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Data Engineer Focused On Search, Ml/ai

hace 3 meses

Buenos Aires, Argentina Sofvio A tiempo completo
We're helping one of our clients,
Web Shop Manager, hire for a
Data Engineer focused on Search, ML/AI.
"Empowering eCommerce success globally with advanced product data expertise and superior customer experience"

Compensation
:
To be agreed upon.

Location
:
Remote (for Argentina, Colombia, Mexico, and Brazil residents).

Skills
:
Proficient Big data technologies, AWS, ETL, Airflow, AWS Bedrock, Hadoop, Elasticsearch, and vector databases.

Responsibilities and more:

  • Participate in all aspects of agile software development, including design, implementation, and deployment.
  • Design, build and maintain data transformations efficiently and reliably for different purposes (e.g. indexing, reporting, growth analysis, multidimensional analysis).
  • Design, implement and maintain reliable, scalable, robust and extensible big data systems that support core products and business.
  • Design, develop and support data pipelines and workflows that integrate various sources of structured and unstructured data across our customers' landscape.
  • Assess and implement any customizations and custom data wrangling needed to transform customer datasets in a way that is best suited for processing by our ML models.
  • Monitor data processing and machine learning workflows to ensure customer data is successfully processed by our ML models, debugging and resolving any issues faced along the way.
  • Generate necessary data artifacts and analytics needed to assess the quality of results generated by different parts of the AI workflow to ensure they meet desired quality standards.
  • Collaborate closely with the engineering team to assess model performance and improve results as needed.
  • Collaborate closely with Product Engineering as needed to resolve any issues faced during customer deployment and onboarding.
  • Collaborate closely with Customer Success Managers and Account managers to maintain close customer relationships and ensure customer satisfaction.
  • Develop tooling and playbooks to streamline and automate key technical delivery activities to be repeatable and scalable.
  • Develop and maintain RAG & Vector embeddings for AI and semantic search.
  • Establish solid design and best engineering practice for engineers as well as nontechnical people.
  • Develop and maintain scalable and highperforming software solutions using the specified tech stack.
  • Architect and provide guidance on building data pipelines and lakes.
  • Collaborate with crossfunctional teams to design and implement new features.
  • Ensure code quality through functional testing.
  • Troubleshoot and debug issues to ensure smooth functionality.
  • Collaborate across time zones via Slack, GitHub comments, documents, and frequent videoconferences.
  • Stay up to date with industry trends and best practices.