Ingénierie des données senior II // Senior Data Engineer II

March 19

Mistplay

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Mobile games • Mobile • Advertising • AdTech • Entertainment

51 - 200

💰 Pre Seed Round on 2018-05

Description

• Design and implement efficient, reusable, and reliable data architecture for the organization • Participate in architecture and systems design discussions, ensuring alignment with overall business goals and technology strategy • Independently perform application development and coding, and perform unit tests of applications • Collaborate with development and AI teams to integrate individual components into complex enterprise systems and ensure seamless integration with existing systems • Monitor key product metrics and identify root causes of changes in metrics and provide insights to senior management on business performance • Analyze and interpret trends or patterns in complex data sets and use visualization tools to tell the story through dashboards and reports • Create and maintain standardized tools for operations and provide results on business performance to different audiences, including senior management • Maintain the existing data lake and migrate to the lakehouse architecture, and automate data pipeline deployments and requests for building machine learning features • Acquire data from primary or secondary data sources and maintain databases/data systems to enable operational and exploratory analysis • Automate analyses and pipeline creation via Kinesis, Airflow, Lambda, Databricks, DBT, and other relevant tools • Collaborate and engage with internal stakeholders such as business teams, product owners, and data science teams to define top priorities and refine processes • Act as a point of contact to resolve stakeholder issues • Focus on continuous improvement and technical standards, improving productivity, monitoring, tooling, and industry best practices

Requirements

• Bachelor's degree or higher in a quantitative discipline such as computer science, or equivalent experience and evidence of exceptional ability • 7 years or more of professional experience in data engineering and platform engineering • Extensive experience in developing a modern data stack (data lake, lakehouse, streaming data, ) and AWS or equivalent cloud service provider • Ability to work under pressure while collaborating and managing competing demands within tight deadlines

Benefits

• Passionate and curious about data • High attention to detail and professionalism in reporting • Team player with ability to collaborate with diverse functional groups • Strong oral and written communication skills for managing and communicating data and system health and integrity • Engage with internal stakeholders such as business teams, product owners, and data science teams to define top priorities and refine processes • Focus on continuous improvement and technical standards, improving productivity, monitoring, tooling, and industry best practices