Senior Data Analyst

Description

Ciklum is looking for a Senior Data Analyst to join our team full-time in Ukraine.

We are a custom product engineering company that supports both multinational organizations and scaling startups to solve their most complex business challenges. With a global team of over 4,000 highly skilled developers, consultants, analysts and product owners, we engineer technology that redefines industries and shapes the way people live.

About the role :

As a Senior Data Analyst, become a part of our Micro-Segmentation AI / ML Platform team.

In this role, you will lead data analysis efforts—ensuring data quality, cataloging, and governance—while delivering actionable insights that drive strategic decisions in network security and segmentation. We’re a dynamic team building the next-generation micro-segmentation platform at the intersection of AI / ML and network security. Our solution helps enterprises automatically classify, monitor, and enforce fine-grained policies across millions of flows—reducing attack surfaces and accelerating incident response.

What Are We Looking For?

An experienced data professional who excels in analyzing production data for quality and insight, driving improvements and informing strategic decisions. You’ll partner with Observability Engineers, ML Scientists, Data Engineering, and DevOps to turn raw telemetry into intelligence.

Responsibilities

• Business Intelligence & Reporting : Collaborate with stakeholders (security, product, operations) to define key metrics and reporting requirements Design, build, and maintain BI dashboards that surface ingestion health, policy effectiveness, and segmentation drift Continuously refine reports and visualizations (Grafana, Looker, Tableau, or Power BI) to meet evolving needs
• Data Analysis & Insights : Analyze large-scale flow logs, policy-violation records, and asset inventories to uncover trends and anomalies Lead deep-dive investigations—., correlating configuration changes to incident rates or unexpected segmentation gaps Ensure all ETL pipelines (Airflow-orchestrated Spark jobs) deliver accurate, timely data
• Data Quality & Governance : Define and enforce data-quality rules (schema validation, de-duplication, anomaly detection) Maintain a comprehensive data catalog with lineage tracking Partner with Data Engineering to automate quality checks and metadata capture
• Collaboration & Communication : Present complex analyses in clear, concise reports to both technical and non- technical audiences

Requirements

What's in it for you