart, innovative and effective visualization methods, and promote engagement and implementation of them


  • Be the main point of contact for technical support related to data activities for various teams within Riskified


Qualifications


  • Minimum 3-4 years experience in a Data Engineering or BI position - must 


  • Strong proficiency in SQL for querying, analyzing, and transforming data - must


  • Knowledge in data modeling and DWH design - must


  • Knowledge of data quality techniques and data monitoring design - must


  • Experience in developing efficient ETL and pipeline processes - must


  • Experience with BI tools such as Tableau, Looker or similar - must


  • Knowledge in building pipelines in Airflow - an advantage


  • Experience with Python - an advantage


  • Bachelor’s Degree in Science/Data Systems Management/Industrial Engineering and Management


  • Good comprehension of data, and how to tell the story behind it



The benefits we offer for the position:


  • Health insurance with dental coverage

  • Wellness Allowance

  • Monthly work allowance

  • Meal allowance

  • Anual Bonus

  • Cool office in Saldanha

  • Udemy Full Access

Working conditions

  • Hybrid working model (2-3 days a week)






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