In an era where AI, Machine Learning, and Big Data are the core of every technological product, Data Engineers are the ones who support the entire infrastructure.
A Data Engineer is responsible for the systems that support all data processes. This core role in modern development teams connects systems, products, and people. They are responsible for building, deploying, and maintaining systems that handle data ingestion, storage, and processing in an organization.
Typical responsibilities include:
This role sits at the intersection of software engineering and DevOps, requiring deep technical expertise, systems thinking, and problem-solving skills.
Without Data Engineers – there is no infrastructure, no data, and no ability to transform data into business value.
Although all three roles work with data, they represent completely different stages in the data workflow:
Data engineers are key partners, working alongside data scientists and data analysts to make their work more efficient and effective.
In summary:
While Analysts and Scientists work with existing data, Data Engineers ensure that data exists, is reliable, and is accessible.
Data Engineering is a critical, in-demand and highly impactful role. In an era where AI and data are the heart of every product, without a Data Engineer, there would be no data to work with.
The Data Engineer role is one of the core positions in the world of data and AI. Data Engineers are responsible for designing, developing, and maintaining complex data infrastructures that enable organizations to work with large volumes of information, build intelligent models, and make data-driven decisions.
The Data Engineering career track at Infinity Labs R&D is an intensive, in-depth 22-week training program designed for bachelor’s degree graduates who want to become leading Data Engineering experts in the industry.
During the training, you will progress through three stages:
You will learn to apply this knowledge through real-world projects, working at the pace and standards of high-tech research and development teams.
Throughout the program, our client relations department and your mentors work intensively to secure your first position – typically a role requiring 2–3 years of experience. Over the past decade, Infinity Labs R&D has found jobs for more than 2,500 graduates at top-tier Israeli companies.
22 weeks Sunday - Thursday 08:30-18:30
Jabotinsky 1 Ramat Gan next to Savidor Merkaz train station
A unique WIN-WIN-WIN model, where we help you secure your first job with one of our 300+ client companies
The training takes place at the Infinity Labs R&D offices, located in the heart of the Bursa District in Ramat Gan, within walking distance of Savidor Center train station.
The location provides convenient access from Tel Aviv, the greater Gush Dan area, the Sharon region, and the Shfela, as well as easy access for participants arriving from the north and south of the country via train and public transportation.
The Infinity Labs R&D Data Engineering track is structured as a progressive training process that equips participants to design, develop, and operate data systems like professional Data Engineers.
The program begins with fundamental software engineering skills, advances through Big Data architectures, and culminates in building production-grade, end-to-end data systems.
Below is an overview of the program’s key training areas and core principles.
In-depth technical breakdown is available in the full syllabus.
The first stage focuses on building the stable, reliable, and scalable software development infrastructure that is the foundation of all modern data systems. Participants develop a systems-engineering mindset, learning how code behaves under load, integrates with infrastructure, and remains readable, efficient, and maintainable over time.
Learning is hands-on, accomplished through practical projects that simulate industry standards, with an emphasis on code quality, testing, automation, and end-to-end ownership.
Key topics:
The second stage moves from focusing on individual components to taking a broad, systemic view. Participants learn to build data pipelines and design large-scale data infrastructures: understanding how data flows, changes, and scales in distributed environments, while designing systems capable of handling large volumes of information and complex operational challenges.
The emphasis is on engineering real-world data pipelines and working with distributed systems, batch processing and streaming architectures, as practiced in technology, fintech, and AI companies.
Key topics:
In the final stage, participants integrate all components into a full production system. They design, implement, and maintain production-grade data systems, simulating full responsibility for reliability, availability, and accuracy—just like professional Data Engineers in the industry.
The stage emphasizes ownership, engineering decision-making, and addressing real challenges in live systems.
Key focus areas:
The Infinity Labs R&D Data Engineering track is structured as a progressive training process that equips participants to design, develop, and operate data systems like professional Data Engineers.
The program begins with fundamental software engineering skills, advances through Big Data architectures, and culminates in building production-grade, end-to-end data systems.
Below is an overview of the program’s key training areas and core principles.
In-depth technical breakdown is available in the full syllabus
The first stage focuses on building the stable, reliable, and scalable software development infrastructure that is the foundation of all modern data systems. Participants develop a systems-engineering mindset, learning how code behaves under load, integrates with infrastructure, and remains readable, efficient, and maintainable over time.
Learning is hands-on, accomplished through practical projects that simulate industry standards, with an emphasis on code quality, testing, automation, and end-to-end ownership.
Key topics:
The second stage moves from focusing on individual components to taking a broad, systemic view. Participants learn to build data pipelines and design large-scale data infrastructures: understanding how data flows, changes, and scales in distributed environments, while designing systems capable of handling large volumes of information and complex operational challenges.
The emphasis is on engineering real-world data pipelines and working with distributed systems, batch processing and streaming architectures, as practiced in technology, fintech, and AI companies.
Key topics:
In the final stage, participants integrate all components into a full production system. They design, implement, and maintain production-grade data systems, simulating full responsibility for reliability, availability, and accuracy—just like professional Data Engineers in the industry.
The stage emphasizes ownership, engineering decision-making, and addressing real challenges in live systems.
Key focus areas:
The Data Engineering career track is built around the Infinity Mentored Social Learning (IMSL™) methodology, an approach developed over the years to simulate the experience of working within a real R&D team.
Participants work in small groups of about 14 students, guided by an experienced Tech Leader from the R&D and Data fields. The learning process focuses on tackling complex problems, conducting independent research, running systematic experiments, writing production quality code, and critically evaluating results.
There are no frontal lectures, no passive learning, and no traditional exams. Success is measured by the ability to take a complex Data problem, break it down, explore different approaches, implement solutions, measure outcomes, and arrive at a high quality result within a defined timeframe.
Learning Principles
The program takes place five days a week, Sunday to Thursday, from 08:30 to 18:30, at the Infinity Labs R&D labs in Ramat Gan.
This is a full time and intensive training program. In most cases, it does not allow participants to work in parallel, due to the level of commitment and depth required.
The Data Engineering track is suitable for bachelor’s degree graduates in STEM fields (Computer Science, Physics, Mathematics, Neuroscience, Engineering, etc.), as well as graduates in Economics, Accounting, or any academic degree with strong academic performance. We seek highly capable, self-driven individuals who are ready to work hard to build a professional career in Data Engineering.
The role is also well-suited for individuals with strong critical thinking, communication skills, and the ability to make information accessible while providing solutions and support. Data Engineers interact daily with multiple parts of an organization.
Key soft skills:
The training program takes place at Infinity Labs R&D offices in Ramat Gan, Jabotinsky 1, in the heart of the stock exchange – a short walk from Savidor Merkaz station, accessible by train and public transportation from Tel Aviv, Gush Dan, Sharon, and Shfela.
To maintain the depth and intensity of the program, the admission requirements are clearly defined:
These requirements ensure that the program maintains the level of depth, pace, and professional standards required for training Data Engineers for industry.
Graduates join core data teams in high-tech companies, startups, banks, defense organizations, and other data-intensive environments. Thanks to the program’s practical and in-depth training, they work on designing, developing, and maintaining data infrastructures and production systems.
Graduate roles include:
In practice, graduates work on the infrastructures that power digital products, algorithms, analytics systems, and AI applications, often in complex, large-scale environments.
With a background in Economics and experience in data analysis, he transitioned into a Software and Data Engineering role within an R&D team. His work involved building complex data infrastructures, developing ETL processes, and managing backend development—a foundation that led him to head a data team at a prominent technology company in Haifa.
Today, he holds a key engineering role at Google, where he applies his deep expertise in systems optimization and large-scale data architecture.
A Computer Science engineer chose the program to acquire the specialized engineering tools required to operate within the global data and cyber domains.
Today, as a Data Engineer at an international company, her role involves designing advanced data solutions and managing the complex technological interfaces between Data Science and research teams. The professional capabilities she developed during the program enable her to lead high-stakes projects at the intersection of development and analytics, ensuring seamless data continuity and quality across large-scale systems
With a strong background in Computer Science, he integrated into an engineering role following the program that combines data and software domains. His ability to approach complex problems with analytical thinking enables him to develop smart data infrastructures tailored to the company’s DevOps needs.
Today, as a Data Engineer at a leading technology company, his responsibilities include designing and implementing advanced data solutions that ensure high performance and reliability across the company’s global software products.
With a strong background in Mathematics and an affinity for solving complex technological challenges, he integrated into a Data Engineering role following the program. During the track, he stood out for his ability to learn independently and overcome complex challenges – skills that now serve him in developing data infrastructures in a Cloud environment.
His responsibilities include designing and implementing smart data solutions and integrations for large-scale BI systems, tailored precisely to the needs of the organization’s clients.
A graduate of Industrial Engineering and Management from a leading institution found that transitioning into Data Engineering was a natural progression of her strengths in optimization and systems thinking. During the program, she acquired the critical technological skills necessary to design advanced cloud architectures and optimize large-scale data systems.
Today, she develops complex data infrastructures within a Google Cloud Platform (GCP) environment for leading high-tech clients. In this role, she manages end-to-end data processes, bridging the gap between sophisticated engineering theory and high-performance industrial application.
Data Engineering is not just a set of tools — it is a meaningful profession that forms the basis of all data systems, which are the foundation of modern technology.
Short courses often focus on learning specific tools, whereas our career track prepares you to work as a professional Data Engineer in environments that simulate real industry conditions.
Our program emphasizes the full ecosystem of data systems — not only technical skills, but also systems thinking and effective communication with both those who produce raw data and those who consume it.
And what about your first job? We take care of that too. Throughout the training program, leading companies from among our 300+ partners interview you for your first Data Engineer role, which typically requires 2–3 years of experience.
For those seeking a data course or general data studies, this program offers much more — a complete retraining and specialization track designed to build a long-term, stable, and rewarding career.
Infinity Labs R&D is a research and development company founded in 2014 that prepares university graduates for careers in high tech through a training environment designed to simulate real industry R&D teams. The program is conducted in small groups of about 14 participants, guided by an experienced Tech Leader, and focuses on working on complex projects at an industrial level.
Students are carefully selected based on their academic background and strong quantitative abilities. During the program, they develop systemic thinking, independent problem solving skills, and the ability to work within Data Engineering and Data platform teams at leading organizations.
To date, more than 2,500 graduates have joined roles that typically require 2 to 3 years of prior experience, across over 300 high tech companies, defense organizations, and leading development centers.
The combination of deep technological training, work in a real R&D style environment, and a comprehensive placement framework is what differentiates Infinity Labs from other training programs.
Key Advantages
The Data Engineer career track at Infinity Labs R&D is an intensive 22 week training program that takes place five days a week at the company’s Ramat Gan labs. The program focuses on building production ready data systems and infrastructure used in modern data driven organizations.
The program is designed for university graduates in STEM fields such as computer science, mathematics, physics, engineering and other analytical disciplines who want to specialize in building data infrastructure and large scale data systems.
Data Engineers design and build the infrastructure that enables organizations to collect, store and process large volumes of data. Their work includes building data pipelines, managing databases, working with distributed systems and ensuring that data is accessible for analytics, machine learning and business applications.
Data Engineers focus on building the data infrastructure and pipelines that make data available and reliable. Data Scientists focus on analyzing that data, building predictive models and extracting insights. Both roles work closely together in modern data teams.
Data Engineers combine software engineering skills with knowledge of data infrastructure. Important skills include Python programming, SQL, data pipeline development, distributed systems, cloud platforms and system architecture. Strong analytical thinking and problem solving skills are also essential.
Data Engineers commonly work with technologies such as Python, SQL and NoSQL databases, Apache Spark, Kafka, ETL pipelines, distributed data systems and cloud platforms used to store and process large scale data.
Graduates of the program typically pursue roles such as Data Engineer, Big Data Engineer, Data Platform Engineer and Data Infrastructure Engineer in technology companies, startups and large organizations.
The training is free for accepted candidates as part of the Infinity Labs R&D training model.
If you are a STEM graduate with strong analytical skills and an ambition to build large scale data systems, the Data Engineering career track at Infinity Labs R&D was designed for you.
up to 50,000 NIS to help with living expenses. Payable upon start of employment or after 1 year.
"The typical recruitment process for inexperienced developers often feels like a gamble due to the lack of prior experience and recommendations, so we seek out those who can demonstrate their wisdom and motivation. Infinity Labs R&D's training program stands out as a great route, offering thorough foundational learning with an emphasis on teamwork. I appreciate the structured approach of meeting motivated individuals during our focused recruitment days, knowing they will integrate seamlessly into our company culture. With several Infinity Labs R&D alumni on our team, all proving themselves as adept developers who seamlessly blend in, it's clear the investment pays off"
"We started with a pilot to assess if Infinity Labs R&D graduates could integrate as part of the team and swiftly add value. The pilot was a great success, so we extended our collaboration. The interview screening and selection process is efficient, consistently delivering high-quality candidates with exceptional learning abilities. Over 80% of our recruits are Infinity Labs R&D graduates, with the majority evolving into long-term assets for our company. It serves as a testament to the mutual success fostered by this partnership"
"Some of our recruits were from Infinity Labs R&D, where they undergo dedicated training according to a pre-defined syllabus so that they arrive as ready as possible for our tasks, and they do arrive ready. We got the people, they were successfully absorbed into the organization pretty quickly, and mostly demonstrated independent learning abilities and entered into new domains they were not familiar with prior. Over time I have seen that the quality of the people is truly exceptional. I am very satisfied with the people on both a personal level and professional level"
“There are several reasons why I decided to recruit from Infinity Labs R&D. Knowing that the participants are undergraduates, my understanding is that the training process is very demanding and in general the method includes a lot of practice while studying independently, as well as teamwork which simulates the way I work. Another thing I like is knowing that if I require one’s completion of technological knowledge specific to my needs, Infinity Labs R&D will complete it"
"We needed to recruit a very large number of people and we certainly have a place to recruit those who are completing a degree that is not necessarily in the sciences – or very talented people who are interested in and have a passion for software. It helps us increase our recruitment capacity and get great people"
"The things I look for and that are important to me as an employer are what I have found in our employees from Infinity Labs R&D. They have the ability to learn on their own, to take a task, understand it, go look for solutions, find them and realize them"
"Infinity Labs R&D's processes work well. The workers always come ready, work well, work like everyone else and are an integral part of the production of the company product"
"I was impressed by the learning abilities of the Infinity Labs R&D graduates that we interviewed, especially their mindset – they have a deep understanding of technology and excellent problem-solving skills. We successfully recruited graduates from them for a diverse range of cybersecurity roles. After interviewing several cyber track graduates, we quickly realized we had found the right company to work with, where candidates aligned with our expectations. If you are looking for efficient, high-quality candidates, I strongly recommend recruiting from Infinity Labs R&D"
Over the past few years, we have recruited several Infinity Labs R&D graduates in the fields of DevOps and C++ programming. Every one of them has integrated seamlessly into the company, demonstrating high technical skills, high energy, a desire to learn and improve, and a drive to make an impact. The interview process is efficiently managed, enabling interviewers to select the right candidate quickly and effectively. Infinity Labs R&D has proven itself as a leader in its field, with a professional and dedicated team that pays close attention to detail. I was impressed by the high level of service, deep knowledge, and personal approach.
