Who We Are

Mayanalytics is a technology and data company that develops growth automation software for Amazon sellers. Our initial product set includes:

  • Advertising management, which optimizes the performance of our customers' campaigns to deliver higher sales and profits
  • Inventory management, which utilizes forecasting based on organic and ad-driven sales to predict when inventory needs to be restocked

We are a venture-backed and Y Combinator W21 startup that is delivering significant results for our customers across the growing e-commerce space. We are looking to expand the team! For more information about Mayanalytics, please visit www.mayanalytics.com.

Our Culture

We value data-driven processes through innovation, collaboration, and a passion for getting things done. For our hires, we aim to cultivate the best + diverse employees as we continue to foster a culture of open communication and transparency. We are redefining what it means to be a remote company with team members living and working across the globe. Work from anywhere and if you and other team members want to work together in Mexico, USA, Spain, wherever — we will help facilitate that. We embrace world-views, diversity in background, diversity in make-up, and diversity in thought.

We are driven and hard-working but also committed to having fun along the way with weekly virtual happy hours, semi-annual offsites, and unlimited paid time off. We embrace life-work balance. We know you have a life outside of Mayanalytics and we want to help you nurture that too. We understand that helping you stay happy and healthy are key ingredients to enable you to deliver your best work.

The Team

At Mayanalytics, we build innovative tech products that create significant competitive advantages for our customers. Transparency, quality, urgency, and intellectual honesty are central tenets of our work ethics while embracing experimentation and collaboration to produce results that customers love. The core MIT founding team brings experience across e-commerce, tech infrastructure, marketing, finance and deep expertise in the Amazon seller ecosystem. Our founder brings experience of being an early team member at the fastest U.S. startup on record to reach "unicorn" status - also operating within the Amazon ecosystem.

The Role

Mayanalytics brings a data-driven approach to the Amazon ecosystem.

The Senior Data Engineer will be a key early employee working closely with our CTO to architect highly-performant, reliable, and scalable end-to-end data products that will be used by thousands of Amazon sellers. The successful candidate will build high performance data pipelines - working with both structured and unstructured data. Candidates must be able to write production level, maintainable code in Python and SQL, and have extensive experience with Apache Airflow. The ideal candidate will also have the ability to prioritize multiple objectives and deliver innovative solutions at a rapid pace. We operate under a startup environment and thus value someone who is self-motivated and can take their own initiative.

In addition to the above, responsibilities will include:

  • Design, develop, and implement end-to-end data solutions
  • Build ETL/ELT pipelines to process structured and unstructured data
  • Design data models for optimal storage and query performance
  • Implement operational procedures to improve the running of pipelines
  • Move data from legacy systems to new solutions
  • Optimize system performance by conducting tests, troubleshooting and integrating new elements
  • Develop security and backup procedures
  • Conduct thorough research to solve difficult challenges and to stay up to date with new technologies, tools, and best practices
  • Work cross functionally with data scientists, backend engineers and product managers to identify future needs and requirements
  • Mentor junior engineers and create a culture of engineering excellence by refining our processes, documentation, onboarding, and interviewing practices

Must Haves

  • 2+ years' experience of working as a Data Engineer, Data Scientist, Data Analyst or other relevant position
  • 4+ years of relevant software engineering work experience
  • Takes ownership of work from beginning to end
  • Strong proficiency with data languages such as Python, SQL, and Scala
  • Strong proficiency working with Apache Airflow or similar
  • Significant experience with data warehouses, Snowflake, BigQuery, Redshift, etc.
  • Experience building data pipelines with ETL and iPaaS providers, such as Fivetran, Data Virtuality, Celigo, etc.
  • Experience working with data visualization tools, such as Looker, Tableau, Plotly, D3.js, etc.
  • Proficiency writing data validation and schema tests
  • Significant experience gathering and analyzing system requirements
  • Experience working with Google Cloud Platform (GCP) and/or AWS
  • Strong analytical and problem-solving skills
  • English skills (ability to effectively communicate via written and spoken english)


Nice to Haves

  • Degree in computer science or related
  • Experience with Snowflake, DBT, and Looker
  • Experience with Hadoop or other big data paradigms, and associated languages, such as Spark, Presto, Hive, etc.
  • Understanding of database structure principles
  • Understanding of anomaly detection algorithms
  • Experience with serverless frameworks (Google/Firebase cloud functions or AWS Lambda)
  • Understanding of cloud infrastructure deployments using Infrastructure-as-code tools, such as Terraform, AWS Cloud Formation, or similar
  • Understanding of CI/CD (e.g. GitLab CI)
  • Experience with Kubernetes or other distributed systems.
  • Excellent communication skills, with the ability to synthesize, simplify, and explain complex problems to different types of audience, including customers, customer success and executives

Mayanalytics does not accept/pay fees for unsolicited resumes from third-party agencies/vendors.

As part of our dedication to our workforce’s diversity, Mayanalytics is committed to Equal Employment Opportunity without regard for race, ethnicity, gender, protected veteran status, disability, sexual orientation, gender identity, or religion.