דרושים » תוכנה » מנהל /ת דאטה בענן - ג'וניור לארגונים מובילים

Were looking for a Junior Data Analyst whos eager to learn, explore big data, and turn raw information into real insights. Youll work closely with our data and R&D teams, analyzing patterns, supporting reports, and contributing to smarter product and business decisions.
This is a great opportunity to grow your analytical and technical skills in a cutting-edge cybersecurity environment.
What Youll Be Doing:
Support analysis of large, complex data sets to identify trends and insights.
Help produce reports on product performance, user behaviors, and new features.
Work closely with multiple teams to answer data-related questions and support decision-making.
Assist in automating data processes and improving reporting efficiency.
Learn and apply tools and methods for device identification and data enrichment.

Required FinOps Engineer
Job Description
As a FinOps Engineer, you'll be responsible for managing and optimizing the financial aspects of our cloud computing operations, including monitoring and controlling AI-related costs. In this role, you will work collaboratively as part of a team, demonstrate initiative, think creatively, and drive innovative solutions. You'll work closely with the CFO and VP of R&D to ensure cost efficiency, budget adherence, and financial transparency across our cloud services.
In your day-to-day, you will:
Work directly with different external hosting providers to manage hosting costs
Manage and monitor cost visibility for multi-data center architecture in a large-scale, multi-cloud environment
Work with financial teams on production-related budgets, forecasts, and expense reports
Create financial models to calculate TCO of new projects
Create financial and usage dashboards, as well as frameworks for efficiency & costs
Partner with the development, support and devops teams to encourage financial responsibility
Stay updated on industry trends and best practices in cloud cost optimization and FinOps methodologies.

We are looking for a Senior SecOps Engineer to enhance our security operations and ensure robust protection against sophisticated threats. This role is crucial for maintaining our Security Operations as a high-performing and resilient hub that can quickly adapt to emerging security challenges in the fintech industry. You will take the lead in refining our SOC capabilities by monitoring network traffic, automating processes, analyzing security incidents, managing security tools, and providing expertise to SOC analysts, without having direct management responsibilities.

The Senior SOC Engineer collaborates with cross-functional teams to build defenses, respond to incidents, and design strategies for robust cybersecurity posture.

What you will be doing:
Drive SOC workflow automation using SOAR, and oversee the full lifecycle management (deployment, tuning, operation) of core security tools like EDR aiming to increase automation coverage and consistency.
Lead Cloud Security Monitoring, including managing AWS security logs via SIEM and working with the CSPM team for proactive cloud defense.
Perform continuous Security Monitoring and Threat Detection, building custom queries and dashboards to enhance visibility across platforms.
Develop and execute Proactive Threat Hunting procedures to identify potential risks.
Enhance and coordinate the Incident Response process, working with cross-functional teams through containment, eradication, and post-incident analysis.
Collaborate with third-party vendors for managed security services and specialized tools.

As a Data Scientist, you will sit at the very core of our company. This isn't just a role about maintaining models-its about transformation. You will be the architect of a "learning machine," turning raw data into usable metrics and developing the statistical algorithms that power our business performance.

You will collaborate with Data Engineers and Product Managers to translate the "voice of the customer" into digital insights that define the industry standard.

Key Responsibilities:
Drive Actionable Insights: Analyze diverse data sources to create insights that directly fuel business growth.
Optimize Performance: Build advanced ML algorithms for bidding-utilizing classification and clustering to maximize campaign performance.
Innovate with GenAI: Leverage Generative AI techniques to query data for intelligent insights and automate decision-making.
Own the Lifecycle: Lead projects from initial exploration and Proof of Concept (POC) to scalable production environments.
Scalability & Performance: Ensure our data pipelines and ML models can handle large-scale, dynamic datasets with high efficiency.
Metric Ownership: Create and own key performance metrics that drive innovative product solutions.

It starts with you - an engineer driven to operate database systems at the highest level of reliability and performance. You care about query latency, uptime, data durability, and getting paged as little as possible. Youll operate, tune, and scale the database engines that serve the platform - from PostgreSQL to Elasticsearch, Redis to vector databases, across cloud and on-prem environments.
If you want to run the databases that power mission-critical AI at national scale, join Dreams mission - this role is for you.
The Dream-Maker Responsibilities
Operate and maintain database systems - PostgreSQL, Elasticsearch, Redis, MongoDB, vector databases, and others across cloud and on-prem.
Own database reliability - high availability configurations, replication, failover automation, and SLA adherence.
Drive performance tuning - query optimization, index design, configuration tuning, and resource profiling to meet latency and throughput targets.
Execute operational procedures - backup/recovery, disaster recovery testing, upgrades, migrations, and capacity scaling.
Lead incident response for database issues - troubleshooting production problems, root cause analysis, and implementing preventive measures.
Build monitoring and alerting - dashboards, metrics collection, slow query analysis, and proactive capacity alerts.
Enable new capabilities - deploying and tuning vector databases for AI workloads, evaluating new database technologies.
Collaborate with Data Platform, Data Engineering, Engineering, and Security teams on database operations and best practices.
Uphold database SLAs that support retrieval paths, feature stores, and embedding durability; coordinate safe schema evolution, partitioning, and replay/backfill practices.
Expose catalog and lineage signals - ownership, change history, and impact analysis - to improve trust and safe consumption for downstream users.
Collaborate with Data Platform, Data Engineering, Engineering, Security, Product, AI/ML, Data Science, and Analytics to balance performance, durability, and evolution across workloads.