Senior Data Engineer
At Possible, we create financial technology products that are built to benefit our customers’ economic mobility. As a Public Benefit Corporation, it’s not only our mission but our responsibility to succeed. We grow our team accordingly—through a selective process that prioritizes candidate and employee experience alike.
Job Description
About Us
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We are seeking an experienced Lead Data Engineer to join our data team. Serving as an experienced Data Engineering professional, you will architect, build, and maintain sophisticated data models and pipelines. You will also mentor team members and lead the technical direction across the organization.
Are you interested in leading data infrastructure initiatives while doing meaningful work? Have you always wanted your work to contribute positively to underserved communities?
As a Senior Data Engineer at Possible, you will own and drive high-impact, large-scale data engineering projects from conception to production. Key responsibilities include: architect and deliver automated data pipelines at scale, build robust data ingestion and transformation frameworks from diverse internal and external sources to our cloud data lake, establish data security guidelines, and lead integration efforts with other systems at Possible. Our stack is mainly based on AWS, Databricks, dbt, Airflow, and Terraform. We are looking for a confirmed technical leader who can deliver sophisticated projects on time, mentor engineers, and leverage data to solve critical business problems.
Possible is at an inflection point, transitioning into a multi-product, high-growth company. This senior role requires outstanding teamwork skills and engineering excellence. You will collaborate across teams to answer key strategic questions. You will guide architecture decisions and set data engineering standards that support Possible’s growth.
Responsibilities
----------------
- Architect and implement highly scalable, reliable data pipelines and ETL processes
- Build and optimize advanced data frameworks for analytics, reporting, and machine learning applications
- Lead technical initiatives and mentor junior data engineers on guidelines
- Partner with collaborators across finance, marketing, product, and engineering to define and support their data needs
- Build and maintain cloud-based data infrastructure (AWS + Databricks) with a focus on scalability and cost optimization
- Establish and implement data quality standards, monitoring systems, and SLAs
- Evaluate, recommend, and implement new data technologies and architectural patterns
- Drive data strategy and roadmap aligned with business objectives
- Establish data engineering guidelines and documentation standards
Requirements
------------
- demonstrated ability in data engineering or a similar role with demonstrated progression in technical complexity
- Expert-level knowledge of SQL, Python, and Spark with validated ability to optimize performance at scale
- Deep understanding of data modeling, architecture principles, and design patterns
- Strong proficiency in cloud platforms (AWS, GCP, or Azure) and IaC tools like Terraform or AWS CloudFormation
- Extensive experience with modern data warehousing solutions and data lake architectures
- Advanced knowledge of orchestration tools (Airflow, Dagster, Prefect, AWS Step Functions)
- Confirmed experience with dbt or similar transformation tools at enterprise scale
- Strong background in implementing and carrying out data governance, security, and compliance practices
- Experience mentoring engineers and leading technical initiatives
- Excellent social skills with the ability to translate technical concepts to non-technical collaborators
Preferred Qualifications
------------------------
- Knowledge of machine learning operations (MLOps) and ML platform development
- Experience with monitoring and observability tools such as DataDog, Grafana, Phenomenal Expectations, and Elementary
- Track record of driving technical strategy and architecture decisions
- Experience with data mesh or similar distributed data architectures
This is a Hybrid position. We work in our centrally located office in downtown Seattle three days a week (M, T, and Th).
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.
About Us
We are seeking an experienced Lead Data Engineer to join our data team. Serving as an experienced Data Engineering professional, you will architect, build, and maintain sophisticated data models and pipelines. You will also mentor team members and lead the technical direction across the organization.
Are you interested in leading data infrastructure initiatives while doing meaningful work? Have you always wanted your work to contribute positively to underserved communities?
As a Senior Data Engineer at Possible, you will own and drive high-impact, large-scale data engineering projects from conception to production. Key responsibilities include: architect and deliver automated data pipelines at scale, build robust data ingestion and transformation frameworks from diverse internal and external sources to our cloud data lake, establish data security guidelines, and lead integration efforts with other systems at Possible. Our stack is mainly based on AWS, Databricks, dbt, Airflow, and Terraform. We are looking for a confirmed technical leader who can deliver sophisticated projects on time, mentor engineers, and leverage data to solve critical business problems.
Possible is at an inflection point, transitioning into a multi-product, high-growth company. This senior role requires outstanding teamwork skills and engineering excellence. You will collaborate across teams to answer key strategic questions. You will guide architecture decisions and set data engineering standards that support Possible’s growth.
Responsibilities
- Architect and implement highly scalable, reliable data pipelines and ETL processes
- Build and optimize advanced data frameworks for analytics, reporting, and machine learning applications
- Lead technical initiatives and mentor junior data engineers on guidelines
- Partner with collaborators across finance, marketing, product, and engineering to define and support their data needs
- Build and maintain cloud-based data infrastructure (AWS + Databricks) with a focus on scalability and cost optimization
- Establish and implement data quality standards, monitoring systems, and SLAs
- Evaluate, recommend, and implement new data technologies and architectural patterns
- Drive data strategy and roadmap aligned with business objectives
- Establish data engineering guidelines and documentation standards
Requirements
- demonstrated ability in data engineering or a similar role with demonstrated progression in technical complexity
- Expert-level knowledge of SQL, Python, and Spark with validated ability to optimize performance at scale
- Deep understanding of data modeling, architecture principles, and design patterns
- Strong proficiency in cloud platforms (AWS, GCP, or Azure) and IaC tools like Terraform or AWS CloudFormation
- Extensive experience with modern data warehousing solutions and data lake architectures
- Advanced knowledge of orchestration tools (Airflow, Dagster, Prefect, AWS Step Functions)
- Confirmed experience with dbt or similar transformation tools at enterprise scale
- Strong background in implementing and carrying out data governance, security, and compliance practices
- Experience mentoring engineers and leading technical initiatives
- Excellent social skills with the ability to translate technical concepts to non-technical collaborators
Preferred Qualifications
- Knowledge of machine learning operations (MLOps) and ML platform development
- Experience with monitoring and observability tools such as DataDog, Grafana, Phenomenal Expectations, and Elementary
- Track record of driving technical strategy and architecture decisions
- Experience with data mesh or similar distributed data architectures
This is a Hybrid position. We work in our centrally located office in downtown Seattle three days a week (M, T, and Th).
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.
