We strongly encourage people of color, lesbian, gay, bisexual, transgender, queer, and non-binary people, veterans, parents, and individuals with disabilities to apply. Banff is an equal opportunity employer and welcomes everyone to our team. If you need reasonable adjustments at any point in the application or interview process, please let us know.
Banff is a tech-enabled talent management start-up tailor-made for executives, investors, corporations, and their networks. We’re a team of talent experts, engineers, machine learning researchers, designers and operations specialists on a mission to ensure no one’s career ambitions are left to chance. Through a two-sided marketplace, we serve exceptional executive leaders and the investors, corporations, search firms, and connectors that covet them. We’re redesigning the executive talent space through purpose and partnership, proud to serve a diverse community of leaders with over 54% of our executive clients identifying as underrepresented in their respective positions and fields. Our platform utilizes machine learning algorithms, various data sources, and our in-house experts to guide our clients in their career journeys, providing them with the data, insights, and connections to make critical career decisions.
We are working to help people achieve purpose in their careers and life - to not rely on chance but instead take control of their future.
We are establishing our engineering team with its first few founding members. As a founding backend engineer at Banff, you will contribute to the company’s growth by extending and building our backend and data infrastructure. You will help grow and shape our engineering team culture and infrastructure. You will work closely with our growing team of engineers, product managers, machine learning researchers, executive advisors, and operational specialists and see all parts of the business and help shape the technology culture from its earliest stages.
Design and build a new reporting infrastructure to generate recurring insights and recommendations for our executive clients
Work with our machine learning researcher to design and build a network-based recommendation system to help our executive clients create more meaningful and impactful career connections
Assist in redesigning our MVP production data pipelines to normalize and standardize unstructured data for the use in recommendation systems
Extend existing APIs to surface new recommendations, insights, and normalized data to Banff clients
Refactor the existing candidate API endpoints to move from overly-complex schema and ORM abstractions to simple and extendable paradigms
25-30 minute initial phone call with the hiring manager, getting to know who you are, what you're looking for, and what you've built in the past.
45-60 minute remote code review and discussion session.
45-60 minute remote technical system design interview.
1.5-2 hours of cross-functional remote interviews with Product and other team members to learn more about problem space, business and team culture.
Ecosystems of Generosity
Generosity across the Banff community is critical to our mission.
We believe inclusion and diversity amplify impact, and our success requires reaching beyond what and who we know.
Talent First
Our clients’ well-being is a priority in every decision we make.
We are humble and grounded. Our role is to enable our clients’ ambitions.
Open and Transparent
We believe vulnerability - by us and by our clients - can be used to identify and inspire action.
We commit to absolute honesty in feedback and advice
You have 5+ years of experience building and maintaining backend systems including data storage systems and pipelines, or can demonstrate a similar proficiency
You are skilled at building APIs using technologies such as (but not limited to) Python, FastAPI / Flask / Django (we use FastAPI)
You’re well versed in service and infrastructure best practices such as testing, CI/CD, monitoring, profiling, and documentation (we use Docker and Heroku)
You have 3+ years of experience with designing and maintaining data warehouses (e.g Postgres), data lakes, ETL and production grade data pipelines
You have designed and built distributed full-text search systems using technologies such as Elasticsearch, Solr, or Algolia (we use Algolia)
You're an excellent communicator, and are able to clearly distill complex topics for both technical and non-technical team members, especially in a remote async-first environment
You are a critical thinker who is able to break down large problems and deeply understand the tradeoffs involved in solving them
You have built data platforms from scratch
You have experience with helping design and create machine learning based recommendation systems, e.g. network based recommendation systems
You are familiar with data privacy and security standards such as GDPR and CCPA
Learners with a growth mindset
Critical thinkers and data driven
Collaborative and like working as part of a tight knit team
Appreciate open communication and feedback for personal, team, and product development
Humble and kind
Like the early-stage startup environment of having autonomy and ownership over the products you build
You know that it takes a village to create a successful business with real impact
Applicants must be authorized to work in the United States. Please note this is a fully remote position (#LI-remote).
Expected annual salary range is $130,000-$170,000.
On top of interesting and impactful work, Banff provides:
Unlimited PTO that we actually use and encourage team members to take
All major holidays off + full week shutdown the last week of December
Remote-first team
Yearly team off-sites to ensure we connect in-person, not just online
High quality medical, dental, and vision health insurance coverage at zero employee contribution
Access to mental health therapy through Talkspace and mental health support through Health Advocate
Access to 24/7 virtual health via Teladoc
Access to One Medical
Up to 4 months of paid parental leave
Quarterly WiFi credit to support remote work
A commitment to using and supporting open-source
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