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. WHAT WE'RE LOOKING FOR- - 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 NICE-TO-HAVES: - 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). COMPENSATION & BENEFITS - 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.