Lakehouse Core Engineer

Granica is pioneering data optimization for large-scale AI and analytics. Our unified platform enables enterprises to dramatically reduce storage and compute costs while accelerating data pipelines - unlocking faster, more efficient access to intelligence at petabyte scale.

At the heart of Granica's mission is the belief that data is the foundation of modern AI. Realizing its full potential requires rethinking how data is managed, moved, and made useful. That's why we bring together world-class talent in AI research, distributed systems, and business to tackle the hardest challenges in data at scale.

Backed by leading investors including NEA and Bain Capital Ventures, Granica is helping the world's most forward-thinking organizations build a smarter, more cost-efficient data layer for the AI era.

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 deep systems role for someone who lives and breathes lakehouse internals, knows open source cold, and wants to push the limits of what’s possible with Delta, Iceberg, and Parquet at petabyte scale.

• Build and scale the transactional core of our data platform. Design, implement, and optimize ACID-compliant data layers based on Delta Lake and Apache Iceberg, enabling reliable time-travel queries and seamless schema evolution on petabyte-scale datasets.

• Accelerate metadata-driven performance. Develop high-performance services for compaction, caching, and metadata pruning that enable sub-50ms query planning—even across millions of file pointers.

• Optimize data layout for maximum efficiency. Work deeply with Parquet and similar formats to improve column ordering, encoding strategies (e.g., dictionary and bit-packing), and indexing methods like bloom filters and zone maps—reducing I/O and boosting scan performance by 10x.

• Develop intelligent, adaptive indexing systems. Collaborate with research to prototype indexing and partitioning strategies that automatically learn from access patterns and evolve over time—eliminating the need for manual table analysis.

• Build robust, self-healing pipelines. Design and maintain data infrastructure that scales automatically across cloud storage platforms (S3, GCS, ADLS), with built-in observability, fault tolerance, and hands-off reliability.

• Write maintainable, long-lasting systems code. Produce clean, test-driven code in Java, Scala, or Go, with clear documentation and architectural design that enables long-term extensibility.

• Optimize for human impact. Your work will directly power faster, more reliable analytics and model training. When dashboards refresh instantly and insights surface in seconds—you’ll know your work made it happen.

WHAT WE’RE LOOKING FOR

• 4+ years building distributed data systems or working on the internals of lakehouse architectures

• Deep expertise with Delta Lake, Iceberg, Hive Metastore, or similar open-source formats

• Strong programming skills in Scala, Java, or Go with production-grade quality and testing

• Experience with Spark, Parquet optimization, file compaction, and advanced query planning

• Ability to optimize for both performance and reliability across cloud storage layers (S3, GCS, ADLS)

• Excited by the opportunity to shape the next layer of AI-ready infrastructure from the ground up

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

• Flexible hybrid work (Bay Area HQ)

• 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.