Possible Finance-posted 1 day ago
$142,000 - $150,000/Yr
Full-time • Mid Level
Hybrid • Seattle, WA
101-250 employees

Since our founding, we have redefined how people approach small-dollar loans—delivering over $1 billion in funding to more than 1 million customers, issuing over 4 million loans, and saving our customers more than $500 million. At Possible, we’re building a new type of consumer finance company; one that helps our customers stay out of debt rather than profit from their staying in it. We are a Public Benefit Corporation with the mission to help communities unlock economic mobility through affordable credit products crafted to improve financial health for generations. Join the team that’s making our goal a reality. We are seeking a hardworking Data Engineer to join our ambitious data team. As a Data Engineer at Possible Financial Inc., you will craft, build, and maintain world-class data models and pipelines. Collaborate cross-functionally to drive data-driven decision-making and successfully implement innovative solutions. Are you interested in architecting flawless data infrastructure while making a positive societal impact? Have you always wanted your work to have a mission to help underserved communities? Join us in Seattle, WA, and work on high-impact, large-scale data engineering projects. We apply AWS, Databricks, dbt, Airflow, and Terraform. We are looking for a self-starter with outstanding abilities to deliver on time and a passion for data to solve business problems. Possible Finance is dedicated to financial fairness and community empowerment. We welcome diverse perspectives and experiences to help us achieve our mission of unlocking economic mobility for generations to come. Learn more about us as a Public Benefit Company .

  • Design and implement scalable data pipelines and ETL processes
  • Build and optimize data models for analytics and machine learning applications
  • Collaborate with finance, marketing, and other teams to support their data needs
  • Develop and maintain cloud-based data infrastructure (AWS + Databricks)
  • Implement data quality measures and monitoring systems
  • Evaluate and implement new data technologies and tools
  • 3+ years of experience in data engineering or a similar role
  • Knowledge of SQL, Python, and Spark
  • Strong understanding of data modeling and architecture principles
  • Proficiency in cloud platforms like AWS, GCP, or Azure and IaC tools such as Terraform
  • Experience with modern data warehousing solutions
  • Knowledge of at least one orchestration tool (e.g. Airflow, Dagster, Prefect, AWS Step Functions)
  • Experience with dbt or similar transformation tools
  • Background in implementing data governance and security practices
  • Experience with real-time data processing systems such as Kafka, Kinesis, etc.
  • Knowledge of machine learning operations (MLOps)
  • Familiarity with monitoring and observability tools like DataDog, Grafana, Great Expectations, and Elementary
  • significant stock options
  • comprehensive benefits
  • a bonus plan
  • commuter benefits
  • an excellent office space with complimentary drinks and food options
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