At Beam, we’re building technology for the social safety net that empowers institutions and government leaders to deliver funding equitably, efficiently, and securely to those who need it most. Our research-backed approach streamlines the administration of benefits while also addressing common pitfalls in program management — including racial bias, inefficiency, compliance risk, and lack of transparency and monitoring — to quickly deliver funds to those with the greatest need. Since 2020, we’ve delivered more $300M in cash grants to hundreds of thousands of people in need through our platform.
Beam is a Series A stage, venture-backed company and has received support from many of the leading impact and postsecondary success investors and has also received non-dilutive support from foundations like the Bill and Melinda Gates Foundation.
Job Overview:
Our team is seeking an experienced Senior Data Engineer who is passionate about building a more equitable social safety net with technology! Data is a key to many aspects of cash assistance programs, from understanding program health, to coordinating service, to planning future programs. Machine learning and AI have the potential to transform workflows managed through our product. This environment means that our data platform has high potential for impact, both for our customers and for their constituents.
Our first data engineer will help scale and empower our small, but mighty data team and help architect a robust data platform primed for growth. You will partner closely with collaborators on the data, product, engineering, design, and other teams, to create and optimize one-of-a-kind, data-driven products that will make it easier for low-income Americans to participate in government-funded assistance, stipend, and incentive programs. This role will span all aspects of the data journey, from ETL through to productionizing applications. Our data and analytics infrastructure is built on cloud technologies. We use many GCP products and services. We recently started to use Dagster on Kubernetes for orchestration. The data team uses BigQuery as our warehouse, Hashboard as our BI platform, and we work with Heap for our clickstream collection. The engineering team uses Node and React Javascript/Typescript frameworks, GraphQL, and a number of cloud tools and skills on GCP.
What you will do:
In your first 3mo, you may do much of the following:
- Get to know your colleagues, our product, our customers, and our ambitions
- Create a couple ETL pipelines from microservice databases or other services into a centralized warehouse, unlocking new projects for teammates
- Partner with other teammates and your manager to develop opinions and draw up plans for key parts Beam’s data platform, such as a data lake, a modeling platform, and/or a datamart
- Partner with teammates to refactor, contribute to, or make a microservice or data app that gets the team’s work into the hands of users (internal or external)
In your first year, you will:
- Work with your colleagues to define the data engineering role at Beam
- Partner closely with our Software Engineering and DevOps teams to build scalable and repeatable data apps or ML microservices using Cloud Run, Kubernetes, Dagster and/or other tools and services
- Enable scaled ETL across lots of different tools and services within our ecosystem, creating new ways for your close colleagues to generate value
- Begin to establish Beam’s very own data platform, including scalable and repeatable processes and tools for productionizing machine learning models and other data products
That whole time, and always, you will:
- Serve as an advocate for engineering best practices internally, as well as within the social safety net community
- Mentor and upskill teammates to keep up with the stack you’re setting up
- Create high-quality documentation as you work, enabling your colleagues to learn as you build
- Participate in conversations that set the medium-to-long term agenda for Beam’s data platform
- Think critically about the needs of beneficiaries and our partner organizations and leverage that understanding to build our data capabilities responsibly
Ability, Experience, and Skills
- Data Skills - Strong SQL and Python skills are expected, including familiarity with common data libraries (e.g. Numpy, Pandas, Polars). Experience with pipeline orchestration software (e.g. Airflow, Dagster, Prefect) and data streaming technologies (e.g. airbyte, datastream, artie, fivetran, or your own flavor), especially in a cloud data environment, such as AWS, Azure, or GCP is essential for this role. A background working with production machine learning will set candidates apart.
- Cloud/Engineering - A functional understanding of cloud service architectures for data applications (e.g. managed Kubernetes, elastic compute) is essential to this role. Experience creating and/or leveraging REST or GRPC APIs and experience with Terraform or other infrastructure-as-code technologies are preferred. A basic grasp of cloud security practices (encryption, secret management, proxies, etc), any of GraphQL, Typescript/Javascript and related frameworks (Node, React, e.g.) are also important for productive partnership with the engineering team, but are nice-to-haves.
- Stewardship - Data governance and stewardship are more important in our sector than some others. A strong desire to produce responsibly crafted work is therefore a must. A good candidate tends to opt for the most reasonable or forward-thinking solution over the flashiest or easiest. They are comfortable communicating best-practices to non-technical stakeholders, as well as supporting the development of customer-facing language to describe your work. They have experience creating and maintaining products that require a high degree of service level. They have experience establishing data retention, access, or other policies related to governance and can fluidly adapt their work to fit within governance frameworks.
- Subject Matter - Experience working in government technology, social impact, or at a progressive organization is preferred, but not required. A good candidate will be excited about our work, either through personal experience, professional experience, or a passion for helping others. Regardless of the connection, they are willing to develop a deep understanding of our problem space and leverage that knowledge in their work.
We recognize that the right candidate may not match 100% of the job qualifications listed above. Importantly, we want you to grow with the company, so we are open to a candidate who can do the core work and is willing to grow some competencies. Therefore, we encourage you to apply if you can demonstrate many, but not all of these skills and competencies and are willing and excited to grow!
