Lead Data Engineer

Remote (United States)

Being a data-informed company, data helps us create exceptional experiences for our customers and provide insights into the effectiveness of our product.


We are looking for Lead Data Engineers that will build and maintain our data warehouse, data pipelines, data applications, collect data from multiple sources, and expose services that make data a first-class citizen at Spin. You will be building, architecting and launching highly reliable and scalable data pipelines to support data processing and analytics needs and work closely with Data Analysts, Data Scientists, and Engineers on coming up with new data models and exploring new data sources to add to our Analytic Data Warehouse. You also take on roles to build full-stack data applications that empower users to make data-driven decisions.


Our team consists of engineers that are passionate about creating finely polished and intuitive experiences and, at the same time, obsess over the performance and reliability of what we build. We challenge the status quo and strive towards finding the best way to solve problems.


We promote being a more well-rounded engineer by working on different parts of the engineering stack. We also work in very small groups to keep processes and overhead low, so we have a lot of trust and accountability to perform the work required to build the best product. 


Responsibilities

  • Build and maintain our data warehouse, pipelines and data applications
  • Scaling up our data infrastructure to meet business needs
  • Deploy sophisticated analytics programs, machine learning, and statistical methods
  • Work cross-functionally with our product, business, finance, operation and engineering teams


Qualifications 

  • Minimum of 5+ years of relevant experience in building and architecting data solutions
  • Expert in SQL and high-level languages such as Python, Java, or Scala
  • Built and maintained data warehouses and ETL pipelines
  • Worked with Cloud-based architecture such as Google Cloud (preferred) or AWS
  • You have worked with big data solutions like BigQuery (preferred), Redshift, or Snowflake
  • Experience with real-time data streaming infrastructures like Kafka (preferred), AWS Kinesis or Spark
  • Experience with Data modeling and warehouse design
  • Deep understanding of distributed systems
  • You will be working with BigQuery, DBT, Airflow, Python, Fivetran, Kafka, git and Looker, and we welcome new ideas.
  • Familiarity with Machine Learning operations (MLOps) and related serverless frameworks like Google MLOps, AI Platform or coding framework like Kedro.

 

Benefits & Perks

  • Opportunity to join a fast-growing startup and help shape and establish the company’s industry leadership
  • Competitive health benefits
  • Unlimited PTO for salaried roles
  • Pre-tax commuter benefits
  • Monthly cell phone bill stipend
  • Wellness perk for salaried roles


Spin is an equal opportunity employer and will not discriminate against any employee or applicant for employment in an unlawful matter. We celebrate diversity and are committed to creating an inclusive environment for all individuals. Spin treats all employees and job applicants on the basis of merit, qualifications, and competence without regard to any qualified individuals' sex, race, color, religion, national origin, ancestry, gender (including pregnancy, breastfeeding, or related medical condition), sexual orientation, gender identity, gender expression, age, physical or mental disability, medical condition, genetic characteristic or information, marital status, military and veteran status, or any other characteristic protected by state or federal law. Spin also considers qualified applicants with criminal histories, consistent with applicable local, state, and federal law.


Spin is committed to providing reasonable accommodations for qualified individuals with disabilities in its job application procedures. If you need assistance or an accommodation due to a disability, you may contact us at job_accommodations@spin.pm.

Subscribe to Job Alerts