https://bayt.page.link/wFjqW4S7qhwZtCPq8
أنشئ تنبيهًا وظيفيًا للوظائف المشابهة

الوصف الوظيفي

Russian hacker, Vladimir Leonidovitch Levin, attempted the biggest bank heist the world had ever seen via dial-up internet in 1994, Zia Hayat, Callsign CEO and founder, was hooked - armchair fraud became a real possibility. From this moment, Zia knew he wanted to play a part in stopping the bad guys and securing the internet for all. Founded In 2012, Callsign's mission has been to make Digital Identity simple and secure for everyone and everything. In that time, we've grown to over 200 employees, opened offices in Singapore and Abu Dhabi, been recognised as a WEF Global Innovator and our technology is being used by many of the world's leading financial institutions to keep millions of consumers safe.


But we aren't stopping here. The identity revolution has only just begun, and we are looking to hire the brightest and inquisitive minds to help us make every web, mobile and physical Interaction seamless and secure. If this sounds like you, lets chat.


Responsibilities:


  • Develop and maintain ETL pipelines to extract data from multiple production environments, for ingestion into a data warehouse, and transformation into an analytics layer
  • Transform the data using techniques such as cleaning, aggregating, and filtering to prepare it for analysis and reporting.
  • Proactively improve processes and documentation around data management, ingestion, versioning, and storage
  • Manage internal stakeholders and interface with consumers of the data warehouse, including data science, analytics and governance
  • Develop tooling for internal developers who consume the data (data scientists, business analysts, and technical consultants)
  • Always keeping security, performance, scalability and cost in mind when designing solutions or working on existing ones
  • Develop, maintain and assist with the release of microservices related to data extraction
  • Optimize the performance and scalability of ETL pipelines by choosing appropriate tools and technologies, and by tuning and optimizing data models and data flows.
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