Granica is redefining how enterprises prepare and optimize data at the most fundamental layer of the AI stack—where raw information becomes usable intelligence. Our technology operates deep in the data infrastructure layer, making data efficient, secure, and ready for scale.We eliminate the hidden inefficiencies in modern data platforms—slashing storage and compute costs, accelerating pipelines, and boosting platform efficiency. The result: 60%+ lower storage costs, up to 60% lower compute spend, 3× faster data processing, and 20% overall efficiency gains.
Why It Matters
Massive data should fuel innovation, not drain budgets. We remove the bottlenecks holding AI and analytics back—making data lighter, faster, and smarter so teams can ship breakthroughs, not babysit storage and compute bills.
Who We Are
- World renowned researchers in compression, information theory, and data systems
- Elite engineers from Google, Pure Storage, Cohesity and top cloud teams
- Enterprise sellers who turn ROI into seven‑figure wins.
Powered by World-Class Investors & Customers
$65M+ raised from NEA, Bain Capital, A* Capital, and operators behind Okta, Eventbrite, Tesla, and Databricks. Our platform already processes hundreds of petabytes for industry leaders
Our Mission:
We’re building the default data substrate for AI, and a generational company built to endure.
What We’re Looking For
You’ve built systems where
petabyte-scale performance, resilience, and clarity of design all matter
. You thrive at the intersection of infrastructure engineering and applied research, and care deeply about both how something works and how well it works at scale. We're looking for someone with experience in:
- Lakehouse and Transactional Data Systems Proven expertise with formats like Delta Lake or Apache Iceberg, including ACID-compliant table design, schema evolution, and time-travel mechanics.
- Columnar Storage Optimization Deep knowledge of Parquet, including techniques like column ordering, dictionary encoding, bit-packing, bloom filters, and zone maps to reduce scan I/O and improve query efficiency.
- Metadata and Indexing Systems Experience building metadata-driven services—compaction, caching, pruning, and adaptive indexing that accelerate query planning and eliminate manual tuning.
- Distributed Compute at Scale Production-grade Spark/Scala pipeline development across object stores like S3, GCS, and ADLS, with an eye toward autoscaling, resilience, and observability.
- Programming for Scale and Longevity Strong coding skills in Java, Scala, or Go, with a focus on clean, testable code and a documented mindset that enables future engineers to build on your work, not rewrite it.
- Resilient Systems and Observability You’ve designed systems that survive chaos drills, avoid pager storms, and surface the right metrics to keep complex infrastructure calm and visible.
- Latency as a Product Metric You think in terms of human latency—how fast a dashboard feels to the analyst, not just the system. You take pride in chasing down every unnecessary millisecond.
- Mentorship and Engineering Rigor You publish your breakthroughs, mentor peers, and contribute to a culture of engineering excellence and continuous learning.
WHY JOIN GRANICA
If you’ve helped build the modern data stack at a large company—Databricks, Snowflake, Confluent, or similar—you already know how critical lakehouse infrastructure is to AI and analytics at scale. At Granica, you’ll take that knowledge and apply it where it matters most…at the most fundamental layer in the data ecosystem.
- Own the product, not just the feature. At Granica, you won’t be optimizing edge cases or maintaining legacy systems. You’ll architect and build foundational components that define how enterprises manage and optimize data for AI.
- Move faster, go deeper. No multi-month review cycles or layers of abstraction—just high-agency engineering work where great ideas ship weekly. You’ll work directly with the founding team, engage closely with design partners, and see your impact hit production fast.
- Work on hard, meaningful problems. From transaction layer design in Delta and Iceberg, to petabyte-scale compaction and schema evolution, to adaptive indexing and cost-aware query planning—this is deep systems engineering at scale.
- Join a team of expert builders. Our engineers have designed the core internals of cloud-scale data systems, and we maintain a culture of peer-driven learning, hands-on prototyping, and technical storytelling.
- Core Differentiation: We’re focused on unlocking a deeper layer of AI infrastructure. By optimizing the way data is stored, processed, and retrieved, we make platforms like Snowflake and Databricks faster, more cost-efficient, and more AI-native. Our work sits at the most fundamental layer of the AI stack: where raw data becomes usable intelligence.
- Be part of something early—without the chaos. Granica has already secured $65M+ from NEA, Bain Capital Ventures, A* Capital, and legendary operators from Okta, Tesla, and Databricks.
- Grow with the company. You’ll have the chance to grow into a technical leadership role, mentor future hires, and shape both the engineering culture and product direction as we scale.
Benefits:
- Highly competitive compensation with uncapped commissions and meaningful equity
- Immigration sponsorship and counseling
- Premium health, dental, and vision coverage
- Flexible remote work and unlimited PTO
- Quarterly recharge days and annual team off-sites
- Budget for learning, development, and conferences
- Help build the foundational infrastructure for the AI era
Granica is an equal opportunity employer.
We celebrate diversity and are committed to creating an inclusive environment for all employees.
