Join Granica’s core engineering team to design and scale systems powering data workflows, automation, and analytics. This is a deep engineering role—not feature delivery.
What You’ll Do-Build backend APIs and scalable data pipelines (Python, PySpark).
Work with modern data lakehouse/warehouse tech (Iceberg, Delta Lake, Snowflake, Databricks).
Orchestrate workflows (Airflow) and optimize big data frameworks.
Manage infra as code (Terraform) and ensure reliability with monitoring/logging.
Collaborate across teams and with customers to solve complex data challenges and design seamless integration solutions.
Drive best practices in scalability, reliability, and cost efficiency.
5+ years in software/data engineering or infrastructure roles
Strong Python skills (backend APIs a plus)
Proven ability to build scalable data pipelines from scratch
Hands-on with Apache Iceberg/Delta Lake + Snowflake/Databricks
Workflow orchestration expertise (Airflow, Luigi, etc.)
Big data frameworks experience (Spark, Hadoop)
Familiar with monitoring/analytics tools (Prometheus, Grafana, ELK, Datadog)
Skilled in designing scalable, reliable, cost-efficient systems
Experience with large-scale distributed data architectures
Thrives in fast-paced startup environments
Excellent problem-solving, communication, and customer-facing skills
Hands-on experience with Terraform or other infrastructure-as-code tools.
Familiarity with security and privacy best practices in data processing pipelines.
Exposure to cloud platforms (AWS, GCP, Azure) and containerisation (Docker, Kubernetes).
Competitive salary, meaningful equity, and performance bonus for top performers
401(k) with company match, comprehensive health coverage, and unlimited PTO
Daily catered meals in our Mountain View office
Support for research, publication, and conference participation
At Granica, you'll help build the next generation of enterprise AI—from exabyte-scale data infrastructure, Large Tabular Models (LTMs), and stateful AI agents. Together, we're creating the infrastructure that enables enterprises to own their data, own the intelligence built on it, and scale both efficiently.
Skills Required
- 5+ years of experience in software engineering, data engineering, or infrastructure roles
- Strong Python skills
- Experience building scalable data pipelines from scratch
- Hands-on experience with Apache Iceberg or Delta Lake and Snowflake or Databricks
- Workflow orchestration expertise with Airflow, Luigi, or similar tools
- Experience with big data frameworks such as Spark or Hadoop
- Familiarity with monitoring and analytics tools such as Prometheus, Grafana, ELK, or Datadog
- Experience designing scalable, reliable, cost-efficient systems and distributed data architectures
- Excellent problem-solving, communication, and customer-facing skills
- Experience with Terraform or other infrastructure-as-code tools
- Familiarity with security and privacy best practices in data processing pipelines
- Exposure to AWS, GCP, or Azure
- Experience with Docker or Kubernetes
Granica Compensation & Benefits Highlights
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Healthcare Strength — Health coverage is described as premium medical, dental, and vision, with one listing noting fully paid employee premiums and 75% coverage for dependents. This depth of coverage is highlighted across company and job‑profile materials.
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Leave & Time Off Breadth — Time off is presented as unlimited PTO paired with paid holidays and sick time, plus quarterly company‑wide recharge days to encourage real downtime. The combination supports rest beyond flexibility alone.
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Strong & Reliable Incentives — Quarterly performance bonuses for all roles are consistently advertised as part of total rewards alongside competitive salary. This regular cadence signals dependable incentive pay rather than one‑off perks.
Granica Insights
What We Do
Our mission is to remove inefficiency from the foundation of AI. By combining new research in information theory, probabilistic modeling, and distributed systems, we’re creating self-optimizing data infrastructure that continuously improves how information is represented and used by intelligent systems.
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, infrastructure, and research led by our Chief Scientist & Stanford Prof. Andrea Montanari * A shared obsession with performance, scale, and clean design
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Granica Offices
OnSite Workspace
