דרושים » תוכנה » Business Intelligence Expert

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're looking for a Data Warehouse Tech Lead to drive the technical vision and execution of our data infrastructure that powers decision-making across.
You'll lead both the technology and the business coordination for our data warehouse - architecting scalable solutions while working closely with stakeholders and data providers to ensure our platform serves the entire organization's needs. This role combines deep technical leadership with strategic business partnership as we build our next-generation data stack.
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 you'll:
Lead technical architecture - design and develop scalable data warehouse solutions that support multiple products and serve the entire organization's analytics needs
Manage the technical roadmap - set strategy and guide execution for the Data Warehouse team, ensuring our platform evolves with business requirements
Drive business process coordination - translate business needs into technical requirements while establishing clear data contracts with R&D, Analytics, and external data providers
Establish and implement best practices - set technical standards for data warehouse architecture, performance tuning, and development methodologies that guide the entire team's approach to building scalable data solutions
Create and maintain sustainable data pipelines - build resilient systems capable of handling unstructured data and managing an evolving schema registry across diverse data sources
Implement advanced data modeling - create robust data structures using methodologies like dimensional modeling, and optimize ETL/ELT processes for our semantic layer
Establish data quality standards - build processes for schema evaluation, anomaly detection, and monitoring data completeness and freshness across all sources
Lead cross-team collaboration - work directly with Data Engineers, ML Platform Engineers, Data Scientists, Analysts, and Product Managers to align technical solutions with business goals

we are looking for a Senior Data Engineer.
As a Senior Data Engineer, you will play a key role in shaping and driving our analytics data pipelines and solutions to empower business insights and decisions. Collaborating with a variety of stakeholders, you will design, develop, and optimize scalable, high-performance data analytics infrastructures using modern tools and technologies. Your work will ensure data is accurate, timely, and actionable for critical decision-making.
Key Responsibilities:
Lead the design, development, and maintenance of robust data pipelines and ETL processes, handling diverse structured and unstructured data sources.
Collaborate with data analysts, data scientists, product engineers and product managers to deliver impactful data solutions.
Architect and maintain the infrastructure for ingesting, processing, and managing data in the analytics data warehouse.
Develop and optimize analytics-oriented data models to support business decision-making.
Champion data quality, consistency, and governance across the analytics layer.

We are looking for a hands-on, strategic Business Application Manager with a proactive, ownership-driven mindset. Someone who takes initiative, thinks beyond the immediate task, and translates data into real business impact. This role requires a unique mix of systems expertise, project management, and analytical skills. Youll not only implement and optimize our platforms but also analyze ROI, create data-driven case studies, and help leadership make informed decisions.

Reporting to the VP of Customer Success, youll work cross-functionally with Sales, Marketing, Finance, Procurement, and Operations to ensure the company has the right tools, workflows, and insights to scale effectively.

This is part project manager, part systems owner, and part business analyst. Youll lead end-to-end implementations, integrate platforms like Salesforce, Intercom, Quicksight, create dashboards and reports, and drive process optimization across the business.


Key Responsibilities

Platform Ownership & Integration

Implement, configure, and maintain core business platforms: CRM (Salesforce), CS tools (Intercom/Zendesk), BI (Quicksight/Tableau), and others.

Serve as system administrator: manage configuration, user roles, workflows, and integrations.

Ensure data integrity and consistency across all systems; reduce silos and duplication.

Evaluate, procure, and integrate new tools as the company scales.


Data Analytics

Build and maintain dashboards and recurring reports for leadership and GTM teams.

Track and analyze key metrics: pipeline, revenue, churn/retention, customer health, support SLAs, and financial KPIs.

Define and maintain KPIs as a single source of truth; ensure alignment across teams.

Analyze ROI and build case studies to demonstrate impact and inform decision-making.

Leverage AI and automation to accelerate insights and improve reporting.


Process Optimization & Project Management

Lead end-to-end business application projects: from scoping and requirements gathering to implementation, testing, and adoption.

Map, analyze, and optimize cross-functional business processes (Customer Success, Sales, Operations).

Drive change management: document workflows, train teams, and promote adoption.

Manage project timelines, dependencies, and risks; deliver high-quality solutions on schedule.


Cross-Functional Enablement

Partner closely with GTM leaders to streamline forecasting, reporting, and operational cadences.

Support forecasting and planning processes, ensuring clean and accurate data.

Act as a trusted advisor to leadership on systems, processes, and data-driven decision-making.

Provide ad-hoc analysis and insights to inform strategy.

Were looking for an Analytics Engineer to join our team and play a key role in shaping how data drives our product and business decisions.
This role is perfect for someone who enjoys working at the intersection of data, product, and strategy. While Product Analysts focus on turning data into insights, youll focus on building the strong data foundations that make those insights possible. You wont just run queries; you will design the data architecture and own the "source of truth" tables that power our strategic decision-making.
Youll work closely with our Growth and Solutions teams, helping them move faster and smarter by making sure the data behind Generative AI, Data-as-a-Service (DaaS), and advanced product models is clear, reliable, and easy to use. Your work will have a direct impact on how we build, scale, and innovate our products.
What Youll Do
Define the Source of Truth: Take raw, complex data and transform it into clean, well-structured tables that Product Analysts and Business Leads can use for high-stakes decision-making.
Translate Strategy into Logic: Work with Product, Growth, and Solutions leads to turn abstract concepts (like "Activation," "Retention," or "Feature Adoption") into precise SQL definitions and automated datasets.
Enable High-Tech Initiatives: Partner with our AI and DaaS specialists to ensure they have the structured data foundations they need to build models and external data products.
Optimize for Usability: Ensure our data is not just "there," but easy to use. You will design the data logic that powers our most important product dashboards and growth funnels.
Maintain Data Integrity: Act as the guardian of our metrics. You will ensure that the numbers used across our product and business reports are consistent, reliable, and logical.

Were seeking an experienced and skilled Data and AI Infra Tech Lead to join our Data Infrastructure team and drive the companys data capabilities at scale.
As the company is fast growing, the mission of the data and AI infrastructure team is to ensure the company can manage data at scale efficiently and seamlessly through robust and reliable data infrastructure.
As a tech lead, you are required to independently lead the design, development, and optimization of our data infrastructure, collaborating closely with software engineers, data scientists, data engineers, and other key stakeholders. You are expected to own critical initiatives, influence architectural decisions, and mentor engineers to foster a high-performing team.
You will:
Lead the design and development of scalable, reliable, and secure data storage, processing, and access systems.
Define and drive best practices for CI/CD processes, ensuring seamless deployment and automation of data services.
Oversee and optimize our machine learning platform for training, releasing, serving, and monitoring models in production.
Own and develop the company-wide LLM infrastructure, enabling teams to efficiently build and deploy projects leveraging LLM capabilities.
Own the company's feature store, ensuring high-quality, reusable, and consistent features for ML and analytics use cases.
Architect and implement real-time event processing and data enrichment solutions, empowering teams with high-quality, real-time insights.
Partner with cross-functional teams to integrate data and machine learning models into products and services.
Ensure that our data systems are compliant with the data governance requirements of our customers and industry best practices.
Mentor and guide engineers, fostering a culture of innovation, knowledge sharing, and continuous improvement.

Join global data team building the infrastructure that powers analytics and AI-driven insights across the organization. As a Data Engineer, you'll design and maintain scalable data pipelines and systems that enable product analytics, business intelligence, and AI applications in our high-growth fintech environment.
What you'll do:
Design, build, and maintain robust batch and streaming pipelines and orchestration across our modern stack (AWS, DBT, Airbyte, Airflow, Snowflake) to support AI-driven data products.
Develop and optimize data models in Snowflake, ensuring data quality, consistency, and performance at scale.
Collaborate with Product Analysts and AI specialists to implement data solutions for customer segmentation, ranking systems, and predictive models.
Partner with cros-functional teams to translate technical requirements into scalable data architecture.
Implement end-to-end observability (data quality checks, monitoring, alerting) and cost/performance optimization in Snowflake and AWS.

Were looking for a hands-on Senior BI Engineer with a can-do attitude to shape data strategy and transform complex datasets into actionable insights that drive key business and product decisions. Youll collaborate closely with data engineers, product teams, and business stakeholders to modernize our analytics stack and deliver trusted, impactful insights across the company.
Your Impact
Own and evolve BI stack, data models, and reporting infrastructure to enable data-driven decision-making.
Define and govern core business metrics to ensure consistency and reliability across all teams.
Lead analyses across product, marketing, and revenue functions to identify growth opportunities and optimize performance.
Build intuitive dashboards and champion analytics best practices for technical and non-technical stakeholders.
Improve data quality, lineage, and governance as the company scales.

We are looking for an experienced and hands-on Data Engineer to lead the migration of enterprise data platforms to Google Cloud Platform (GCP).
In this role, you will design, build and maintain scalable ETL/ELT pipelines, develop advanced data models in BigQuery and contribute to the creation of a high-performance, reliable and cost-efficient data architecture.
You will work closely with analysts, data scientists and engineers and have real impact on how data is consumed across the organization.
What You Will Do:
Lead the migration of data from on-premise core systems to Google Cloud Platform (GCP).
Design and develop processed data layers (Silver and Gold) and data marts in BigQuery, including complex business logic.
Build, orchestrate and maintain data pipelines using Cloud Composer / Apache Airflow.
Develop robust data transformations, including cleansing, enrichment and data quality improvements.
Write efficient and optimized SQL queries in BigQuery with strong focus on performance and cost.
Create and maintain clear and up-to-date technical documentation for data architecture and processes.

our Data & Analytics team believes theres a better way to make data useful than just creating endless dashboards. We focus on in-depth analysis and building scalable, trustworthy data solutions that help every team make faster, smarter decisions. From analytics and business intelligence to data pipelines and predictive models, we turn raw information into real impact. If youre passionate about finding radical new ways to leverage data, youll fit right in.
On your day to day:
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.