Zipher is building the Autonomous Execution Layer for cloud data and AI workloads. Backed by $50M in funding , we dynamically orchestrate clusters, predict bottlenecks, and auto-heal infrastructure in real time — with zero human intervention . Our platform runs in production at global enterprise customers, including Fortune 500 companies , delivering mission-critical resilience and sub-second optimization We are looking for a Data Analyst to own the intelligence layer on top of Zipher’s autonomous execution engine. You will turn enterprise-scale telemetry from production data and AI workloads into the metrics, models, and answers that engineering, product, and executives run on.
What You’ll Do
* Own end-to-end analytics for core product areas: cost optimization, SLA, failure rates, and workload efficiency
* Define and instrument the product KPIs and dashboards used daily by engineering, product, and the executive team
* Build and maintain production-grade data pipelines and models on enterprise-scale telemetry — Databricks/Spark, logs, metrics, and traces
* Partner closely with backend and ML engineers to translate complex multi-cloud performance data into actionable platform intelligence
* Run deep-dive analyses and experiments that validate features, quantify impact, and uncover new optimization opportunities
What We Offer
* A chance to build the core execution engine for a new category of autonomous data platform High ownership from day one : real architectural influence, direct exposure to founders, and responsibility for mission-critical systems
* Technical, high-velocity team that values curiosity, speed, and engineering craftsmanship Top-of-market compensation and meaningful equity
Ready to build the data engine behind autonomous AI workloads? Hit Apply.
What You’ll Do
* Own end-to-end analytics for core product areas: cost optimization, SLA, failure rates, and workload efficiency
* Define and instrument the product KPIs and dashboards used daily by engineering, product, and the executive team
* Build and maintain production-grade data pipelines and models on enterprise-scale telemetry — Databricks/Spark, logs, metrics, and traces
* Partner closely with backend and ML engineers to translate complex multi-cloud performance data into actionable platform intelligence
* Run deep-dive analyses and experiments that validate features, quantify impact, and uncover new optimization opportunities
What We Offer
* A chance to build the core execution engine for a new category of autonomous data platform High ownership from day one : real architectural influence, direct exposure to founders, and responsibility for mission-critical systems
* Technical, high-velocity team that values curiosity, speed, and engineering craftsmanship Top-of-market compensation and meaningful equity
Ready to build the data engine behind autonomous AI workloads? Hit Apply.
Requirements:
What You’ll Bring Experience in an elite IDF technology/intelligence unit (e.g. 8200, Mamram, Matzpen) ?3–6+ years in Data Analytics, Product Analytics, or Analytics Engineering , including ownership of analysis that drove real product decisions Advanced, production-level SQL and strong Python (pandas, numpy; scikit-learn is a plus)
* Proven experience with large-scale datasets , scalable data models, and end-to-end data products running in production
* Strong applied statistics and exploratory analysis , plus the technical storytelling to make findings land with non-technical stakeholders
* A high-agency, engineering-first mindset : you enjoy ambiguous, high-leverage problems and take responsibility for the correctness and quality of what you ship
Nice to Have
* Experience with Databricks, Snowflake, Spark , AWS Athena/Glue, dbt, or Airflow/Prefect
* Background in cloud infrastructure metrics , compute engines, or MLOps/AIOps telemetry B.Sc. in Computer Science, Industrial Engineering, Statistics, or Mathematics , or equivalent
What You’ll Bring Experience in an elite IDF technology/intelligence unit (e.g. 8200, Mamram, Matzpen) ?3–6+ years in Data Analytics, Product Analytics, or Analytics Engineering , including ownership of analysis that drove real product decisions Advanced, production-level SQL and strong Python (pandas, numpy; scikit-learn is a plus)
* Proven experience with large-scale datasets , scalable data models, and end-to-end data products running in production
* Strong applied statistics and exploratory analysis , plus the technical storytelling to make findings land with non-technical stakeholders
* A high-agency, engineering-first mindset : you enjoy ambiguous, high-leverage problems and take responsibility for the correctness and quality of what you ship
Nice to Have
* Experience with Databricks, Snowflake, Spark , AWS Athena/Glue, dbt, or Airflow/Prefect
* Background in cloud infrastructure metrics , compute engines, or MLOps/AIOps telemetry B.Sc. in Computer Science, Industrial Engineering, Statistics, or Mathematics , or equivalent
This position is open to all candidates.
