Senior Data Engineer

Latin America
Engineering /
Full-time /
Who we are:
Factored was conceived in Palo Alto, California by Andrew Ng and a team of highly experienced AI researchers, educators, and engineers to help address the significant shortage of qualified AI & Machine-Learning engineers globally. ​We know that exceptional technical aptitude, intelligence, communication skills, and passion are equally distributed worldwide, and we are very committed to testing, vetting, and nurturing the most talented engineers for our program and on behalf of our clients. 

We are looking for a Senior Data Engineer with experience in machine learning environments to join our team. You will drive the development of AI products for external clients and internal efforts, and participate in the development of top-notch AI systems.

At Factored we are building a company that we all hold as our own, every single one of us. We need your skills to help take this rocketship to new heights and help create new opportunities for us.  In return, you will be rewarded with an amazing team that supports you, rich culture, shared success, and the flexibility to work– from the comfort of your home. #LI-Remote

What you will be doing:

    • Consume different ML pipelines in real-time that use multiple data sources for inference.
    • Design and develop optimal data processing techniques to handle real-time and near real-time requests over millions of transactions.
    • Implement ETL processes for different datasets using a big data tech stack and orchestration tools.
    • Deploy and maintain data infrastructure using cloud tools, ensuring high availability and responsiveness of the system through the use of best practices.
    • Monitor performance and advise infrastructure changes.

What you must bring:

    • +7 years of experience with data, with at least 3+ years working with data engineering in the context of machine learning projects.
    • 6+ years of professional experience shipping high-quality, production-ready code.
    • Strong computer science foundations, including data structures & algorithms, OS, computer networks, databases, algorithms, and object-oriented programming. 
    • Strong experience with Big Data environments (EMR, Scala, Python, SQL, Airflow). 
    • Experience using AWS tools and platforms (Model deployment/evaluation/monitoring, ML feature pipeline).
    • Experience setting up data pipelines using relational SQL and NoSQL databases, including Postgres, Cassandra, or MongoDB.
    • 1+ year of prior experience or exposure to streaming data processing platforms (Apache Kafka, Amazon Kinesis, or similar).
    • Experience with Azure Databricks or Databricks is a MUST.
    • Expertise in workspace configuration to ensure optimal performance and collaboration within the Databricks environment.
    • In-depth experience with Unity Catalog setup, ensuring a well-organized and efficient data catalog.
    • Proficiency in user management, including setting up access controls and maintaining a secure data environment.
    • Skilled in cluster resource management, ensuring optimal utilization of resources and efficient processing.
    • Critical thinking, structured and logical communication skills, problem-solving ability, and articulate solutions for complex settings. 
    • System architecture and design skills.
    • Excellent English communication skills and the ability to have in-depth technical discussions with both the engineering team and business people.
    • Proven success manipulating, processing, and extracting value from large datasets.
    • Expertise with version control systems, such as Git.
    • Strong analytic skills related to working with unstructured datasets.

Nice to have:

    • Master’s or PhD degree is a plus.
    • Experience with real-time scenarios, low-latency systems, and data-intensive environments is a plus.
    • Experience developing scalable RESTful APIs.
    • Experience with consumer applications and data handling.
    • Familiarity with data privacy regulations and best practices.
    • Experience with Golang is a big plus.
At Factored, we believe that passionate, smart people expect honesty and transparency, as well as the freedom to do the best work of their lives while learning and growing as much as possible. Great people enjoy working with other passionate, smart people, so we believe in hiring right, and are very selective about who joins our team. Once we hire you, we will invest in you and support your career and professional growth in many meaningful ways. We hire people who are supremely intelligent and talented, but we recognize that intelligence is not enough. Perhaps more importantly, we look for those who are also passionate about our mission and are honest, diligent, collaborative, kind to others, and fun to be around. Life is too short to work with people who don’t inspire you.  

We are a transparent workplace, where EVERYBODY has a voice in building OUR company, and where learning and growth is available to everyone based on their merits, not just on stamps on their resume. As impressive as some of the stamps on our resumes are, we recognize that human talent and passion exist everywhere, and come from many backgrounds, so stamps matter much less than results. All of us are dedicated doers and are highly energetic, focusing vehemently on execution because we know that the best learning happens by doing. We recognize that we are creating OUR COMPANY TOGETHER, which is not only a high-performing fast-growing business but is changing the way the world perceives the quality of technical talent in Latin America. We are fueled by the great positive impact we are making in the places where we do business, and are committed to accelerating careers and investing in hundreds (and hopefully thousands) of highly talented data science engineers and data analysts. 

In short, our business is about people, so we hire the best people and invest as much as possible in making them fall in love with their work, their learning, and their mission.  When not nerding out on data science, we love to make music together, play sports, play games, dance salsa, cook delicious food, brew the best coffee, throw the best parties, and generally have a great time with each other.