Data Engineer

Job Details

Posted on: 
July 8, 2024
Job ID:

About the Company

Established in 2004, ALLSTARSIT was founded with a clear vision: to enhance the landscape of global IT employment by bridging the gap between companies and skilled professionals. The core belief was that assembling a team shouldn't be hindered by geographical constraints. Fast forward to the present day, ALLSTARSIT stands as an international outstaffing service provider committed to change the way businesses recruit, compensate, and oversee top talent worldwide. 

With operational hubs scattered across Europe, Asia, and LATAM, and its headquarters situated in San Francisco, US, the company boasts a workforce of over 1,000 adept professionals. Spanning across more than 20 countries, ALLSTARSIT offers a diverse range of skilled employees across various verticals, including AI, cybersecurity, healthcare, fintech, telecom, media, and so on.

About the Project

Our Partner is revolutionizing retail with their dynamic pricing B2B SaaS platform, leading the charge in automating and optimizing pricing strategies with AI-driven insights. Their comprehensive solution, embraced by retailers and brands across over 40 markets, delivers actionable pricing recommendations that drive business growth and profitability. Since 2018, they've been empowering a wide range of industries, including consumer electronics, beauty, and apparel, to seamlessly integrate pricing strategies across online and offline channels.

Our client invites you to join our dynamic and pioneering team, where your expertise in data science will significantly influence our path forward. They are passionate about tackling real-world challenges and seek like-minded individuals eager to make a mark in the retail pricing arena. Embark on this exciting journey with us and play a key role in sculpting the future of dynamic pricing in retail.



Years on the market

Team size and structure

Current technology stack

Required skills:

To excel in this role, candidates should possess the following qualifications and experiences:

  • A Master’s or higher in Computer Science, Physics, Applied Mathematics or a related field, demonstrating a strong foundation in analytical thinking.
  • 3+ years of applied experience in, and a proven track record of using data to drive business results.
  • Strong skills in python development, including package management, deployment, and unit testing.
  • Proficiency in SQL and experience with large-scale data systems such as Hadoop or Spark.
  • Deep understanding of data engineering principles, including ETL pipelines, data quality control and data scalability.
  • Practical experience with AWS cloud services.


  • Familiarity with MLOps infrastructure: CI/CD, software, data & model versioning control, observability, and deployment.
  • Experience in AI/ML system design and implementation.
  • Strong working knowledge and expertise in machine learning, statistical modeling, and data mining is a significant advantage.
  • Hands-on familiarity with key python packages (e.g. polars/pandas, statsmodels, scikit-learn, pytorch, xgboost, etc.).
  • Practical understanding of containerization with Docker and orchestration with Kubernetes.

Scope of work:

We're looking for ambitious individuals passionate about making a significant impact in the retailtech space. If you're motivated by innovation and eager to contribute to a pioneering companyshaping the future of retail pricing, Quicklizard offers the perfect opportunity to challengeyourself and grow with us. Join us in our mission to transform pricing strategies into proactive,visionary actions that redefine retail success.

Your Role and Impact:

  • Design and implement end-to-end solutions, covering system architecture and software development, to support our AI-driven services.
  • Build scalable systems with integrated observability, logging, and tracing to quickly detect, understand, and resolve runtime issues.
  • Collaborate with diverse teams, both internal and external to the R&D group, to drive product innovation and client success.


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