לוח משרות דרושים מהנדס/ת דאטה/DATA ENGINEER

As an Analytics Engineer within the Delivery & Operations organization, you will operate at the intersection of data engineering and analytics, with a strong focus on data quality, reliability, and scalability.

This role combines hands-on ownership of data pipelines and data transformations with the ability to effectively interface with customer-facing teams (Customer Success, and Delivery) when needed-helping ensure that data outputs are accurate, clear, and aligned with real-world use cases.

Responsibilities:
Build and maintain data models, pipelines, and ETL processes to support analytics, reporting, and machine learning.
Own data quality and validation, including monitoring, auditing datasets, and identifying anomalies.
Support customer-facing teams by providing reliable data, clarifying definitions, and investigating data issues.
Collaborate cross-functionally and work with existing codebases to debug, improve, and maintain data workflows.
Ensure high-quality data across the lifecycle to support reliable ML pipelines.

Experienced Data Engineer? Excellent team player?
Come join a great team to overcome meaningful cyber challenges!
Our Data Solutions Group is looking for an exceptional Python developer with Data Engineering experience.

Methodology Development: Develop new data analysis methods and technologies in line with the department roadmap. This includes performing statistical design and evaluation of experiments, multivariate data analysis, and harnessing predictive modeling approaches.
Continuous Improvement: Monitor model performance and make iterative improvements based on feedback and new data.
Innovation: Explore novel AI/ML approaches to enhance cell culture media development processes.
Project Leadership: Propose, execute and lead ML- and data -based work packages within defined projects in related technology areas.
IT data Infrastructure
Reporting: Evaluate, analyze and present project results
Expert Engagement: Actively participate in internal and external expert groups and/or networks
data Pipeline Maintenance: Design, build, TEST and maintan robust data processing pipelines.

We're seeking a Mid to Senior Data Engineer to join our Cloud Identity & Perimeter, a critical component of our 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.

This position is based in our Tel Aviv, Israel office and requires strong leadership presence and ability to work closely with cross-functional teams.

We are searching for a Senior Data Engineer to join our growing team in Tel Aviv and serve as a cornerstone of data evolution. We need an experienced, high-impact engineer ready to elevate our infrastructure from "functional" to "world-class."

As a pivotal member of the team, you wont just build pipelines; you will architect the future of our data ecosystem. Were looking for someone who obsesses over query latency, high-performance analytics, and cost-efficiency - someone who views data integrity as non-negotiable and thrives on turning complex event streams into elegant, scalable models.

Responsibilities
Lead the end-to-end data strategy, evolving our event-driven architecture to ensure seamless, low-latency data flow across the organization.
Design and implement robust, scalable data models that serve as the "single source of truth" for the entire organization.
Act as our internal Snowflake expert - optimizing performance and cost through best practices in clustering, materialized views, and warehouse management.
Build and maintain sophisticated ELT/ETL pipelines that transform raw event data into actionable insights, with a heavy focus on reliability and observability.
Proactively identify infrastructure bottlenecks and re-engineer processes to handle increasing scale without breaking a sweat.
Partner closely with Product and Engineering teams to translate business needs into technical reality, while mentoring analysts and peers on high-quality SQL and architectural standards.

Were looking for a talented Data Engineer to join our Data team and spread the power of our company. The Data team develops and maintains the infrastructure for internal data and product analytics. We are looking for data enthusiasts, independent, logical thinkers with a can-do approach and a passion for problem-solving. We run a SaaS-based stack using BigQuery, Snowflake and dbt.
WHAT YOU'LL DO
Design, build, and maintain data pipelines, datasets and catalogs for fast-growing products and business groups.
Develop self-service data analytics solutions and infrastructure.
Support ad hoc needs and requests of internal stakeholders.
Collaborate with analysts, engineers, and internal customers from Product, Finance, Revenue, and Marketing.

Were looking for a hands-on Technical Project Manager and spread the power of our company. As part of the CTO operations team, you will focuses on improving deployment pipelines and internal tools by digging into logs, finding recurring issues, and reducing manual work. The role combines technical problem-solving with practical execution and coordination.
WHAT YOULL DO
Youll work with engineers and domain leads to help teams improve how they build and operate systems.
Help build and maintain the Unified Maturity Table, defining the technical parameters (workflows, support packages, other metrics) and their KPIs that conclude a domains readiness and maturity.
Partner with the team to refine internal AI agents by measuring the performance of their answers against human expert interventions.
Use cluster analysis (AI) of support ticket descriptions to identify recurring patterns, then design and implement automated workflows to streamline resolution.
Take part in driving the departments "operating system" by facilitating design meetings, managing cross-domain syncs, and ensuring the documentation and support packages required for daily execution are current and actionable.
Define and implement different thresholds by analyzing support ticket complexity, resolution times, and domain-specific friction.
Transition static maturity reports into live, dynamic dashboards with trend lines.
Lead design meetings to establish cross-functional standards for domain maturity and system health alerts.

We are looking for a highly skilled Data Engineer . to build and maintain robust, scalable data pipelines and data marts acting as the connective tissue for intelligence insights generation that serves executive stakeholders , internal our company customers and 3rd party
The Fintech AI & Data group is looking for a staff Data Engineer to work closely with analysts, data scientists, and software developers and strengthen Fintech by building data capabilities and AI transformation.
Responsibilities
Gather data needs from internal customers like product and analysts, and translate those requirements into a working database and analytic software.
Design, build, and maintain scalable, reliable batch and real time data pipelines, data marts and warehouse supporting executive dashboards, operational analytics, and internal customer use cases
Ensure high data quality, observability, reliability, and governance across all data assets
Optimize data models for performance, cost-efficiency, and scalability
Develop data-centric software using leading-edge big data technologies.
Build data capabilities that enable automated agentic insights and decision intelligence
Develop reusable data services and APIs that power AI-driven workflows
Evolve our data architecture into an AI-native data layer designed to power LLMs, AI agents, and intelligent applications
Collaborate with analytics, product, and AI teams to translate business needs into scalable data solutions
Influence the software architecture and working procedures for building data and analytics
Work bBe the go-to person for anything and everything regarding understanding the data - exploration, pipelines, analytics, etc. and work both independently and as part of a team
How youll succeed
Have an impact on satisfying customers and reducing financial fraud
Help build the team by hiring the best talent
Contribute toexperiments and research on how to enhance our capabilities
Learn new technologies and methodologies
Collaborate with other data engineers, analysts, data scientists and developers
Be proactive with a self-starter attitude
Be a good listener, while also having strong opinions on what is right
Be fun to be around.

Required Data Engineer Position
I-Next Data Center, the AI Center is a pioneering data and research hub leading various initiatives to enhance medical diagnosis, prevention and treatment. Our projects encompass diverse areas, including decision-support applications for clinicians, predictive models, image processing, NLP and more.
We are seeking a highly motivated full-time data engineer who is enthusiastic about working with extensive clinical big data sources. The ideal candidate will be dedicated to creating and enhancing data processes to support our dynamic team.
Responsibilities
Conduct data extraction, validation and profiling to maximize the value of data
Design, implement, monitor and maintain data pipelines & ETLs for multiple data sources
Collaborate with researchers, experts and data scientists to comprehend data requirements as well as product design and deliver high-quality outcomes
Manage data development process, including methodology, QA and maintenance.

Required MDClone Engineer 
I-Next Data Center, the AI Center is a pioneering data and research hub leading various initiatives to enhance medical diagnosis, prevention and treatment. Our projects encompass diverse areas, including decision-support applications for clinicians, predictive models, image processing, NLP and more.
We are looking for a highly motivated full-time team member who is eager to work with clinical data. This individual will assist and guide clinicians and researchers in using a clinical data platform. In the future, they will also help improve data processes to enhance the platform further.
Responsibilities
Provide data-related services, support and guide clinicians ensuring their needs are met effectively
Collaborate closely with team members, fostering a cooperative and productive work environment.
Continuously learn and develop new skills independently to stay up to date in the data platform field.
Participate in team discussions and projects to enhance overall team performance and share knowledge.
Proactively identify opportunities for improvement and contribute to data platform development initiatives tailored to the healthcare member's sector.

we are a data driven company, the data Engineering team is the bridge between raw data and impactful business insights. You will lead a team of talented engineers to architect, build, and maintain the data infrastructure of our company. Your mission is to ensure our data is reliable, secure, and ready for everything from standard BI reporting to cutting-edge Generative AI applications. Youll act as a key partner to our business teams, translating high-level needs into technical reality and driving a massive impact on our bottom line. In addition youll spend time mentoring your team as well as tackling high-level architecture decisions, pushing technical strategy and contributing to the codebase.
What am I going to do?:

* Lead a team that designs and scales Real-Time data pipelines processing millions of events hourly.
* Utilize cutting-edge technologies to build scalable and high performant data infrastructure.
* Influence and drive architecture and data strategy decisions.
* Work closely with other stakeholders such as data Developers, Analysts, data Science and R&D.
* Hands-on development of data infrastructure tools (~50% of the time).
* Lead and mentor the team talent.
* Finops and governance of data infrastructure domains.
Equal opportunities:
At our company, we prioritize diversity. We celebrate difference and embed it into every aspect of our workplace and product, as well as our community. we are proud and committed to providing equal opportunity employment to all individuals regardless of race, color, religion, sex, sexual orientation, citizenship, national origin, disability, Veteran status, or any other characteristic protected by law. In addition, we will provide accommodation to individuals with disabilities or a special need.

In your role as a Data Engineer , you'll be actively engaged in the most fascinating and demanding projects for our clients. Handling high-scale operations, heavy traffic, stringent SLAs, and massive data volumes is just the starting point. Our leadership in the realms of Big Data, Streaming Data, and Complex Event Processing (CEP) stems from our adept use of cutting-edge, optimal technologies.
Responsibilities:
Apply software-engineering methods and best practices (Medallion Architecture) in Data Lake management, using tools like DBT.
Develop Data pipelines to ingest and transform data.
Manage and enhance orchestrated pipelines across company
Data Modeling: Developing data models to ensure efficient storage, retrieval, and processing of data, often involving schema design for NoSQL databases, data lakes, and data warehouses. This will also include catalogs of data.
Scalability: Ensuring that the big data architecture can scale horizontally to handle large volumes of data and high traffic loads.
Data Security: Implementing security measures to protect sensitive data, including encryption, access controls, and data masking.
Data Governance: Establishing data governance policies to ensure data quality, compliance with regulations, and data lineage.

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.