Data Engineer focused on Search ML/AI

We're helping one of our clients, Web Shop Manager, hire for 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, México, Colombia and Brazil residents).

Skills: Proficient in 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 non-technical people.

- Develop and maintain scalable and high-performing software solutions using the specified tech stack.

- Architect and provide guidance on building data pipelines and lakes.

- Collaborate with cross-functional teams to design and implement new features.

- Ensure code quality through functional testing.

- Optimize applications for maximum speed and scalability.

- 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.

Required skills and qualifications:

- At least four years of experience in building large-scale software applications.

Experience in the automotive industry and automotive parts standards such as ACES and PIES.

- ​​Experience in performing data analysis, data ingestion and ETL (Extraction, Transformation & Loading).

- Experience with Big Data technologies (Airflow, Hadoop, M/R, Hive, Spark, Metastore, Presto, Flume, Kafka, ClickHouse, Flink, etc.).

- Experience with Elasticsearch & OpenSearch.

- Experience with Vector Databases (Qdrant, Opensearch, Milvus).

- Experience with AWS Bedrock & Q.

- Excellent problem-solving and communication skills.

- Experience working in a small team startup environment.

- Experience working on or implementing e-commerce platforms or solutions.

- Experience with AWS and cloud computing services.

- Ability to write and maintain clear and concise technical documentation.

- Experience in search technologies such as full-text lexical search and/or semantic vector-based search.

- Strong understanding of Git and experience with CI/CD pipelines.

- Experience building SaaS dashboards with graphs to display analytics and performance KPIs.

- Experience working with RESTful and GraphQL APIs.

- Knowledge of Python, R, Rust.

- Excellent ability to write efficient SQL queries.

- Excellent debugging and optimization skills.

- Preferred skills and qualifications.

- Bachelor's degree in Computer Science, a related technical field involving software or systems engineering, or equivalent practical experience.

- Interest in learning new tools, languages, workflows, and philosophies.

- Professional certification.

If you are a talented Data Engineer passionate about creating innovative solutions and thriving in a fast-paced startup environment, we would love to hear from you.

Please submit your resume, cover letter, and portfolio or GitHub showcasing your previous work.

Note: This job description is for reference purposes only and is not an exhaustive list of responsibilities and qualifications.