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.
Smarter Infrastructure for the AI Era:
We make data efficient, safe, and ready for scale—think smarter, more foundational infrastructure for the AI era. Our technology integrates directly with modern data stacks like Snowflake, Databricks, and S3-based data lakes, enabling:
60%+ reduction in storage costs and up to 60% lower compute spend
3x faster data processing
20% platform efficiency gains
Trusted by Industry Leaders
Enterprise leaders globally already rely on Granica to cut costs, boost performance, and unlock more value from their existing data platforms.
A Deep Tech Approach to AI
We’re unlocking the layers beneath platforms like Snowflake and Databricks, making them faster, cheaper, and more AI-native. We combine advanced research with practical productization, powered by a dual-track strategy:
Research: Led by Chief Scientist Andrea Montanari (Stanford Professor), we publish 1–2 top-tier papers per quarter.
Product: Actively processing 100+ PBs today and targeting Exabyte scale by Q4 2025.
Backed by the Best
We’ve raised $60M+ from NEA, Bain Capital, A Capital, and operators behind Okta, Eventbrite, Tesla, and Databricks.
Our Mission
To convert entropy into intelligence, so every builder—human or AI—can make the impossible real.
We’re building the default data substrate for AI, and a generational company built to endure beyond any single product cycle.
WHAT YOU’LL DO
This is a technical leadership role for an experienced systems builder who wants to define how AI data infrastructure scales from hundreds of PBs to exabytes.
Architect and lead the evolution of Granica’s distributed data systems—catalogs, metadata stores, ACID layers, schema evolution frameworks.
Advance data and storage efficiency. Design adaptive compaction, caching, and indexing strategies that minimize I/O and latency.
Drive platform reliability & observability. Define SLOs, chaos drills, and metrics frameworks across Spark/Kafka/Flink fleets.
Mentor and scale teams. Conduct design reviews, set technical standards, and guide high-impact engineers.
Collaborate with AI infra & research. Align platform evolution with model training and inference data needs.
Publish and represent Granica externally. Contribute to research or OSS; help shape the future of AI-scale data systems.
WHAT WE’RE LOOKING FOR
You’ve shipped distributed systems at scale and can both design architectures and guide others in executing them.
Core Skills
7+ years in distributed systems, storage, or large-scale data infrastructure.
Deep expertise in system design, scalability, and performance optimization.
Strong coding skills in Java, Scala, Go, or C++, with disciplined testing and observability.
Proven leadership across cross-functional or multi-team projects.
Demonstrated success driving cost/performance improvements or platform reliability gains.
Desired Skills
Experience with table formats (Iceberg, Delta, Hudi), query engines (Trino, Druid, Presto), or metadata/catalog systems.
Contributions to open-source or published technical work in data infrastructure.
Operating cloud-scale Spark/streaming fleets with strong observability.
Prior experience mentoring and scaling technical teams.
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.
COMPENSATION & BENEFITS
Competitive salary and meaningful equity
Unlimited PTO + quarterly recharge days
Premium health, vision, and dental
Team offsites, deep tech talks, and learning stipends
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.
Top Skills
What We Do
Massive-scale data should be an asset — not a liability.
At Granica, we’re building a state-of-the-art AI efficiency, data optimization and compression platform designed to make cloud-scale data cheaper, faster, safer and more intelligent.
As enterprises generate and store unprecedented volumes of data, traditional infrastructure can’t keep up — costs explode, performance lags, and privacy becomes harder to enforce. Granica changes that. We sit beneath the lakehouse — optimizing the data itself through advanced lossless compression, intelligent data selection, and built-in privacy preservation. Our platform enables enterprises to cut cloud data costs by up to 80% while improving performance and reducing operational complexity.
This is deep infrastructure — already deployed in live production environments, operating across hundreds of petabytes of enterprise data.
Why Work With Us
We’re a tight-knit team combining -->
* Fundamental research in compression, data systems, and information theory
* World-class systems engineering across storage, cloud infrastructure, and security
* A shared obsession with performance, scale, and clean design
Gallery
Granica Offices
Hybrid Workspace
Employees engage in a combination of remote and on-site work.
