Hi, We're Possible Finance!

About Us

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We are seeking an experienced Senior Data Engineer to architect, build, and maintain sophisticated data models and pipelines while mentoring team members across the organization. You will own and drive high-impact, large-scale data engineering projects from conception to production using our stack: AWS, Databricks, dbt, Airflow, and Terraform.

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Possible is at an inflection point, transitioning into a multi-product, high-growth company. This senior role requires outstanding teamwork skills and engineering excellence as you collaborate across teams, guide architecture decisions, and set data engineering standards that support our growth.

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You Are

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You bring deep experience in fintech and/or a genuine passion for helping people achieve financial success and economic mobility. You're a natural collaborator with the maturity to own problems from inception through completion, and you're senior enough to drive an agenda and deliver results even when the path forward isn't clear.

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Most importantly, you've built systems at this scale multiple times before. You can thoughtfully discuss both your successes and failures, articulate the trade-offs between different architectural approaches, and explain why certain decisions worked in one context but not another. You've learned from experience what it takes to build data systems that truly scale, and you bring that hard-won wisdom to every project.

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Responsibilities

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You will architect and implement highly scalable data pipelines and ETL processes while building advanced data frameworks for analytics, reporting, and machine learning applications. Leading technical initiatives and mentoring junior engineers on best practices will be central to your role.

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Partnering with collaborators across finance, marketing, product, and engineering, you will define and support their data needs while establishing data quality standards, monitoring systems, and SLAs. You will drive our data strategy and roadmap, evaluate and implement new technologies, and establish comprehensive engineering guidelines and documentation standards.

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Requirements

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This position requires a minimum of 7 years of demonstrated experience in data engineering with continued progression in technical complexity. You must possess expert-level proficiency in SQL, Python, and Spark with proven ability to optimize performance at scale, along with a deep understanding of data modeling, architecture principles, and design patterns.

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Strong proficiency in AWS and infrastructure-as-code tools like Terraform is essential, with hands-on experience managing production environments. You must have extensive experience with modern data warehousing solutions and data lake architectures, advanced knowledge of orchestration tools (Airflow, Dagster, Prefect, or AWS Step Functions), and confirmed experience with dbt at enterprise scale.

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A strong background in data governance, security, and compliance practices is required, along with proven experience mentoring engineers and driving technical strategy and architecture decisions. Excellent communication skills with the ability to translate technical concepts to non-technical collaborators are essential.

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Experience with monitoring and observability tools (DataDog, Grafana, Great Expectations, Elementary), MLOps, and distributed data architectures such as data mesh will distinguish exceptional candidates.

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This is a Hybrid position. We work in our centrally located office in downtown Seattle three days a week (M, T, and Th).

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The compensation range for this role is $165,000 to $185,000. We also offer significant stock options, comprehensive benefits, a bonus plan, commuter benefits, and an excellent office space with complimentary drinks and food options.