We are looking for a Senior Data Engineer.
As a Senior Data Engineer, you will play a pivotal role in our Data Engineering team, driving a multitude of responsibilities essential to fueling our groundbreaking R&D endeavors. Youll have the autonomy to explore and implement cutting-edge technologies and data solutions, collaborating with diverse team of data scientists, developers, analysts, and stakeholders. Every day will present new learning opportunities and challenges as we strive together to reshape the future of work.
Responsibilities:
Design, develop, and maintain scalable data pipelines and infrastructure to support the collection, processing, and analysis of large volumes of data.
Collaborate with cross-functional teams, including data scientists, software engineers, and business stakeholders, to understand data requirements and develop solutions that meet business needs.
Implement best practices for data governance, security, and quality assurance to ensure the integrity and reliability of our data assets.
Optimize and tune existing data pipelines and processes for improved performance and efficiency.
Stay up to date with current best practices in the big data field.
Mentor and coach other members of the data engineering team, providing guidance and support to help them grow their skills and expertise.

We are seeking an experienced DataOps Engineer (the first position in our data organization) to join our dynamic team of analytics experts. In this role, you will play a pivotal part in both data ops and data engineering functions, contributing to the enhancement and maintenance of our data integration and pipeline processes, as well as ensuring the robustness and scalability of our data platform.
The ideal candidate is someone who thrives in a fast-paced environment, adept at both data engineering practices and DevOps principles. You should be passionate about optimizing data systems and possess a strong desire to continuously improve our companys data architecture to support evolving products and data initiatives.
In this role, you will be responsible for:
Develop and maintain ETL/ELT/Streaming processes and SQL queries for efficient data movement.
Design and implement scalable, automated processes for large-scale data analyses.
Engage with stakeholders to understand data requirements and build datasets accordingly.
Collaborate with teams to enhance data models and promote data-driven decision-making.
Contribute to the long-term strategy and architecture of the data platform.
Maintain data lake pipelines and ensure adherence to schema standards.
Apply data security standards and seek ways to optimize data flow.
Serve as the point of contact to the DevOps team and handle MLOps operations.

We are seeking an experienced Data Engineer to join our dynamic team of analytics experts. In this role, you will play a pivotal part in both data ops and data engineering functions, contributing to the enhancement and maintenance of our data integration and pipeline processes, as well as ensuring the robustness and scalability of our data platform.
The ideal candidate is someone who thrives in a fast-paced environment, adept at both data engineering practices and DevOps principles.
You should be passionate about optimizing data systems and possess a strong desire to continuously improve our companys data architecture to support evolving products and data initiatives.
In this role, you will be responsible for:
Develop and maintain ETL/ELT/Streaming processes and SQL queries for efficient data movement.
Design and implement scalable, automated processes for large-scale data analyses.
Engage with stakeholders to understand data requirements and build datasets accordingly.
Collaborate with teams to enhance data models and promote data-driven decision-making.
Contribute to the long-term strategy and architecture of the data platform.
Maintain data lake pipelines and ensure adherence to schema standards.
Apply data security standards and seek ways to optimize data flow.
Serve as the point of contact to the DevOps team and handle MLOps operations.

We are looking for a brilliant, quick-learner Data Engineer for our data engineering team - an independent logical thinker who understands the importance of data structuring for macro-business decisions.
The position combines high technical skills with business orientation, working closely with the analysts and the R&D team, and affecting the company's cross-departments decisions directly. Our Data Engineer should have the ability to speak in technical and practical terms, and more importantly, lead from one to the other, while dealing with challenges and creating them - to make our team even better than it is.
Roles and Responsibilities:
Creating and structuring end-to-end data pipelines & ETLs: from the source all the way to the analysts hands, enabling them the ideal conditions to make smart and data driven business decisions.
Cracking top industry data challenges while initiating and building creative technical solutions - in house Device Graph, Server-to-Server to multiple systems, Privacy challenges, Online-to-Offline and more.
Deep understanding of the business needs, technical requirements and the companys roadmap - and translating it into custom made data solutions and scalable products.
Craft code following best practices to ensure efficiency, while integrating CI/CD principles.
Writing multi-step scalable processes from more than 50 data sources - Marketing. Operations, CS, Product, CRM and more... tying them up to a valuable & useful source of insights for the analysts.
Understanding data challenges and weaknesses, and managing high standards monitoring and reliability processes.

We are looking for a talented Data Practitioner to join our team and revolutionize the world of external data! In this role, you will be in charge of designing, implementing, testing, deploying, and maintaining our data products, which include data pipelines and ETL processes.
Additionally, you'll harness cutting-edge data science and engineering technologies, such as DBT, Databricks, and Large Language Models (LLMs), to create novel solutions that address complex business challenges.
This role demands strong technical skills alongside a deep understanding of various business contexts, making it ideal for someone passionate about employing the latest technologies to produce meaningful and impactful business outcomes.
Responsibilities:
Lead the development of data products, effectively translating business needs into actionable technical specifications.
Employ cutting-edge technologies including DBT, LLMs, and GenAI to push forward our data science and engineering practices.
Take charge of the entire data product lifecycle, from the creation to the maintenance of ETLs and real-time data pipelines.
Use data science tools to extract actionable insights and valuable business indicators from large datasets.
Ensure high reliability and performance of production systems through robust testing, monitoring, and alerting procedures.
Conduct data analysis across various sources, bringing valuable insights to products and catering to sectors like manufacturing, CPG, and SaaS.

Were looking for an exceptional Data Team Lead to lead our data analytics team and transform the scraping industry. As a Head of Data, you will be a major focal point in the company, lead a team of data professionals and work closely with cross-functional teams to ensure data-driven decision-making and impactful insights.
What Youll be Doing:
Provide strong leadership and mentorship to a team of data analysts and data engineers by setting clear goals, providing regular feedback, and ensuring the teams professional growth and development
Work closely with Product, Sales and CS teams to gather needs for data insights and reports within the company
Own internal data in the company, including product and business analytics, end to end and be responsible for its delivery, infrastructure, accuracy and integrity
Work closely with the product team to lead data features of our own customer facing analytics dashboard
Lead the analysis of complex datasets to extract valuable insights, trends, patterns and anomalies that drive strategic decisions
Present findings and actionable insights to senior management and cross-functional teams
Lead the building and upgrade of existing data infrastructure to cope with performance, scalability, and growth ץ

Lead the design, implementation, and ongoing management of our company's data pipeline architecture.
Lead team architectural discussions
Manage a team of 2-3 data engineers
Work as an integral part of the data team and work closely with data Scientists, data Analysts and data Engineers.
Work directly with others (Developers, Product, and Internal stakeholders) to develop a solid understanding of the business application and requirements for which the application is being designed.

On our journey, we have discovered that building AI that delivers value in the real world, requires much more than just an algorithm - it requires mastering the data layers the algorithms are trained and evaluated on. AI organization, the data development achievements of our group are at the heart of improvements in our AI accuracy and scalability. We are among the few companies paving the way for methodologies and architectural patterns (that don't exist in this field yet) as we go.

Our AI Data Development Group is the data analytics core in our AI algorithms development process, and has several main areas of responsibility:

Mining the optimal data for our datasets, based on a deep understanding of the nuances of medical data, medical workflows, and algorithms.
Evaluating our algorithms performances, in order to maximize their success in real-world environments.
Facilitating data-driven product decisions through in-depth analysis.
Technical project management of the dataset development process.
Responsibilities
End-to-end ownership and technical project management of dataset development projects, for training and evaluation of AI algorithms, from ideation to delivery. This responsibility includes:
The facilitation of the data across various teams.
Detecting errors and anomalies in the data, defining the most efficient and accurate tables and views per project, and researching these issues to verify the quality signature of the dataset, which will have a sound effect on the product outcome.
Developing the optimal data pipeline per project.
Facilitating data-driven product decisions, by deeply understanding the product questions and identifying whether there are cost-effective data analyses that could provide a valuable answer to this question, based on a deep understanding of the relevant clinical workflows and algorithms.
Mapping bottlenecks in existing processes, and leading development of tools, infrastructure, and mechanisms to enhance our efficiency and decision-making processes at all levels.
Continuously assessing the projects risks and successfully mitigating them.
Develop and execute control and review processes for improving the teams quality signature on deliverables.

As a Data Engineer, you will play a pivotal role in shaping our evolving data culture. You will be responsible for collecting, organizing, and analyzing data to provide valuable insights that drive informed decision-making across the organization.
This is an opportunity to join a dynamic team and contribute to the development of data-driven solutions that drive business growth and innovation. If you are passionate about data and thrive in a collaborative environment, we encourage you to apply.
Responsibilities:
Collect and gather data from various sources, both internal and external.
Organize and clean datasets to ensure accuracy and reliability.
Utilize appropriate tools and software to analyze and visualize data effectively.
Collaborate with cross-functional teams to identify data needs and requirements.
Develop and implement data collection strategies to support business objectives.
Interpret data and provide insights to inform decision-making processes.
Create reports and presentations to communicate findings and recommendations.
Assist in the development of data-driven solutions to address business challenges.
Stay updated on industry trends and best practices in data analysis.

As an AI Solution Engineer, you will play a critical role in ensuring our AI solutions optimal performance, reliability, and continuous improvement. You will be responsible for monitoring the performance of AI models, detecting data drift, deploying AI modules, designing customized solutions, investigating issues, and developing tools to support data analysis. This role requires expertise in data science, system engineering, analytics, statistical analysis,product and clinical understanding, and proficiency in Python and SQL. The ideal candidate holds a relevant degree, with a master's degree being an advantage, and possesses hands-on experience managing AI solutions in an operational production environment.

Responsibilities
Deploying AI modules to production:

Collaborate with cross-functional teams to integrate AI solutions into existing workflows.
Deploy, configure, and implement hundreds of AI modules yearly using our orchestration mechanisms.
Design scalable deployment methodologies for new AI products
Address complex challenges associated with data in operational production environments, such as data quality, availability, and integration.
Collaborate with different stakeholders across the organization to make sure production requirements are addressed when new modules and products are developed.
Maintain our AI solutions in top performance:

Become a crucial part of our Ops team and work in a live operational environment, finding real-time solutions to complex problems.
Monitor the performance of AI solutions, ensuring they deliver accurate and reliable results using existing monitors.
Implement mechanisms to monitor and detect data drift to ensure AI models remain effective over time.
Design new monitoring solutions and metrics to address production issues, data drifts, and performance degradation.
Investigate issues raised by our customers and identify root causes, recommend corrective actions, and implement solutions to prevent reoccurrence
Tool Development:

Develop tools and scripts to support data analysts and ensure efficient data processing and analysis.
Visualize data in informative and to the point visualizations.
Automate tasks related to AI deployment, data validation, and reporting.