Bigeye

Backend Engineer

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About Bigeye

At Bigeye, our mission is making it a delight to work with data every day. We built some of the most widely adopted tools at companies like Uber and saw how fast teams move when they have a great data toolchain. Now Bigeye is building best-of-breed tools for anyone who eats, sleeps, and breathes data: analysts, data scientists, and data engineers around the world.

The DevOps movement changed the world of working with infrastructure. The DataOps movement is just getting started. Come help us write the first chapter.

About the job

Today, we’re focused on one of the most painful aspects of DataOps: observability and outages. Most teams still discover data outages – duplicated, missing, and unexpected data – after they impact application features, dashboards, ML models, and ultimately their stakeholders. We’re building a data observability platform to monitor their data content and alert them early so they can triage and respond instantly.

What you'll be doing
  • Design and develop product solutions to the needs of our earliest customers
  • Keep Bigeye reliable and performant as customers deploy it on hundred of tables, thousands of columns, and billions of rows
  • Design and contribute to an engineering platform that keeps us iterating rapidly and efficiently
  • Hone the team’s engineering best practices and shared toolset
  • Collaborate with the design and data science teams to research, development, and implement solutions
Tech Stack

Java, Python, REST APIs, RabbitMQ, Protobuf, Datadog, Docker

You should apply if you have
  • 4+ years of experience in Java or Python
Bonus
  • Experience working within a Service Oriented Architecture.
  • Experience designing, building, and supporting a user-facing product.
  • A desire to learn and grow as an engineer.
  • Proven passion for uncovering and solving the real customer problem. We think this is the core of a successful product.
  • Excitement about being an early engineer. You’ll be defining our engineering best practices, choosing our shared tools, and helping us build a world-class team.
  • Clear and straightforward communication. We’ll be moving fast and building some complex products together, so clarity matters.

Company

Bigeye

Bigeye

Headquarters
San Francisco

Website
www.bigeye.com

Company Size
10-50

Funding Round
Series A

Total Funding
$21M

Industry
Enterprise Technology

Visa Sponsorship
Available

Remote Friendly
Yes

Team and Leadership

Hiring Manager
"My favorite thing about working at Bigeye is the people. Our engineering process is highly collaborative. Everyone gets a chance to contribute, and we put getting to the best solution above our own egos."
Team
Hear from a teammate
"At Bigeye, I enjoy working with great people. We leverage our collective experience in data systems to help other companies evaluate their data. The collaboration and transparency here has been wonderful."
Company Leaders

The Interview Process

The average turnaround time for the interview process is 2 weeks.

Round 1 - Recruiter Screen
Time - 30 min
Intro to Bigeye - General discussion about the candidate's background and skills to make sure they are a good fit. Katie shares information about bigeye.
Round 2 - Hiring Manager Screen
Time - 45 min
A more technical discussion about their past work experience. Technologies used, what their responsibilities were. Looking for signal on technical communication. Also a discussion about their career goals (eg., do they want to go into management or remain an IC). AJ shows the product and answers any question the candidate may have.
Round 3 - Tech Screen
Time - 60 min
Data structures and basic algos. Code up a solution to a programming problem. We use codinghire.com, the candidate can use their preferred programming language.
Final Round
Total Time - 3.5 hr
Code Challenge
Time - 60 min
Data structures and basic algos. Code up a solution to a programming problem. We use codinghire.com, the candidate can use their preferred programming language.
Software architecture and design
Time - 60 min
High level system design, no coding. Looking for an understanding of software architecture.
Team Collaboration
Time - 30 min
A discussion with someone from a different function with whom the candidate will work, e.g., Frontend eng, Designer, Product Manager, Data Scientist. A discussion about their experience working with folks in other roles.
Cofounder Discussion (CTO)
Time - 30 min
A discussion with the CTO about about the role and opportunities that match their goals. Can discuss the eng team, VCs, customer pain / opportunity of new big market. An opportunity for the candidate to ask questions of the cofounders.
Cofounder Discussion (CEO)
Time - 30 min
A discussion with the CEO about about the role and opportunities that match their goals. Can discuss the eng team, VCs, customer pain / opportunity of new big market. An opportunity for the candidate to ask questions of the cofounders.

Diversity & Inclusion

Engineering numbers

The Bigeye team is committed to filling at least 30% of our positions with women and individuals from underrepresented groups.

Engineering Values

Solve real problems

Bigeye solves real problems for real data teams, and Bigeye Engineering prioritizes those problems above all else. Engineering must be equally aware of customer needs as sales and customer support, and constantly reevaluate whether what we are building is relevant.

Use boring technology

Success comes from building great products that solve real challenges for customers, not from satisfying our own technical curiosities. If a solution for a problem exists internally, we leverage or extend the solution. If this is a new space, we evaluate existing external solutions before committing to building something from scratch.

Build fast, zoom out often

We make customers happy by solving their problems faster than anyone else can (including themselves!), and that means not getting crushed by our scale or complexity. Bigeye Engineering makes time to extract commonalities into the platform layer, pay down technical debt, and with more information around problem spaces, rethink designs and architectures, and rebuild when we have to.

Benefits and Policies