Software Engineer, Distributed Data Systems (US)
Indexed description
We are a team of self-driven, inspired, and seasoned builders that have created large-scale data systems and globally distributed platforms that sit at the heart of some of the largest enterprises out there including Uber, Snowflake, AWS, Linkedin, Confluent and many more. Riding off a fresh $35M Series B backed by Craft, Greylock and Addition Ventures, we're now at $68M total funding and looking for rising talent to grow with us and become future leaders of the team. Come help us build the world's best fully managed and self-optimizing data lake platform!
- If not local to Bay Area, you must be willing to relocate within 45 days and onboard in person for one week. Relocation package provided.
The Impact You Will Drive:
- Design new concurrency control and transactional capabilities that maximize 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.
- 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.
- Nice to haves (but not required):
- 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.
- Competitive Compensation; the estimated base salary range for this role is $215,000 - $250,000
- Equity Compensation; our success is your success with eligible participation in our company equity plan
- Health & Well-being; we'll invest in your physical and mental well-being with up to 90% health coverage (50% for spouses/dependents) including comprehensive medical, dental & vision benefits
- Financial Future; we'll invest in your financial well-being by making this role eligible to contribute to our company 401(k) or Roth 401(k) retirement plan
- Location; we are a remote-friendly company (internationally distributed across N. America + India), though some roles will be subject to in-person requirements in alignment with the needs of the business
- Generous Time Off; unlimited PTO (mandatory 1 week/year minimum), uncapped sick days and 11 paid company holidays
- Company Camaraderie; Annual company offsites and Quarterly team onsites @Sunnyvale HQ
- Food & Meal Allowance; weekly lunch stipend, in-office snacks/drinks
- Equipment; we'll provide you with the equipment you need to be successful and a one-time $500 stipend for your initial desk setup
- Child Bonding!; 8 weeks off for parents (birthing, non-birthing, adoptive, foster, child placement, new guardianship) - fully paid so you can focus your energy on your newest addition
We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.
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