Data Engineer Tech Lead

About The Position

Justt is the world leader in fighting illegitimate chargebacks on behalf of merchants. Our chargeback mitigation solution uses smart technology to create a hands-off experience for merchants, while providing the highest overall success rates in the industry.


As the first data engineer tech lead in the company, you will lead the designing and developing efforts of data systems & ETLs. You will be responsible for choosing the technology that will directly impact the company’s business goals. As well as design and develop tools in order to productionalize machine learning models, support and optimize their performance and cost over time, and allow the Product team to make crucial business decisions.

Responsibilities:

  • Partner with leadership, engineers, and data scientists to understand data needs. 
  • Designing, building and maintaining extremely efficient, reliable, distributed infrastructure and exploratory-data-analysis tooling that will allow the product to work with constantly evolving data requirements and quality levels, and diverse ML models.
  • Designing data models and data warehouses and using SQL and NoSQL database management systems.
  • Writing and maintaining batch & real-time ETLs which operate on a variety of structured and unstructured sources, including the continuous management of ETL, data pipelines, processing, storage, and governance.
  • Enable researchers, data scientists and data analysts to be data driven and create tools that in turn allow the company to push the boundaries of business KPIs.
  • Monitor data performance, taking into account chargeback reversal decisions, that may arrive up to 120 days later.
  • SQL performance tuning, e.g., query optimization considering cost vs speed tradeoffs.
  • Identify and address gaps in processes, engineering habits, peer code reviews, and unit testing, and continually improve the company’s processes and standards.



Requirements


  • Bachelor's degree in Computer Science or related technical field, or an equivalent practical experience.
  • 4+ years experience with large scale data processing, with distributed systems such as Spark.
  • 4+ years development in Python or one other general purpose programming language such as Java.
  • Experience with Airflow or similar solutions.
  • Experience with Docker.
  • Experience with cloud services such as AWS, GCP, Azure or similar on-prem tools & solutions.
  • Speaking and writing English fluently.
  • Independent learner, imaginative and motivated to run on their own, works well with others, with a “can do” approach.


Preferred qualifications:

  • Experience in FinTech and specifically working with Payments data and delayed feedback.
  • Experience with data quality and validation.
  • Experience with machine learning or data science workflows.
  • Experience with Kubernetes.



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