Data Engineer (Python)

Latin America
Engineering /
Full-time /
Remote
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 an exceptionally talented Data Engineer to join our team. You will be called on for a wide range of responsibilities, from data aggregation, scraping, validation, transformation, quality and DevOps administration of both structured and unstructured datasets. Ideally, you will be experienced in optimizing data architecture, building data pipelines and wrangling data to suit the needs of our algorithms and application functionality. Since you’ll be joining an early-stage startup at the ground level, you’ll need to be a self-starter with a high degree of initiative and accountability. You must be able to wear multiple hats and take on additional responsibility on our growing team. #LI-Remote

What you will be doing:

    • Convert data pipelines in Databricks to Unity Catalog and migrate their data storage practices to achieve Unity Catalog compatibility.
    • Build and operate data pipelines in Databricks to bring data from distributed storage locations to the central data lakehouse.
    • Create and maintain optimal data pipeline architecture across multiple data sources, including licensed and scraped data.
    • Assemble large, complex data sets that meet functional needs across Data Teams.
    • Design and develop optimal data processing techniques: automating manual processes, data delivery, data validation and data augmentation.
    • Develop any necessary ETL processes to optimize analysis and performance.
    • Manage analytics tools that provide actionable insights into usage, customer acquisition, operational efficiency and other key business performance metrics.
    • Design and develop a API integrations in order to feed different data models.
    • Architect and implement new features from scratch, partnering with AI/ML engineers to identify data sources, gaps and dependencies.
    • Identify bugs and performance issues across the stack, including performance monitoring and testing tools to ensure data integrity and quality user experience.
    • Build a highly scalable infrastructure using SQL and AWS big data technologies.
    • Keep data secure and compliant with international data handling rules.

What you must bring:

    • 3 - 5+ 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. 
    • Experience with Databricks.
    • Experience in Python and Java.
    • Experience in setting up data pipelines using relational SQL and NoSQL databases, including Postgres, Cassandra or MongoDB.
    • Experience with cloud services for handling data infrastructure such as: Snowflake(preferred), Azure, Databricks, Azure Databricks, and/or AWS.
    • Experience with orchestration tools such as Airflow
    • Proven success manipulating, processing, and extracting value from large datasets.
    • Experience with big data tools, including Hadoop, Spark, Kafka, etc.
    • Expertise with version control systems, such as Git.
    • Strong analytic skills related to working with unstructured datasets.
    • Excellent verbal and written communication skills in English.

Nice to have:

    • BSc in Computer Science, Mathematics or similar field; 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.
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.