דרושים » דאטה » Senior Analytics Engineer

looking for a Data Engineer to help build and scale our analytics data infrastructure. In this role, you will work closely with analysts and business stakeholders to design reliable data models and support the development of a centralized semantic layer used across the company.

You will play a key role in improving the structure, reliability, and usability of our data stack. This includes building and maintaining dbt models, supporting data pipelines, and ensuring analysts have access to clean, well-documented, and consistent data.

This role is ideal for someone who enjoys working at the intersection of data engineering and analytics - translating business needs into scalable data models and enabling teams to move faster with trusted data.

Responsibilities

Design and implement data models that support analytics across key business domains such as GTM, CX, and Finance
Build and maintain transformation workflows using dbt
Work closely with analysts to translate business questions into scalable and reusable data models
Help define and implement a structured semantic layer that enables consistent metrics across the company
Improve the reliability and clarity of the analytics data stack by centralizing logic into well-designed data models
Support the ingestion and transformation of data from various sources using tools such as Fivetran and Airbyte
Contribute to improving data quality, monitoring, and documentation practices
Help establish best practices for analytics modeling and data usage across teams
Actively leverage AI tools (e.g. Cursor, LLM-based assistants) to improve development speed, data modeling, and data workflows

We are looking for a Senior Analytics Engineer to help design and build the engineering foundation that powers analytics across the organization.
Our goal is to create a modern data environment where analytics development is fast, reliable, scalable, and increasingly automated. This includes building strong data warehouse foundations, scalable modeling layers, and introducing AI-powered tools and automation that accelerate how data products are built and used.
In this role, you will be part of an analytics squad, working closely with analysts and business stakeholders while building the infrastructure, automation frameworks, and intelligent tooling that enable analytics to scale across the organization.
This is a unique opportunity to help build the next generation of the data organization.
Key Responsibilities
Lead AI adoption in the analytics platform, building tools and workflows that automate analytics development, dashboards, and data exploration
Design and build scalable data warehouse models and transformation layers
Build and optimize ETL pipelines and core analytics infrastructure (Bronze / Silver)
Improve performance, reliability, and scalability of the analytics platform
Develop automation and internal tools that accelerate analytics workflows
Enable self-serve data access across the company through semantic layers and reusable datasets
Collaborate with analysts and business teams within an analytics squad.

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

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.

Were looking for a Senior BI Data Engineer to join our BI team and take end-to-end ownership of high-impact analytics foundations. This role sits at the core of how our company measures success, makes decisions, and scales - turning raw data into trusted, business-critical insights used across Product, GTM, and Finance.
Youll design and evolve data models, pipelines, and the BI layer, work closely with Data Science and business stakeholders, and help raise the bar for analytics engineering across the company.
Hands-on experience using GenAI to improve analytics engineering workflows, automate development processes, and increase delivery speed is a must for this role.
This role is based in Tel Aviv. We work in a hybrid model, with 3 days a week in the office.
This might be for you if:
You enjoy owning data foundations end to end - from raw data to semantic layers
You like turning ambiguous business questions into clear, governed metrics
You care about data quality, performance, and trust at scale
You enjoy mentoring, setting standards, and leading by example
You actively leverage AI tools to improve development speed and analytical accuracy.

We are looking for a hands on, proactive, and impact driven Senior Business Analyst to join our data team. In this role, youll shape how the company measures success and help embed a strong data driven culture across every domain, from business operations to product, finance, and beyond.

This is an opportunity for someone who thrives in dynamic, fast changing environments, loves building from scratch, and is just as comfortable running deep analyses and leading cross functional measurement discussions as they are partnering with data engineering to design scalable data models that empower the entire organization.

In this role you will
Collaborate with cross functional teams to understand business objectives and develop data driven solutions
Lead measurement and metric discussions with diverse stakeholders, translating needs into clear, consistent, and actionable definitions
Conduct deep dive analyses to uncover insights and deliver impactful recommendations
Partner with data engineering to design scalable data models and improve data accessibility
Build clear, intuitive dashboards and reports to track performance and enable self serve analytics
Proactively monitor business metrics and provide timely insights to optimize operations and identify opportunities
Promote a data driven culture by empowering teams to use data confidently in decision making
Mentor teammates and contribute to the growth and maturity of the data function

We are looking for a Senior Data Engineer to take ownership of our evolving data platform.

Our data environment is entering a significant growth phase. We are strengthening our Redshift-based warehouse, expanding our transformation capabilities with dbt, and investing in modern engineering standards across the stack.

In parallel, we are building a dedicated application layer for delivering data products. This role is responsible for designing and owning the data foundations that support it.

AI-assisted development is not a side experiment. It is a core part of how we engineer. We expect this role to actively leverage advanced AI development tools as part of daily work, accelerating design, implementation, validation and documentation while maintaining strong architectural judgment and production-level quality.

This position requires architectural thinking, long-term platform vision and the ability to lead complex initiatives from design through production in an AI-augmented engineering environment.

What You Will Do:

Own the architecture and evolution of our cloud-based Data Warehouse.

Lead complex data initiatives end to end, from requirements definition and technical design through implementation, deployment and post-production optimization.

Apply AI-assisted development workflows to improve engineering velocity, code quality and system reliability.

Design and evolve transformation standards and modeling practices using dbt as a strategic layer within the team.

Architect the data foundations that power our data-driven applications.

Translate business needs into structured, production-grade data solutions.

Drive technical standards, consistency and engineering discipline across the data stack.

Take full accountability for delivery, stability and long-term scalability of the systems you build.

Were looking for an experienced Data Engineer to join our DataWarehouse team in TLV.
In this role, you will play a pivotal role in the Data Platform organization, leading the design, development, and maintenance of our data warehouse. In your day-to-day, youll work on data models and Backend BI solutions that empower stakeholders across the company and contribute to informed decision-making processes all while leveraging your extensive experience in business intelligence.
This is an excellent opportunity to be part of establishing our state-of-the-art data stack, implementing cutting-edge technologies in a cloud environment.
We believe three things matter for every role: drive to push through challenges, efficiency that keeps standards high while moving fast, and adaptability that lets you pivot with data and AI insights. These aren't buzzwords, they're how we actually work.
Our AI-first approach isn't just a tagline either. We're building the future of insurance with AI at the center, and we need people who are genuinely excited to learn and grow alongside these tools.
In this role youll:
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 the semantic layer
Develop processes to enforce schema evaluation, cover anomaly detection, and monitor data completeness and freshness
Identify and address performance bottlenecks within our data warehouse, optimize queries and processes, and enhance data retrieval efficiency
Implement best practices for data warehouse and database performance tuning
Conduct thorough testing of data applications and implement robust validation processes
Collaborate with Data Infra Engineers, Developers, ML Platform Engineers, Data Scientists, Analysts, and Product Managers

We are looking for a Senior Data & Machine Learning Engineer to operate at the intersection of data platform engineering and machine learning enablement. This role is responsible for building scalable, efficient, and reliable data systems while enabling Data Science and Analytics teams to develop and deploy ML-driven features.

You will take ownership of the data and ML infrastructure layer, ensuring that pipelines, storage models, and compute usage are optimized, while also shaping how data workflows and ML solutions are designed across the organization.


Responsibilities
Data Platform & Infrastructure

Design, build, and maintain scalable data pipelines and storage systems supporting analytics and ML use cases
Ensure compute and cost efficiency across pipelines, storage models, and processing workflows
Own and improve data orchestration, transformation, and serving layers (e.g., Spark, DBT, streaming/batch systems)
Build and maintain shared infrastructure components, including:
IO managers and data access abstractions
Integrations with DBT, Spark, and other data frameworks
Internal tooling to improve developer productivity and reliability
ML Enablement & Collaboration

Partner closely with Data Science to design and productions ML solutions for new features and research initiatives
Translate experimental models into robust, scalable production systems
Support feature engineering, training pipelines, and inference workflows
Help define best practices for ML lifecycle management (training, validation, deployment, monitoring)
Data Quality, Governance & Best Practices

Enforce best practices for building and maintaining data processes across Data Analyst and Data Science teams
Define standards for:
Data modeling and transformations
Pipeline reliability and observability
Testing, versioning, and documentation
Improve data quality, consistency, and discoverability across the organization
Performance & Reliability

Optimize systems for performance, scalability, and cost efficiency
Monitor and troubleshoot data pipelines and ML systems in production
Implement observability (logging, metrics, alerting) across data workflows

Were looking for a Business Analyst - HR / People Analytics to join our fast-growing Business Analytics team and focus on building scalable people and workforce analytics capabilities across the company.
This role partners closely with People (HR), FP&A, and Data teams to deliver insights on workforce trends, hiring effectiveness, headcount planning, and people-related financial impact. The role complements existing HR analytics capabilities by focusing on cross-functional, strategic, and company-level analytics, in addition to operational HR reporting.
Youll combine strong analytical skills, understanding of people data, and business storytelling to help leadership make informed decisions about workforce planning, organizational health, and cost management.
Responsibilities
Talent & Recruitment Analytics
Analyze recruitment funnel metrics including time-to-hire, time-to-fill, conversion rates, and hiring velocity.
Support hiring plan tracking and capacity analysis in collaboration with HR and Finance.
Work closely with the HR Ops supporting Greenhouse to align data definitions and reporting logic.
Identify bottlenecks and improvement opportunities in the hiring process through data-driven analysis.
People & Workforce Analytics
Analyze workforce trends including headcount evolution, attrition, retention, internal mobility, and tenure.
Build reporting and insights around employee lifecycle metrics and organizational structure.
Partner with HR to improve data quality, definitions, and consistency across people systems.
Deliver actionable insights to People leadership and senior management on workforce health and risks.
Headcount, Cost & Financial Impact Analysis
Partner with Finance and FP&A to support headcount planning, forecasting, and scenario analysis.
Analyze the financial impact of hiring plans, attrition, and organizational changes on operating expenses.
Support workforce cost modeling, including payroll and people-related expenses.
Help align people plans with budget targets and company-level financial objectives.
Data & Analytics Operations
Use SQL and Snowflake to extract, structure, and analyze people-related data.
Build end-to-end dashboards and reports using Tableau (preferred), from data modeling to visualization.
Collaborate with Data /BI team to improve data pipelines, governance, and reporting infrastructure.
Leverage automation and AI-driven tools where applicable to improve reporting efficiency and scalability.
Cross-Functional Collaboration & Communication
Act as a trusted analytics partner to HR, Finance, and leadership stakeholders.
Translate complex data into clear insights and business stories for executive audiences.
Prepare presentations and analysis for leadership reviews, planning cycles, and strategic discussions.
Contribute to the continuous improvement of people analytics frameworks and reporting standards across the company.