דרושים » דאטה » Analytics Engineer

This role has been designed as Hybrid with an expectation that you will work on average 2 days per week from our office.

We are looking for a talented Data Engineer to help build and enhance the data platform that supports analytics, operations, and data-driven decision-making across the organization. You will work hands-on to develop scalable data pipelines, improve data models, ensure data quality, and contribute to the continuous evolution of our modern data ecosystem.

Youll collaborate closely with Senior Engineers, Analysts, Data Scientists, and stakeholders across the business to deliver reliable, well-structured, and well-governed data solutions.


What Youll Do
Engineering & Delivery
Build, maintain, and optimize data pipelines for batch and streaming workloads.

Develop reliable data models and transformations to support analytics, reporting, and operational use cases.

Integrate new data sources, APIs, and event streams into the platform.

Implement data quality checks, testing, documentation, and monitoring.

Write clean, performant SQL and Python code.

Contribute to improving performance, scalability, and cost-efficiency across the data platform.

Collaboration & Teamwork

Work closely with senior engineers to implement architectural patterns and best practices.

Collaborate with analysts and data scientists to translate requirements into technical solutions.

Participate in code reviews, design discussions, and continuous improvement initiatives.

Help maintain clear documentation of data flows, models, and processes.

Platform & Process

Support the adoption and roll-out of new data tools, standards, and workflows.

Contribute to DataOps processes such as CI/CD, testing, and automation.

Assist in monitoring pipeline health and resolving data-related issues.

We are looking for a highly analytical Data Analyst to join our Data Science team and support the development, evaluation, and improvement of data-driven models and research initiatives. In this role, you will work closely with data scientists to analyze large-scale behavioral and transactional datasets, generate insights, and help translate raw data into meaningful signals.
Responsibilities
Conduct exploratory analysis on large-scale behavioral and transactional datasets.
Partner with data scientists to support model development, evaluation, and validation activities.
Investigate patterns, anomalies, and trends in user behavior, fraud indicators, and system performance.
Build Python-based analytical workflows to support data investigations and research tasks.
Collaborate with engineering and data teams to maintain high standards of data quality and integrity.
Communicate analytical findings clearly and concisely to the data science team.

We are looking for a strong, hands-on Data Engineer to join our team and play a key role in building our data infrastructure from the ground up. In this role, you will design and implement scalable data pipelines and platforms, supporting both batch and real-time use cases. You will work closely with analysts and stakeholders to deliver reliable, high-quality data solutions, and take full ownership of data flows - from ingestion to consumption. This is a great opportunity for an executor who enjoys building, moving fast, and making an impact.
What will your job look like?
Design, build, and maintain robust and scalable data pipelines (batch and real-time) end-to-end.
Design and implement scalable, flexible data architectures to support evolving business needs.
Build and manage data platforms, including data lakes and data warehouses.
Integrate multiple data sources (structured and unstructured) into a unified data platform using batch (ETL) and real-time streaming solutions.
Design and implement efficient data models, schemas, and database structures (SQL / NoSQL).
Develop and implement data quality processes to ensure accuracy, consistency, and reliability.
Monitor, optimize, and troubleshoot data infrastructure to meet performance and SLA requirements.

We're looking for a Data Analyst to join one of our R&D. You'll design and deliver data-driven solutions that combine data analysis, statistical methods, improved heuristics, and ML models training to power our company's autonomous supply chain intelligence platform. You'll work closely with data science, engineering, product, and supply chain experts - owning solutions from problem definition to iterative improvement.
Responsibilities
Analyze large, multi-source operational datasets to identify trends, anomalies, and drivers of supply chain performance
Improve and maintain heuristic rules and analytical models for supply chain use cases (e.g., inventory risk, demand patterns, root-cause analysis)
Train and iterate on ML models to enhance existing analytical solutions
Define success metrics and evaluation plans with support from senior DS/PM; run error analysis
Work with stakeholders to create and maintain ground truth (label definitions, labeling workflows, QA checks, feedback loops)
Implement and refine hybrid decision logic by combining analytical outputs with statistical methods and SQL/rules-based logic for robustness and explainability
Collaborate with software engineers to support deployment of analytical solutions, including testing and logging
Monitor deployed models/rules, investigate performance issues (data quality, drift, edge cases), and iterate based on outcomes
Contribute to team practices: reproducible notebooks/code, documentation, and experiment tracking.

We are looking for a Data Analyst who will be part of our Growth team and have a significant ability to impact our business.
Whats the job?
Develop predictive models and perform advanced data analysis to generate key insights and actionable recommendations for high-level management.
Conduct deep analytical investigations, including hypothesis-driven analysis, data exploration, and anomaly detection, to uncover trends, root causes, and business opportunities.
Work closely with Customer Success, Product, and Business teams to analyze partner performance, identify optimization opportunities, and translate data insights into scalable operational improvements.
Build and maintain machine learning pipelines, data analytics automation tools, and scalable processes to improve company revenue, partner performance, and Customer Success operations.
Collaborate with the team to design experiments (A/B testing) and continuously improve the analytical and reporting processes through streamlined and scalable approaches.
Contribute to the development and maintenance of advanced data dashboards, reports, and visualizations that track business performance, model performance, and overall data health, and ensure robust data quality and tracking mechanisms.

This role has been designed as Hybrid with an expectation that you will work on average 2 days per week from our office.

We are looking for a highly skilled Senior Data Engineer with strong architectural expertise to design and evolve our next-generation data platform. You will define the technical vision, build scalable and reliable data systems, and guide the long-term architecture that powers analytics, operational decision-making, and data-driven products across the organization.

This role is both strategic and hands-on. You will evaluate modern data technologies, define engineering best practices, and lead the implementation of robust, high-performance data solutions-including the design, build, and lifecycle management of data pipelines that support batch, streaming, and near-real-time workloads.

What Youll Do

Architecture & Strategy
Own the architecture of our data platform, ensuring scalability, performance, reliability, and security.
Define standards and best practices for data modeling, transformation, orchestration, governance, and lifecycle management.
Evaluate and integrate modern data technologies and frameworks that align with our long-term platform strategy.
Collaborate with engineering and product leadership to shape the technical roadmap.

Engineering & Delivery
Design, build, and manage scalable, resilient data pipelines for batch, streaming, and event-driven workloads.
Develop clean, high-quality data models and schemas to support analytics, BI, operational systems, and ML workflows.
Implement data quality, lineage, observability, and automated testing frameworks.
Build ingestion patterns for APIs, event streams, files, and third-party data sources.
Optimize compute, storage, and transformation layers for performance and cost efficiency.

Leadership & Collaboration
Serve as a senior technical leader and mentor within the data engineering team.
Lead architecture reviews, design discussions, and cross-team engineering initiatives.
Work closely with analysts, data scientists, software engineers, and product owners to define and deliver data solutions.
Communicate architectural decisions and trade-offs to technical and non-technical stakeholders.

We are looking for a Senior Data Engineer to join the NSV (Network Solutions Validation) group. NSV builds high-performing software automation for our Data Center environments and helps drive the data growth of the world's biggest companies. In this role, you will design, build, and maintain scalable, high-performance data pipelines that handle massive volumes of data from hardware, communication modules, firmware, and large-scale AI and HPC clusters. You'll also contribute to our growing Agentic AI initiatives, helping develop AI Agents that bring our data capabilities to the next level.
What you'll be doing:
Define and execute the group's data technical roadmap, aligning with Infra, DevOps, and Performance teams
Design and maintain flexible ETL/ELT frameworks for ingesting, transforming, and classifying cluster verification and telemetry data
Build and optimize streaming pipelines using Apache Spark, Kafka, and Databricks, ensuring high throughput, reliability, and adaptability to evolving data schemas
Ensure data quality and pipeline health through observability standards, schema validation, lineage tracking, monitoring, and alerting
Deliver reliable insights for cluster performance analysis, telemetry visibility, and end-to-end test coverage
Support self-service analytics for engineers and researchers via Databricks notebooks, APIs, and datasets
Drive best practices in data modeling, code quality, and operational excellence; collaborate with cross-functional teams to support data-driven decision-making
Contribute to the development of AI Agents that enhance the visibility and accessibility of insights and data for our users.

we are looking for a Senior Analytics Engineer.
On a day-to-day basis, we transform raw data into clean, structured models using tools like SQL, Python, and dbt. We build and maintain modern BI platforms, develop reporting systems, and design AI-driven analytics that surface valuable insights quickly and reliably.
Our team is hands-on with building reusable metrics, defining source-of-truth data models, and ensuring consistency through a strong semantic layer. Whether were shipping a new dashboard, debugging a dbt model, or refining how a metric is defined across the business, our focus is always on clarity, scalability, and enabling smarter, faster decisions.

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

Were looking for a Data Analyst to join the Data for AI team. This is a hands-on, customer-facing role focused on working with leading AI companies to turn real-world data into inputs that support model development and evaluation.
Youll collaborate closely with external AI teams and internal engineering and product partners to deliver data-driven solutions for specific AI use cases. The work is fast-paced, technical, and often open-ended, requiring comfort with large datasets, ambiguous requirements, and end-to-end ownership.
What does the day-to-day looks like:
Own end-to-end delivery of data solutions for AI use cases, from understanding model and product requirements to analysis, implementation, quality, and automation
Work hands-on with large, raw datasets to create high-quality data inputs that support model training, evaluation, and iteration
Apply strong quantitative analysis and data exploration skills to assess coverage, quality, and behavior of data used in AI systems
Build scripts, analyses, and reusable components in Python and SQL to support scalable and repeatable workflows
Collaborate closely with Engineering to ensure solutions are reliable, scalable, and production-ready
Partner directly with external AI teams and internal stakeholders to translate open-ended questions into concrete data outputs