לוח משרות דרושים איש ביג דאטה Big Data, לחיפוש זה נמצאו 24 משרות

we are looking for a Knowledge & Quality Specialist.
As a Knowledge and Quality Specialist, you will be a member of the team that ensures the quality of the data the company provides its clients.
As part of this, the Knowledge and Quality Specialist is responsible for building and maintaining a knowledge base on the basis of which data analysis is performed, as well as for quality control processes and quality improvement processes of data analysis, and for training analysts and improving processes.
Responsibilities:
Data analysis based on dashboards
Specialization in the type of data analyzed by the company
Specialization in labeling and quality control systems
Improvement and development labeling and quality control systems and features
Performance of quality control tests
Development and implementation of learning and training sets
Collaboration with operation, outsource, development and QA teams

We are looking for a Data Engineer to join our usage metering & billing platform team! with a strong background in writing ETLs and complicated data processing pipelines. Youre deeply familiar with modern data processing stack (especially Spark, Hadoop and Airflow), have a strong problem-solving attitude and, most importantly, youre passionate about understanding the business side of the platform. Our platform engineers have an end-to-end understanding of the data our products generate and the commercial models and data structures in which they fit.
Working with this enormous volume of data begins with massive ETL pipelines built using cutting-edge technologies such as Kafka, BigQuery, Airflow, S3, PostgreSQL, Athena, SQS, Redis, and especially Spark. We are big believers in working with the right tool for the right job, including programming languages. We run a truly polyglot shot with Scala, Python, Go and Node being especially common here . The extreme growth rate of our data and client base means that solutions need to be designed to handle 10X growth or more.
What youll do:
Develop end-to-end ETLs and data infrastructure features from data processing logic to database choice and implementation through to API development
Improve the scalability and performance of existing data pipelines
Delve into existing pipelines and business logic, target weaknesses and add functionality
Mentor, advise, and work collaboratively within the Biz Data & Dev group, with other development teams, and with all other business teams of the company
Continuously learn and follow new technologies both for personal growth and to ensure we are making the most informed technology choices possible

We are looking for a Data Engineer to join our usage metering & billing platform team! with a strong background in writing ETLs and complicated data processing pipelines. Youre deeply familiar with modern data processing stack (especially Spark, Hadoop and Airflow), have a strong problem-solving attitude and, most importantly, youre passionate about understanding the business side of the platform. Our platform engineers have an end-to-end understanding of the data our products generate and the commercial models and data structures in which they fit.
Working with this enormous volume of data begins with massive ETL pipelines built using cutting-edge technologies such as Kafka, BigQuery, Airflow, S3, PostgreSQL, Athena, SQS, Redis, and especially Spark. We are big believers in working with the right tool for the right job, including programming languages. We run a truly polyglot shot with Scala, Python, Go and Node being especially common here . The extreme growth rate of our data and client base means that solutions need to be designed to handle 10X growth or more.
What youll do:
Develop end-to-end ETLs and data infrastructure features from data processing logic to database choice and implementation through to API development
Improve the scalability and performance of existing data pipelines
Delve into existing pipelines and business logic, target weaknesses and add functionality
Mentor, advise, and work collaboratively within the Biz Data & Dev group, with other development teams, and with all other business teams of the company
Continuously learn and follow new technologies both for personal growth and to ensure we are making the most informed technology choices possible

We are responsible for building data pipelines end to end-from raw data ingestion to the creation of actionable datasets-following the bronze, silver, and gold paradigm. This includes business logic, infrastructure, ETLs, optimization, and ongoing maintenance.

The data we deliver drives insights and decision-making across the organization and enhances our product offerings. We leverage technologies such as AWS, Snowflake, Iceberg, Airflow, Spark, and more.

What Youll Do
Lead the translation of business and product requirements into scalable data models, transformations, and pipelines.

Design and own datasets across bronze, silver, and gold layers, including defining grain, aggregations, and data contracts.

Develop and maintain SQL-heavy data pipelines and Airflow DAGs (workflow logic, dependencies, backfills, python, and lots of SQL).

Own data correctness for key business metrics (e.g., ARR), including deep root cause analysis and resolution of data issues.

Define and drive best practices for SQL, data modeling, and pipeline design across the team.

Optimize queries and data models for performance, scalability, and cost efficiency.

Collaborate closely with product managers, analysts, and BI developers to refine requirements and ensure high-quality data delivery.

Develop AI-agents to accelerate data analysis by internal and external users.

Work with complex data inputs (e.g., JSON, schemas, logs) and incorporate them into robust data pipelines.

Were looking for a Data Engineering Team Lead to take ownership of Ports data engineering team and help shape the future of agentic engineering portals. This is a hands-on leadership role: youll guide a team, drive technical direction, and help establish Ports data warehouse both for product use cases and for internal business analytics.

What youll do:

were building a platform by developers, for developers. As a Data Engineering Team Lead, youll balance leadership and data engineering work - setting technical direction while enabling your team to thrive.

Your responsibilities will include:

Lead the design and development of scalable and efficient data warehouse and BI solutions that align with organizational goals and requirements.
Utilize advanced data modeling techniques to create robust data structures supporting reporting and analytics needs.
Implement ETL/ELT processes to assist in the extraction, transformation, and loading of data from various sources into a shared data warehouse.
Identify and address performance bottlenecks within our data warehouse, optimize queries and processes, and enhance data retrieval efficiency.
Develop and provide a data backend for product facing features such as usage analytics, data insights and enabling an agentic context lake
Collaborate with cross-functional teams (product, R&D, analysts) to deliver actionable data solutions tailored to their needs.

we are looking for a Big Data Engineer.
As a Senior Big Data Engineer, working within Mobility Group, you will play a pivotal role in designing, developing, and maintaining the data infrastructure that powers our location analytics platform.
RESPONSIBILITIES:
Data Pipeline Architecture and Development: Design, build, and optimize robust and scalable data pipelines to process, transform, and integrate large volumes of data from various sources into our analytics platform.
Data Quality Assurance: Implement data validation, cleansing, and enrichment techniques to ensure high-quality and consistent data across the platform.
Performance Optimization: Identify performance bottlenecks and optimize data processing and storage mechanisms to enhance overall system performance and reduce latency.
Cloud Infrastructure: Work extensively with cloud-based technologies (GCP and AWS), to design and manage scalable data infrastructure.
Collaboration: Collaborate with cross-functional teams including Data Analysts, Data Scientists, Product Managers, and Software Engineers to understand requirements and deliver solutions that meet business needs.
Data Governance: Implement and enforce data governance practices, ensuring compliance with relevant regulations and best practices related to data privacy and security.
Monitoring and Maintenance: Monitor the health and performance of data pipelines, troubleshoot issues, and ensure high availability of data infrastructure.
Mentorship: Provide technical guidance and mentorship to junior data engineers, fostering a culture of learning and growth within the team.

Were looking for a Big Data Engineer to develop and integrate systems that retrieve, process and analyze data from around the digital world, generating customer-facing data. This role will report to our Team Manager, R&D.
Why is this role so important?
A data-focused company, and data is the heart of our business.
As a big data engineer developer, you will work at the very core of the company, designing and implementing complex high scale systems to retrieve and analyze data from millions of digital users.
Your role as a big data engineer will give you the opportunity to use the most cutting-edge technologies and best practices to solve complex technical problems while demonstrating technical leadership.
So, what will you be doing all day?
Your role as part of the R&D team means your daily responsibilities may include:
Design and implement complex high scale systems using a large variety of technologies.
You will work in a data research team alongside other data engineers, data scientists and data analysts. Together you will tackle complex data challenges and bring new solutions and algorithms to production.
Contribute and improve the existing infrastructure of code and data pipelines, constantly exploring new technologies and eliminating bottlenecks.
You will experiment with various technologies in the domain of Machine Learning and big data processing.
You will work on a monitoring infrastructure for our data pipelines to ensure smooth and reliable data ingestion and calculation.

we are the leader in hybrid-cloud security posture management, using the attacker's perspective to find and remediate critical attack paths across on-premises and multi-cloud networks. we are  looking for a talented Senior Big Data Developer to join our Vulnerability Risk Management (VRM) team. Join a team building the data platform behind XM Cyber's Vulnerability Risk Management (VRM) - a system that ingests, normalizes, and correlates vulnerability and asset data from on-premises networks, endpoints, and physical machines at enormous scale. You'll design the pipelines that fuse CVE severity, EPSS exploit-prediction, and business impact with attack-graph context, turning billions of raw findings into a ranked, actionable picture of real risk. The result: customers stop chasing every CVE and start fixing the handful that are genuinely exploitable on their critical assets.
This role provides the opportunity to lead end-to-end design & implementation of advanced server-side features using a wide range of technologies: Apache Spark, Apache Airflow, Scala, k8s, with Relational Database, Redis, Kafka, Dockers. If you are up for the challenge and you have the 'XM factor', come and join us!

Were looking for a sharp and driven Data Analyst to join our fast - paced Data Labs team. As part of a high-performing group of analysts, youll handle complex, custom requests from some of the biggest names in the market, turning raw data into strategic, ad hoc insights. The work is intense and constantly evolving - it requires strong analytical skills and the ability to work independently under pressure. Youll need to be curious, adaptable, and willing to dive deep to find answers where others might stop. If you thrive in a demanding environment and are excited by the opportunity to make a real impact, we want you on our team.
What does the day to day of a Big Data Analyst Customer Facing (Data Labs) look like:
Building custom-made reports end to end - from meeting with the client and understanding their needs, to writing the code and setting up the report for ongoing delivery.
Apply your expertise in quantitative analysis and data mining to turn data into insights.
Conduct research and develop tools which will help answer client's business. questions by using our raw data sets and algorithms.
Partner with Engineering teams to establish an infrastructure to scale solutions.
Partner with Advisory Services team of Consultants to answer strategic business questions and deliver custom data products seamlessly.

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.

At UVeye, we're on a mission to redefine vehicle safety and reliability on a global scale. Founded in 2016, we pioneered the world's first fully automated suite of AI-powered vehicle inspection systems, combining computer vision, machine learning, and generative AI. With over $380M in funding and strategic partnerships with Toyota, Amazon, General Motors, JLR, Volvo, and Hertz, our technology is deployed across manufacturing plants, dealerships, wholesale auctions, fleets, and seaports worldwide. Named one of Fast Company's Most Innovative Companies of 2026, our 300+ global employees are solutions-oriented, accountable, and driven by one shared goal: making roads safer for everyone.
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 you’ll 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.

Join our team and lead the design, implementation and maintaining cutting-edge Data Platforms and Big Data Solutions. In this position, you will have the unique opportunity to significantly impact intelligence processes, contribute to the counter - terrorism efforts and leveraging advanced Big Data technologies.
Design, install, maintain and upgrade Big Data technologies
Monitor and optimize system performance, identifying areas for improving and implementing solutions
Provide technical support to internal teams and end - users, ensuring seamless operations
Design and implement advanced infrastructure solutions using the Hadoop Ecosystem
Analyze user requirements, evaluate and recommend new technologies in the Big Data domain.

We are looking for developers interested in joining exciting and innovative bigdata projects
This is a great opportunity for individuals seeking to develop solutions to the most challenging problems in the bigdata field, dealing with operational requirements while using cutting edge technologies.

We are seeking a highly organized and detail-oriented Operations Manager with a strong background in complex project management and a passion for AI technology and photography.

As the Operations Manager you will coordinate outsourced data tagging tasks, acting as a keystone between the product and AI teams to external partners and play a pivotal role in ensuring the seamless execution of tasks, a critical component of our AI algorithms for photographers.

Responsibilities:
Requirement Gathering: collaborate closely with the product and AI team to gather and understand the task requirements.
Task Planning: create comprehensive project plans that outline the technical description, goals, scope, timeline, and resources required for each task.
Task Monitoring: continuously monitor the progress, track success criteria, and address any issues or delays promptly.
Quality Control: conduct regular quality assessments of the annotated data from outsourcing agencies, ensuring alignment with our strict quality benchmarks.
Team Collaboration: act as the primary point of contact between the teams, providing regular updates on project status and addressing any questions or concerns in a positive and collaborative manner.
Enhancement and Refinement: actively seek feedback, both internally and from outsourcing partners, to iterate on and improve the annotation process and outcomes.

We are looking for an experienced NLP Data Science Team Leader to lead a team of talented NLP Data Scientists and drive the development of cutting-edge NLP solutions at scale. This role combines hands-on technical leadership, people management, and strategic influence over product and research directions.



Responsibilities

Lead and grow a team of NLP Data Scientists
Manage, mentor, and support team members professional development
Foster a culture of excellence, ownership, and continuous learning
Own end-to-end delivery of NLP solutions
Oversee algorithmic features from ideation through research, development, and production
Ensure high-quality, scalable, and maintainable solutions
Drive technical direction and innovation
Guide research efforts and evaluate new NLP/ML technologies
Translate business needs into impactful NLP solutions
Collaborate cross-functionally
Work closely with Product, Engineering, and Business stakeholders
Align team priorities with company goals and product roadmap
Maintain hands-on involvement
Contribute to architecture, modeling, and critical algorithmic challenges
Review code, experiments, and methodologies
Scale impact
Improve processes, workflows, and best practices for research and production
Ensure efficient use of large-scale data and infrastructure