Required Data Engineer
Description
Join our core platform engineering team, developing our AI-powered automotive data management platform.
We are developing the next generation data-driven products for the Automotive industry, focusing on cybersecurity (XDR) and vehicle quality. our products monitor and secure millions of vehicles worldwide and help automakers leverage connected vehicle data to deliver cyber resilience, safety, customer satisfaction and increase brand loyalty.
Our Data Engineering & Data Science Group leads the development of our Iceberg-based data platform, including data lake, query engine, and ML-Ops tools, serving as a solid AI-ready foundation for all our products.
At the core of our Engineering Team, you will build and operate scalable, production-grade customer-facing data and ML platform components, focusing on reliability and performance.
Technological background and focus: Iceberg, Trino, Prefect, GitHub Actions, Kubernetes, JupyterHub, MLflow, dbt
This role is full-time and is Herzliya, Israel based.
Responsibilities
Design, build, and maintain scalable data pipelines to ingest and transform batch data on our data lake, enabling analytics and ML with strong data quality, governance, observability, and CI/CD.
Build and expand our foundational data infrastructure, including our data lake, analytics engine, and batch processing frameworks.
Create robust infrastructure to enable automated pipelines that will ingest and process data into our analytical platforms, leveraging open-source, cloud-agnostic frameworks and toolsets.
Develop and maintain our data lake layouts and architectures for efficient data access and advanced analytics.
Develop and manage orchestration tools, governance tools, data discovery tools, and more.
Work with other team members of the engineering group, including data architects, data analysts, and data scientists, to provide solutions using a use case-based approach that drives the construction of technical data flows.
End-to-end ownership mindset with a proactive, production-first approach.

Required Senior Data Engineer
Join our core platform engineering team, developing our AI-powered automotive data management platform.
We are developing the next generation data-driven products for the Automotive industry, focusing on cybersecurity (XDR) and vehicle quality. Our products monitor and secure millions of vehicles worldwide and help automakers leverage connected vehicle data to deliver cyber resilience, safety, customer satisfaction and increase brand loyalty.
Our Data Engineering & Data Science Group leads the development of our Iceberg-based data platform, including data lake, query engine, and ML-Ops tools, serving as a solid AI-ready foundation for all our products.
At the core of our Engineering Team, you will build and operate scalable, production-grade customer-facing data and ML platform components, focusing on reliability and performance.
Technological background and focus: Iceberg, Trino, Prefect, GitHub Actions, Kubernetes, JupyterHub, MLflow, dbt
This role is full-time and is Herzliya, Israel based.
Responsibilities
Design, build, and maintain scalable data pipelines to ingest and transform batch data on our data lake, enabling analytics and ML with strong data quality, governance, observability, and CI/CD.
Build and expand our foundational data infrastructure, including our data lake, analytics engine, and batch processing frameworks.
Create robust infrastructure to enable automated pipelines that will ingest and process data into our analytical platforms, leveraging open-source, cloud-agnostic frameworks and toolsets.
Develop and maintain our data lake layouts and architectures for efficient data access and advanced analytics.
Develop and manage orchestration tools, governance tools, data discovery tools, and more.
Work with other team members of the engineering group, including data scientists, data architects, and data analysts, to provide solutions using a use case-based approach that drives the construction of technical data flows.

We are looking for a motivated Data Engineer to join our growing Data team. This is an exciting opportunity to be part of a core group responsible for building, maintaining, and scaling our data platform, while working closely with Product, Engineering, and business teams.

You will play a key role in developing reliable data pipelines, ensuring data quality and consistency, and enabling data-driven decision-making across the organization.

Responsibilities:
Design, build, and maintain data pipelines and data models to support analytics and reporting needs.
Work with structured data across databases, data lakes, and data warehouses.
Write efficient and maintainable SQL and Python code for data transformation and validation.
Ensure data quality, consistency, and basic data lineage across systems.
Collaborate with Product, Engineering, and business stakeholders to understand data requirements.
Support dashboards and reporting tools by providing clean, well-modeled data.
Contribute to improving data standards, documentation, and best practices.

We are seeking an experienced Data Engineer with a strong background in BI and Data Engineering, excellent problem-solving skills, and the ability to work independently and learn quickly.
Role Overview
You will join a dynamic team responsible for designing and implementing end-to-end data solutions on the Microsoft Fabric platform. This role involves:
Building and maintaining robust data processes.
Driving adoption of new technology within the organization.
Ensuring scalability, performance, and reliability of data solutions.

Responsibilities:
Collaborate with leaders, stakeholders, and product managers to understand data requirements and deliver effective BI solutions.
Design, develop and maintain robust data pipelines for efficient data ingestion, processing, and storage.
Optimize data storage and retrieval processes for optimal performance.
Monitor data pipelines and systems consistently to identify performance issues, ensuring timely maintenance and troubleshooting.
Create and maintain documentation of data processes and systems.

we are an innovative, data -oriented, high-tech company that owns, develops, and publishes multi-platform digital Assets. All our products and content coordinate together to create unique monetization solutions and advanced revenue streams for digital properties. We are expanding our teams and are focused on adding like-minded, result-oriented, and high-achieving talents.
Impact and Responsibilities
* Design, implement, and maintain scalable, secure, and reliable cloud infrastructure on AWS (3+ years of experience required) and GCP (preferred).
* Build and maintain CI/CD pipelines to automate application deployment and infrastructure updates.
* Demonstrate hands-on experience using Generative AI tools (e.g., GitHub Copilot, ChatGPT, Cursor, or similar) to accelerate scripting, infrastructure automation, CI/CD configuration, and operational troubleshooting.
* Automate infrastructure provisioning and management using Infrastructure-as-Code (IaC) tools, with Terraform experience being a must.
* Automate infrastructure provisioning and management with Ansible experience being a must.
* Collaborate with development teams to optimize application performance and reliability.
* Troubleshoot and resolve system, application, and network issues to ensure high availability and reliability.
* Ensure the compliance of our infrastructure with security best practices and standards.
* Leverage advanced networking and proxy configuration expertise to design robust and secure systems.
* Continuously research, evaluate, and implement new technologies to enhance infrastructure efficiency and cost-effectiveness.

Fire-Arc is an innovative, data-oriented, high-tech company that owns, develops, and publishes multi-platform digital Assets. All our products and content coordinate together to create unique monetization solutions and advanced revenue streams for digital properties. We are expanding our teams and are focused on adding like-minded, result-oriented, and high-achieving talents. We’re looking for a Mid-Level Client Developer with strong leadership capabilities, extensive experience building Windows desktop applications , and a passion for mentoring others and solving complex problems.
Impact and Responsibilities
* Lead the design and development of Windows desktop applications using technologies mostly C# (.NET) WPF
* Drive high-quality integrations with AWS services like S3, Lambda (serverless), EC2, DynamoDB and RDS
* Use AI-powered development tools and IDEs (such as GitHub Copilot, Cursor, and similar assistants) as part of the daily workflow to improve development speed, code quality, and problem-solving
* Design, build, and maintain backend services that support and seamlessly integrate with Windows desktop client applications.
* Apply practical experience with Generative AI tools to increase productivity while maintaining strong engineering standards and critical thinking.
* Proactively identify technical and architectural challenges, and craft scalable, secure, and user-centric solutions
* Oversee and enhance application installation, deployment, and update processes with a focus on security and user experience
* Foster a collaborative, respectful work environment , supporting team members and driving alignment with cross-functional teams
* Participate in code reviews and contribute to a culture of quality and shared knowledge
* Continuously monitor and optimize application performance, security, and scalability
* Stay up-to-date with industry trends and recommend new tools, techniques, or improvements to enhance team effectiveness

Brand:
FireArc

Design, build, and maintain scalable ETL/ELT pipelines to integrate data from diverse sources, optimizing for performance and cost efficiency.
Leverage Databricks and other modern data platforms to manage, transform, and process data
Collaborate with software teams to understand data needs and ensure data solutions meet business requirements.
Optimize data processing workflows for performance and scalability.

Were looking for an experienced MLOps Engineer to join our team and help design, implement, and maintain scalable machine learning infrastructure and data processing pipelines.
The ideal candidate is passionate about operational excellence, automation, and building reliable systems that empower data scientists and engineers alike.
This role is responsible for enhancing, automating, monitoring, and optimizing data pipelines that collect, transform, cache, index, and manage large-scale datasets.

We are searching for an innovative and experienced Data Engineer that will join us and be part of our reference and alternative data team in our data group.
As a Data Engineer, you will:
Be a part of a cross functional team of data and backend engineers.
Be responsible for ingesting financial data and providing it over numerous APIs in close collaboration with algorithmic teams and other partners.
Lead the architecture, planning, design and development of mission-critical and diverse data pipelines over both public and on-prem cloud solutions.

We are looking for a hands-on GTM Engineer to help make our Go-to-Market engine smarter, more efficient, and more effective. This role focuses on removing manual and administrative work from GTM teams, enabling humans to focus on strategy, creativity, and decision-making while systems handle execution and scale.

The GTM Engineer designs and operates HubSpot-centered GTM architecture and AI-powered automation that improves speed, accuracy, and scalability across Marketing, Sales, and SDR workflows.

What you will do:
Own day-to-day administration, configuration, and optimization of HubSpot across Marketing and Sales use cases.
Design and maintain GTM system architecture, including data models, lifecycle logic, routing, scoring, and automation frameworks.
Build, operate, and continuously improve AI-powered workflows that reduce manual work and increase GTM velocity.
Implement advanced automation using tools such as Clay, AI agents, and workflow orchestration platforms.
Integrate HubSpot with Salesforce and other GTM systems to ensure reliable data flow and process consistency.
Automate enrichment, qualification, routing, outbound support, and handoff processes across the funnel.
Monitor data quality, automation health, and system performance, proactively identifying and resolving issues.
Document system logic, workflows, and automation patterns to ensure maintainability and scalability.
Continuously experiment with new AI and automation approaches and apply them to practical GTM use cases.