Data Orchestration Engineer

Remote position (only for professionals based in Argentina or Uruguay)

We are seeking a skilled Data Orchestration Engineer to join one of our client's team. The perfect candidate will have expertise in designing lean data models, building advanced data products, and maintaining robust data pipelines. The ideal candidate will have a strong command of statistical and machine learning techniques, including natural language processing and large language models (LLMs). You will be responsible for developing insights, enhancing discoverability, and ensuring data accuracy within our platform. Proficiency in tools such as Airflow, Snowflake, Python, and AWS is essential for success in this role.

Responsibilities:

- Design a clear and lean data model that clearly outlines where information is coming from and how it is being generated at every step along the way.

- Thoroughly data-test and validate assumptions about the data at each step along the way.

- Insights Layer Ownership: Build models and algorithms to generate first-party data using statistical and machine learning techniques, including LLMs and natural language processing. Generate derived insights and determine accurate values from error-prone sources (e.g., headcount information).

- Data Product Development: Develop and enhance data products to improve the discoverability of companies in our database. Continuously improve similarity, relevance, and tagging algorithms that power our search engine.

- Pipeline Maintenance: Oversee the maintenance and health of data pipelines to ensure accurate and efficient data transformations.

- Team Collaboration: Collaborate with the team to devise product goals, outline milestones, and execute plans with minimal guidance.

- Data Warehouse Design: Design a robust data warehouse following best practices and industry standards. Transferring data from S3, etc.

- Collaborate with our platform team to make design decisions on the optimal middle layer database flow.

Skillset Familiarity:

- Orchestration Tools: Airflow, Dagster

- Data Warehouses: Snowflake, Databricks

- ETL Tools: DBT Models

- Programming Languages: Python, SQL

- Containerization: Docker

- DevOps: AWS

- Databases: Clickhouse, Postgres, DuckDB

About RYZ Labs:

RYZ Labs is a startup studio built in 2021 by two lifelong entrepreneurs. The founders of RYZ have worked at some of the world's largest tech companies and some of the most iconic consumer brands. They have lived and worked in Argentina for many years and have decades of experience in Latam. What brought them together is the passion for the early phases of company creation and the idea of attracting the brightest talents in order to build industry-defining companies in a post-pandemic world.

Our teams are remote and distributed throughout the US and Latam. They use the latest cutting edge technologies in cloud computing to create applications that are scalable and resilient. We aim to provide diverse product solutions for different industries, planning to build a large number of startups in the upcoming years.

At RYZ, you will find yourself working with autonomy and efficiency, owning every step of your development. We provide an environment of opportunities, learning, growth, expansion and challenging projects. You will deepen your experience while sharing and learning from a team of great professionals and specialists.

Our values and what to expect:

- Customer First Mentality - every decision we make should be made through the lens of the customer.

- Bias for Action - urgency is critical, expect that the timeline to get something done is accelerated.

- Ownership -  step up if you see an opportunity to help, even if not your core responsibility. 

- Humility and Respect - be willing to learn, be vulnerable, and treat everyone that interacts with RYZ with respect.

- Frugality - being frugal and cost conscious helps us do more with less.

- Deliver Impact - get things done in the most efficient way. 

- Raise our Standards - always be looking to improve our processes, our team, our expectations. Status quo is not good enough and never should be.