Analytics Engineer

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 around the world, 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 currently looking for a talented Analytics Engineer to join our team. You will be responsible to design and implement transformation steps of ELT pipelines to transform the data into proper formats for data consumption. 

What you will be doing:

• Perform data validation at the beginning of the pipeline.
• Write modular data transformations in clean and test code using version control systems like git.
• Build and test code using CI/CD best practices.
• Perform transformations using state-of-the-art data to create data models for consumption, often leveraging new data stack tools like dbt.  
• Ensure data is ready to be consumed by writing business-aware tests at the end of the pipeline via frameworks like Great Expectations.
• Write and maintain data catalogs and definitions.
• Train business users on how to use a data platform or data visualization tools.

What you bring:

• 2-5 years of experience working in data analytics or analytics engineering-related fields.
• Experience writing clean and testable code with a deep understanding of CI/CD.
• Previous experiences performing advanced, modular SQL-based transformations.
• Experience applying software engineering best practices to analytics code (Version control, testing, continuous integration).
• Strong experience building excellent data documentation in company-wide data discovery tools.
• Strong communication skills in English.

Nice to have:

• Proficiency in Python and other programming languages.
• Experience with the design of ETLs.
• Familiarity with object-oriented programming 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 are 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.