Factored
From Factored's careers page
Status: listed on the employer's own careers page when we last checked (daily). Confirm on their site before applying.
At Factored, you’ll be part of a community that values learning, ownership, and authenticity, where your growth is personal and your ideas matter.
Fully remote | Complete engagement job
Founded in Palo Alto by Dr. Andrew Ng and Israel Niezen, Factored helps U.S. companies build and scale world-class AI, ML, and Data teams, powered by the top 1% of LATAM talent, with a defining purpose: To empower brilliant humans, unleash their potential, and amplify their impact in the world.
At Factored, you’ll be part of a community that values learning, ownership, and authenticity, where your growth is personal and your ideas matter. We’re transparent, curious, and collaborative. We strive for excellence, celebrate diversity, encourage curiosity, and build an environment where you can truly thrive.
As a Senior Data Engineer, you will engage full-time in designing and evolving the data architectures that power intelligent products for global and Fortune 500 organizations. You’ll build high-performance pipelines, optimize large-scale processing frameworks, and design data models that enable analytics, machine learning, and enterprise-grade decision-making.
This role is ideal for engineers who excel at navigating complex data environments, think in terms of scalable systems, and take ownership of data reliability, quality, and performance across the entire lifecycle. Your work will ensure teams can experiment faster, deliver smarter products, and unlock meaningful insights through trusted, well-orchestrated data.
We are especially interested in candidates with strong hands-on experience in Databricks and Snowflake, and exposure to graph-based data models or technologies is a strong plus.
Develop and maintain ETL (Extract, Transform, Load) processes using Python.
Write efficient SQL queries to extract, manipulate, and analyze data from various databases.
Design, build, and optimize large-scale data pipelines using modern cloud data platforms such as Databricks and Snowflake.
Design and develop optimal data processing techniques, including automating manual processes, data delivery, data validation, and data augmentation.
Collaborate with stakeholders to understand data needs and translate them into scalable solutions.
Design and develop 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.
(Nice to have) Work with or contribute to graph data models or graph databases (e.g., Neo4j) to support relationship-driven use cases.
5+ years of professional experience shipping high-quality, production-ready code.
Strong computer science foundations, including data structures & algorithms, OS, computer networks, databases, and object-oriented programming.
Experience in setting up data pipelines using relational SQL and NoSQL databases, including Postgres, Cassandra or MongoDB.
Strong experience with data processing and warehousing tools such as Databricks and Snowflake.
Experience with cloud platforms such as AWS, GCP, or Azure
Experience with processing and orchestration, such as Spark or Airflow.
Proven success in 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.
Excellent verbal and written communication skills in English.
(Nice to have) Familiarity with graph technologies (e.g., Neo4j) or graph-based data modeling.
Ownership through equity participation.
Annual company retreat.
Company-wide winter break.
Paid time off.
Optional in-person events and meetups.
Tailored career roadmaps.
High-performance culture.
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.
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