Data Infrastructure Engineer, Onehouse
Pre-built data lakehouse foundation
Open for applications
Pre-built data lakehouse foundation
21-100 employees
Open for applications
21-100 employees
Company mission
To aid companies of all sizes in supercharging their data engineering/data science, by automating painful data infrastructure buildout.
Role
Who you are
- Strong, object-oriented design and coding skills (Java and/or C/C++ preferably on a UNIX or Linux platform)
- Experience with inner workings of distributed (multi-tiered) systems, algorithms, and relational databases
- You embrace ambiguous/undefined problems with an ability to think abstractly and articulate technical challenges and solutions
- An ability to prioritize across feature development and tech debt with urgency and speed
- An ability to solve complex programming/optimization problems
- An ability to quickly prototype optimization solutions and analyze large/complex data
- Robust and clear communication skills
Desirable
- Experience working with database systems, Query Engines or Spark codebases
- Experience in optimization mathematics (linear programming, nonlinear optimization)
- Existing publications of optimizing large-scale data systems in top-tier distributed system conferences
- PhD degree with 2+ years industry experience in solving and delivering high-impact optimization projects
What the job involves
- Design new concurrency control and transactional capabilities, that maximizes throughput for competing writers
- Design and implement new indexing schemes, specifically optimized for incremental data processing and analytical query performance
- Design systems that help scale and streamline metadata and data access from different query/compute engines
- Solve hard optimization problems to improve the efficiency (increase performance and lower cost) of distributed data processing algorithms over a Kubernetes cluster
- Leverage data from existing systems to find inefficiencies, and quickly build and validate prototypes
- Collaborate with other engineers to implement and deploy, safely rollout the optimized solutions in production
Our take
Managing the ballooning volume of unstructured data is becoming a tough task for enterprise companies. The traditional solution, data lakes, doesn’t offer management or transaction capabilities. This lack of oversight could lead to data violations, that are becoming more costly as regulations tighten. Onehouse is catering to the growing number of businesses opting for an alternative, the so-called ‘data lakehouse’. It's hybrid architecture that offers the management and transaction capabilities of a warehouse, with the cost-effectiveness of a data lake.
The Onehouse platform is a management plane that helps businesses set up a data lakehouse without having to invest the time and expertise in building one from scratch. With an open data format, it can be used to work with protected or sensitive data; it also allows companies to easily pull their data from Onehouse without egress fees if they decide to leave the service.
Onehouse has carved out an astute market niche for itself: businesses under increasingly close scrutiny, but with ballooning data pools, who don’t need to build out highly customized lakehouses. For the moment, this tends to be top-tier enterprises, which is how Onehouse has secure deep pocketed clients like Walmart, Amazon, Zendesk, and Uber. As the first company to make fully managed data lakes possible, it is no surprise that it has received substantial funding. This will allow it to continue advancing the platform and grow its team to meet market demand.
Steph
Company Specialist
Insights
Company
Funding (last 2 of 3 rounds)
Jun 2024
$35m
SERIES B
Feb 2023
$25m
SERIES A
Total funding: $68m
Company benefits
- Health, dental, vision
- Unlimited PTO
- Paid parental leave
- Equity
- Flexible schedule
- Contribute directly to open source
- Work and grow with an experienced team
Company HQ
Sharon Heights, Menlo Park, CA
Articles
Leadership
Vinoth Chandar
(CEO)Previously a Principal Engineer at Uber, then Confluent, and subsequently served as VP of Apache Hudl at The Apache Software Foundation.
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