לוח משרות דרושים איש ביג דאטה Big Data בהרצליה

XM Cyber is a global leader in hybrid cloud security. XM Cyber brings a new approach that uses the attacker’s perspective to find and remediate critical attack paths across on-premises and multi-cloud networks. The XM Cyber platform enables companies to rapidly prioritize and respond to cyber risks affecting their business-sensitive systems. As a Senior Backend engineer with Spark experience at XM Cyber, you'll be responsible for implementing core features, building infrastructure, and finding innovative solutions while getting into the language internals. We're looking for top talents who are ready to level up their skills in an exciting and fast-paced environment. You will be responsible for leading features and products end to end, from design to production; build and develop modules, data pipelines, and services.

We are looking for a Java Backend Developer to be part of our core technology team.
This position is full-time, hybrid, in our offices in Herzliya.

We are looking for a highly motivated and passionate Advanced Analytics & AI Specialist to drive high priority customer initiatives on the Azure Platform in collaboration with customers and the field in Enterprise accounts segment of our business. This is a customer facing role, owning overall technical relationship between customer and Data, Advanced Analytics and Artificial Intelligence Platform.

You will own the Data Platform & Advanced Analytics technical customer engagements including envisioning, specific implementation projects and/or MVPs. The ideal candidate will have experience in customer-facing roles and success leading deep technical architecture discussions with senior customer executives, Enterprise Architects, IT Management and Developers to drive Data Platform and Advanced Analytics solutions to productions.
Responsibilities
Key responsibilities include:

Understand customers overall data & analytics estate, business use-cases, priorities and success measures to design implementation architectures and solutions.
Apply technical knowledge to architect solutions that meet business and analytics needs, create Data Platform, Data Migration Strategy, Analytics and AI roadmaps, and ensure long term technical viability of new deployments, infusing key analytics technologies where appropriate (e.g. SQL Server, Azure Synapse, Azure ML, Azure Cognitive Services, Azure Data Factory, Big Data, Data Lake, Azure Databricks, Power BI, etc.)
Ensure that solution exhibits high levels of performance, security, scalability, maintainability, appropriate reusability and reliability upon deployment
Develop deep relationships with key customer IT decision makers and relevant business decision makers, who drive long-term cloud adoption within their company to enable them to be cloud advocates
Be a Voice of Customer to share insights and best practices, connect with Engineering team to remove key blockers
Assess the Customers' knowledge of Azure platform and overall cloud readiness to support customers through a structured learning plan and ensure its delivery through partners.
Collaborate with other Cloud Solution Architects and MS stakeholders in developing complex end-to-end Enterprise solutions on Cloud platforms.
Maintain technical skills and knowledge, keeping up to date with market trends and competitive insights; collaborate and share with the technical community while educate customers on Azure platform
Be an Azure Platform evangelist with customers, partners and external communities.

We are searching for an innovative and experienced Senior Big Data Engineer that will join us and be part of our big data group.

As a Senior Big Data Engineer, you will:
Lead the architecture and development of mission-critical, diverse and large-scale data pipelines over both public and on-prem cloud solutions.
Derive policies for data storage and versioning over peta-bytes scale complex storage solutions of multiple data lakes.
Design and develop smart ML infrastructure in order to build Agile ML processes (MLOps).
Work with Data Scientists to understand needs and design ML infrastructure solutions
Be a part of a collaborative heterogeneous data team which includes developers, data scientists, data engineers, MLOps and data scouts.