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We are seeking an experienced Solutions Data Engineer who possess both technical depth and strong interpersonal skills to partner with internal and external teams to develop scalable, flexible, and cutting-edge solutions. Solutions Engineers collaborate with operations and business development to help craft solutions to meet customer business problems.
A Solutions Engineer works to balance various aspects of the project, from safety to design. Additionally, a Solutions Engineer researches advanced technology regarding best practices in the field and seek to find cost-effective solutions.
Job Description:
Were looking for a Solutions Engineer with deep experience in Big Data technologies, real-time data pipelines, and scalable infrastructure-someone whos been delivering critical systems under pressure, and knows what it takes to bring complex data architectures to life. This isnt just about checking boxes on tech stacks-its about solving real-world data problems, collaborating with smart people, and building robust, future-proof solutions.
In this role, youll partner closely with engineering, product, and customers to design and deliver high-impact systems that move, transform, and serve data at scale. Youll help customers architect pipelines that are not only performant and cost-efficient but also easy to operate and evolve.
We want someone whos comfortable switching hats between low-level debugging, high-level architecture, and communicating clearly with stakeholders of all technical levels.
Key Responsibilities:
Build distributed data pipelines using technologies like Kafka, Spark (batch & streaming), Python, Trino, Airflow, and S3-compatible data lakes-designed for scale, modularity, and seamless integration across real-time and batch workloads.
Design, deploy, and troubleshoot hybrid cloud/on-prem environments using Terraform, Docker, Kubernetes, and CI/CD automation tools.
Implement event-driven and serverless workflows with precise control over latency, throughput, and fault tolerance trade-offs.
Create technical guides, architecture docs, and demo pipelines to support onboarding, evangelize best practices, and accelerate adoption across engineering, product, and customer-facing teams.
Integrate data validation, observability tools, and governance directly into the pipeline lifecycle.
Own end-to-end platform lifecycle: ingestion → transformation → storage (Parquet/ORC on S3) → compute layer (Trino/Spark).
Benchmark and tune storage backends (S3/NFS/SMB) and compute layers for throughput, latency, and scalability using production datasets.
Work cross-functionally with R&D to push performance limits across interactive, streaming, and ML-ready analytics workloads.
Operate and debug object store-backed data lake infrastructure, enabling schema-on-read access, high-throughput ingestion, advanced searching strategies, and performance tuning for large-scale workloads.

We're seeking a Mid to Senior Data Engineer to join our Cloud Identity & Perimeter, a critical component of CrowdStrike's security infrastructure. Our team develops and maintains complex data pipelines that process billions of records daily, analyzing identity-related security patterns, effective permissions, internet exposure, and attack paths. We're at the forefront of securing enterprise identities and delivering actionable security insights at scale.

What You'll Do:

Design and implement high-performance, distributed data processing pipelines handling petabytes of security data.

Architect complex data transformations using Apache Spark for large-scale batch and stream processing.

Be part of shaping new products while collaborating with product teams, customers, and sales.

Build and optimize real-time data streaming solutions using Kafka for identity analytics.

Develop and maintain scalable ETL processes that handle billions of daily events.

Create efficient data models for complex security analytics queries.

Collaborate with cross-functional teams to deliver high-impact security features.

Optimize query performance and data storage patterns for large-scale distributed systems.

Participate in system design discussions and architectural decisions.

We are looking for a Data Engineer to join our growing team!
This is a great opportunity to be part of one of the fastest-growing infrastructure companies in history, an organization that is in the center of the hurricane being created by the revolution in artificial intelligence.
In this role, you will be responsible for:
Designing, building, and maintaining scalable data pipeline architectures
Developing ETL processes to integrate data from multiple sources
Creating and optimizing data models for efficient storage and retrieval
Implementing data quality controls and monitoring systems
Collaborating with data scientists and analysts to deliver data solutions
Building and maintaining data warehouses and data lakes
Performing in-depth data analysis and providing insights to stakeholders
Taking full ownership of data quality, documentation, and governance processes
Building and maintaining comprehensive reports and dashboards
Ensuring data security and regulatory compliance.

We are looking for a highly enthusiastic Data Engineer to join our group on the journey of leveraging Big Data to revolutionize our offering, business operations and decision making across the companys ecosystem.
Job Responsibilities:
Design, build & deploy backend data solutions to prod, starting from research and design to development and testing.
Work closely with data engineers, product, architects and other R&D teams to deliver the best solutions to the business.
Monitor the solutions in production to make sure they are fully stable, scalable and performant at all times.
Work closely with data sciences experts

You will architect and build a scalable data platform from scratch, engineering high-throughput, low-latency pipelines that drive real-time security analytics and AI-powered systems. As a key member of the Data & AI Algorithms group, you will collaborate with AI/ML engineers, data scientists, and security researchers to design production-grade infrastructure at scale.
This role requires strong ownership, systems thinking, and the agility to operate in a fast-moving environment.
What Youll Do:
Build ML infrastructure to support scalable, low-latency production deployment of data & AI models.
Ensure availability, reliability, and performance of mission-critical data infrastructure
Define and promote best practices for data modeling, orchestration, CI/CD, and infrastructure-as-code
Collaborate cross-functionally to enable data-driven product capabilities

Required Customer-Facing Data Scientist - Demand Forecasting
HQ in Tel Aviv with a growing sales and marketing organization in the US
Customers across CPG, retail, healthcare, mobile apps, fintech, insurance, and consumer services. Marquee customers include Johnson & Johnson, Mars, and SciPlay.
Demand Forecasting Team:
The Demand Forecasting team is at a pivotal, high-growth stage. We have successfully built our core pipeline and are now aggressively onboarding new, diverse customers. This role is highly dynamic, requiring a blend of technical depth, proactive research, and exceptional communication to adapt our platform to real-world customer data and challenges. You will be a critical link between the core product and our clients business success.
Responsibilities:
As a key Customer-Facing Data Scientist on the Demand Forecasting team, you will:
Work at the forefront of the data world, focusing on the optimization and deployment of Demand Forecasting models.
Handle complex data science challenges using state-of-the-art techniques relevant to demand forecasting and time series, such as forecasting model ensembling, anomaly detection, feature engineering for trend/seasonality, and causal inference modeling.
Act as a highly communicative partner to our clients, diving deep into their unique datasets to understand the nuances and challenges of their business.
Lead the rigorous testing and application of our core ML pipeline on new customer data, identifying areas where it performs exceptionally well and researching/developing solutions for complex cases where it does not.
Be instrumental in helping our clients achieve their business goals and realize the measurable value of our Demand Forecasting module.
Work within a production and product-oriented environment, ensuring models are robust, scalable, and directly integrated into the clients operational workflow.

Required Senior Business Analyst
The Senior Business Analyst will lead strategic and tactical initiatives across the organization, translating complex data into actionable insights and measurable business outcomes. This role requires strong ownership, independent execution, and close collaboration with cross-functional stakeholders.
Key Responsibilities:
Own and lead end-to-end analytical projects tied to core business processes, with direct impact on revenue growth, cost efficiency, and profitability.
Analyze business performance across products, channels, and customer segments, and translate insights into clear recommendations for strategic and tactical decision-making.
Build, maintain, and continuously improve reports, dashboards, and KPIs to support business monitoring and executive decision-making.
Partner with stakeholders across Strategy, Marketing, Product, Operations, and Finance to drive execution and ensure alignment with business objectives.
Conduct deep customer analysis, including segmentation, lifetime value, profitability, behavioral trends, and cohort analysis.
Work with large, complex datasets and develop scalable analytical tools to streamline processes and improve operational efficiency.
Deliver ad-hoc analyses under tight timelines to support fast-paced business decisions.
Ideal Candidate Profile:
A proactive, hands-on business analyst who takes full ownership of initiatives from problem definition through execution and measurable impact.
Strong commercial mindset with the ability to connect data insights to P&L drivers, growth levers, and profitability optimization.
Comfortable operating independently in a fast-growing, dynamic environment, while influencing stakeholders without formal authority.
Highly analytical, detail-oriented, and driven by turning data into clear actions and results.

We are on the lookout for a Senior Data Engineer to join our growing data team!

In this role, you will design and develop scalable data solutions, optimize data workflows, and support critical business processes. You will work with a variety of databases and big data tools in a cloud environment, focusing on data modeling, governance, and analytics.

What youll be doing:
Design, develop, and maintain end-to-end ETL pipelines, from gathering business requirements to implementation.
Work with multiple database technologies, especially BigQuery.
Optimize data models (DWH, fact & dimension tables, RI, SCDs) for performance and scalability.
Implement data governance best practices and maintain comprehensive documentation.
Utilize Big Data tools in cloud environments (GCP preferred).
Develop and support complex business workflows and data processes.
Design and implement monitoring systems to ensure data quality throughout the pipeline.
Workflow orchestration using Apache Airflow.
Collaborate with analysts and stakeholders to ensure high-quality data for business insights.
Support and optimize Tableau infrastructure for data visualization.

We are looking for a Senior Data Infrastructure Engineer to lead the design, build, and optimization of a modern data platform. The role involves hands-on work with cloud-based data technologies, building data lakes from scratch, and managing large-scale data pipelines while ensuring high performance, cost efficiency, and reliability. You will collaborate closely with data engineers, data science, analytics, and product teams to support business needs.



Key Responsibilities:

Design and build scalable data lakes / platforms using technologies such as Snowflake, Databricks, BigQuery, or Redshift
Develop and optimize large-scale data pipelines for batch and streaming use cases
Ensure high performance, scalability, and cost efficiency across data systems
Work with complex data workflows, AI models, transformations, and orchestration
Apply best practices in data modeling, monitoring, security, and governance

About us We are Tailor Brands . We built a platform that builds businesses. From launching and managing to growing a business, Tailor Brands is the all-in-one solution that empowers any business owner. Our platform services over 40 million small businesses. Our "Guidance Engine" assesses each new business introduced to our platform and devises a tailored plan that allows you to manage all your business needs from a single dashboard. Through our business-building platform, we’re turning the process of starting, managing, and growing a business into a better experience; we’re simplifying the business journey. At Tailor Brands, we believe in more than just handing you another tool; we are dedicated to teaching you the art of building a business. About the Role: As a Data Engineer at Tailor Brands, you'll design and maintain the data pipelines that power decision-making across product, marketing, and finance. Working with Apache Airflow, Python, and SQL, you'll build trusted, well-documented datasets that enable self-service analytics for the entire organization. You'll champion data quality through validation and monitoring, optimize infrastructure for scale, and be part of a forward-thinking team that actively leverages AI tools like Claude to push the boundaries of modern data engineering. If you thrive on turning messy data into reliable, actionable foundations — and want to do it for a platform serving over 40 million small businesses — this role is for you. What we’re looking for
* Design, implement and maintain pipelines that deliver data with measurable quality and SLAs for our product, marketing, finance, and other departments
* Partner with business domain experts, data analysts, and engineering teams to build foundational datasets that are trusted, well-understood, aligned with business strategy and enable a self-service analysis
* Focus on data quality, detect data/analytics quality issues, implement bug fixes and data validations for prevention
* Identify, design, and implement internal process improvements such as automating manual processes, optimizing data delivery, re-designing infrastructure for greater scalability, etc
* Be part of a team that actively integrates AI tools like Claude into day-to-day workflows, pushing the boundaries of how data engineering gets done

we are looking for a Data Engineer.
This is a full-time, on-site role for a Data Engineer, located in Haifa.
The Data Engineer will design, build, and maintain scalable data pipelines, implement robust Extract, Transform, Load (ETL) processes, and develop efficient data models to support business intelligence and data analytics needs. The role also involves building and improving data warehousing solutions and collaborating with cross-functional teams to ensure data integrity and optimize workflows.

A fast-growing fintech AI start-up company, focused on eliminating fraud and chargebacks in online commerce, is looking for an experienced Senior Data Engineer.

In this Roll, you will build large-scale, cutting-edge data solutions for fraud prevention, with the potential to grow into a technical leadership role.

The company is located in Modi'in, central Israel. Hybrid work model.



Responsibilities

Build and maintain scalable data pipelines and ETL processes.
Design complex data models and optimize data architecture.
Collaborate with teams to deliver high-quality, compliant solutions.
Troubleshoot production issues and implement best practices.
Recommend new technologies to enhance the data infrastructure.

Required Senior Data Engineer
Main responsibilities:
Provide the direction of our data architecture. Determine the right tools for the right jobs. We collaborate on the requirements and then you call the shots on what gets built.
Manage end-to-end execution of high-performance, large-scale data-driven projects, including design, implementation, and ongoing maintenance.
Optimize and monitor the team-related cloud costs.
Design and construct monitoring tools to ensure the efficiency and reliability of data processes.
Implement CI/CD for Data Workflows.

We are looking for an experienced Data Engineering Team Leader.
In this role, you will lead and strengthen our Data Team, drive innovation, and ensure the robustness of our data and analytics platforms.
A day in the life and how youll make an impact:
Drive the technical strategy and roadmap for the data engineering function, ensuring alignment with overall business objectives.
Own the design, development, and evolution of scalable, high-performance data pipelines to enable diverse and growing business needs.
Establish and enforce a strong data governance framework, including comprehensive data quality standards, monitoring, and security protocols, taking full accountability for data integrity and reliability.
Lead the continuous enhancement and optimization of the data analytics platform and infrastructure, focusing on performance, scalability, and cost efficiency.
Champion the complete data lifecycle, from robust infrastructure and data ingestion to detailed analysis and automated reporting, to maximize the strategic value of data and drive business growth.