דרושים » תוכנה » Data Analytics Engineer (Maternity Cover)

We are looking for a hands-on Data Lead to build and own our data domain end-to-end.
This is a key role for someone who combines strong engineering capabilities, deep data passion, product thinking, and business understanding. We are looking for a builder who can independently create the data infrastructure, deliver reliable dashboards and insights, support product and business decision-making, and turn data into a strategic asset for the company.
This is not just a reporting or BI role. You will be responsible for building the data foundation that will support our next stage of growth- across infrastructure, product analytics, business insights, executive reporting, customer-facing analytics, and future AI-driven use cases.
What youll do:
Own our data domain end-to-end- from infrastructure and pipelines to dashboards, insights, and business impact.
Build and maintain scalable data pipelines across product, finance, GTM, customer, and operational data sources.
Design reliable data models and create a clear source of truth for key company metrics.
Build business and executive dashboards that help leadership understand the state of the business.
Analyze product usage, engagement, adoption, retention, feature performance, and customer value.
Support Product, R&D, Sales, Marketing, Customer Success, Finance, and leadership with meaningful data insights.
Translate business and product questions into clear data analysis and actionable recommendations.
Work closely with R&D, while being technically independent and able to build and deliver solutions without relying on engineering support for every step.
Define data standards, documentation, quality checks, metric definitions, and best practices.
Use modern AI tools to accelerate data development, analysis, documentation, automation, and insight generation.
Identify opportunities where our data can support smarter product experiences, automated insights, customer-facing analytics, and AI-supported decision-making.

We are looking for an experienced Data Engineer to own and evolve data infrastructure and analytics platform.

You will design and build scalable data pipelines and data models, working with large and diverse datasets generated across Trigos global retail deployments. You will own the data lifecycle from ingestion and transformation through orchestration, reliability, and analytics-ready datasets.

As a key technical owner of data platform, you will also work closely with analysts, Product, R&D, Operations, and Customer Success to build trusted data products, evolve our BI semantic layer, and turn complex data into scalable solutions

A day in the life
Design, build, and maintain scalable ETL/ELT pipelines processing large and diverse datasets.
Own and evolve data architecture, from ingestion and transformation through analytics-ready data models and consumption.
Build reliable data workflows and orchestration processes, with a focus on scalability, performance, and maintainability.
Design and maintain curated data models that power analytics, operational workflows, and data-driven products.
Ensure data quality, observability, monitoring, and reliability across datasets and pipelines.
Develop and evolve the BI semantic layer, enabling trusted metrics and self-service analytics across the company.
Work closely with R&D and Product on data integrations and new data-driven capabilities, including use cases that bridge offline analytics and production systems.
Partner with analysts and business stakeholders to translate complex requirements into scalable data solutions.

We are looking for an Analytics Engineer (contract) to join Artifactory Product Analytics and build the data platform behind how we measure our products. You will own the engineering side of analytics: designing product telemetry with PMs and R&D, modeling that data into trusted, reusable datasets in the warehouse, and making those datasets easy for analysts and stakeholders to consume. Product analysts own the product questions and metric definitions; you make the data underneath them fast, consistent, and dependable.
You will work inside an AI-native analytics environment (Cursor, Claude, and similar coding agents) as the default way of shipping - not as an optional add-on.
Fixed-term contract: 6-8 months. Start date: October 12, 2026.
Responsibilities:
Design telemetry: partner with PMs and R&D to define event and data specs for product usage - schemas, properties, validation, and the path into the warehouse (core, ongoing part of the role)
Build the modeled layer: develop and maintain dbt transformation models (staging → intermediate → gold) so Artifactory product data is consistent, tested, documented, and reusable
Enable self-serve: with the analysts, design and implement how stakeholders reach certified product data so recurring questions don't need a custom pull
Align definitions: standardize entities, grain, and model structure across Artifactory areas together with the analysts who own product meaning
Ship in an AI-native workflow: specs, SQL, dbt models, reviews, and documentation done in Cursor / Claude and equivalent tools.

We're looking for Product Data Analyst to own the numbers behind Ace and play a central role in shaping product decisions. Youll work closely with Product, Engineering, Growth, and company leadership to understand how people use Ace
Youll own the analytical process end to end: identifying the right questions, defining metrics, designing experiments, working directly with product data, interpreting results, and translating findings into clear product decisions.
We move fast, experiment constantly, and expect analysts to be hands-on, curious, technically strong, and comfortable challenging assumptions.
What You'll Do:
Own the consumer funnel end to end. Analyze acquisition, install, onboarding, activation, engagement, retention, and monetization across desktop and mobile. Identify where users drop, understand why, quantify the opportunity, and turn insights into concrete product opportunities.
Run the experimentation engine. Own experiments end to end - identify whats worth testing, define the right metrics and methodology, analyze the results, and translate learnings into clear product decisions.
Go deep into the data. Work directly with large-scale behavioral data to investigate questions, uncover patterns, diagnose problems, and find opportunities that arent obvious from a dashboard.
Shape how we measure the product. Define the metrics that matter, make sure were measuring new features correctly, and create a trusted analytical foundation for understanding product performance.
Be a strategic product partner. Work closely with Product and leadership to frame important questions, challenge assumptions, and bring a strong data-driven perspective to product strategy and prioritization.
Use AI to work differently. Use modern AI tools as part of your daily workflow to explore faster, investigate deeper, automate repetitive work, and build lightweight solutions when needed.
Make the organization faster with data. Build frameworks and self-service capabilities that help teams answer common questions independently, so your time stays focused on the highest-impact problems.

We are looking for a brilliant Data Engineer- an independent, logical thinker who enjoys solving complex problems and building scalable data solutions. You will own and evolve the data foundations that power Product, Finance, Operations, and Business teams. Working closely with diverse stakeholders, Analysts, and R&D teams, you will serve as a technical partner, translating complex business challenges into robust data models, pipelines, and infrastructure. You should be able to translate business and data requirements into scalable data pipelines and data models, integrating multiple internal and external data sources using the most appropriate technologies. Beyond building pipelines, you will improve data quality, modernize existing data assets, automate manual workflows, and help create a clean, reliable, and scalable data ecosystem that supports the company's growth.
Roles and Responsibilities:
Design and build end-to-end data pipelines - From defining source structures and integrating APIs to delivering clean, trusted datasets that enable analytics, reporting, and operational workflows.
Translate business needs into scalable data solutions based on business priorities and the product roadmap, understand technical requirements, and deliver purpose-built pipelines and tools.
Act as the technical partner for Product, Finance, Operations, and R&D teams, translating business needs into scalable data models, pipelines, and internal tools while ensuring reliable, trusted data across the organization.
Write high-quality, maintainable code, while following best practices and leveraging modern data tooling and CI/CD principles.
Drive data quality and reliability - Monitor, validate, troubleshoot, and continuously improve data quality and pipeline reliability across the data platform.

We are looking for a Backend Engineer with deep data engineering expertise to build and evolve the systems that power product, analytics, experimentation, and AI development.
You will work across production backend services and data infrastructure, taking technical ownership of the full data lifecycle - from event ingestion and real-time processing to orchestration, modeling, quality, and reliable data access. This role combines hands-on backend development with ownership of shared data platform, working closely with backend, frontend, AI, DevOps, analytics, and product teams.
What you'll do:
Build and maintain production-grade Python and Java backend services, APIs, and reactive data-processing pipelines with clear interfaces, resilient failure handling, and comprehensive observability.
Own and evolve batch and streaming data pipelines supporting product analytics, learner insights, experimentation, and AI model training.
Design and maintain trusted data models, shared metrics, and semantic-layer business logic across the analytical data platform.
Define and enforce standards for data contracts, testing, lineage, freshness, and observability.
Develop reliable approaches to schema evolution, backfills, replay, workload distribution, and failure recovery.
Collaborate with DevOps, backend, frontend, AI, analytics, and product teams to deliver reusable data capabilities and maintain clear system boundaries.

We are looking for an experienced Senior Data Engineer to join our Data team. In this role, you will lead and strengthen our Data Team, drive innovation, and ensure the robustness of our data/analytics platforms.
A day in the life and how youll make an impact:
Design and develop high-performance Data Pipelines and ETL processes to support diverse business needs.
Work closely with Product, Business Intelligence, Sales and other teams to integrate data solutions, ensuring seamless alignment and collaboration across functions.
Continuously improve our data analytics platforms, optimizing system performance and ensuring robust, reliable data infrastructure.
Oversee the entire data lifecycle, from infrastructure setup and data acquisition to detailed analysis and automated reporting, driving business growth through data-driven insights.
Implement robust data quality checks, monitoring mechanisms, and data governance policies to maintain data integrity and security, troubleshooting and resolving any data-related issues efficiently.

As our Founding Data Engineer, you will be the first dedicated Data Engineer at the company, with the opportunity to build our data engineering function from the ground up. You'll own the architecture and foundations of our internal data platform - the central warehouse, pipelines, and models every team relies on to understand how our product is performing, and provide tools for day to day operations. You'll define how data from across the company is collected, modeled, transformed, and governed, and establish the standards and best practices that will scale with us as we grow. Working closely with Engineering, Data Science, Delivery, Product, and Analytics teams, you'll turn data into reliable, structured assets that power product and business decisions.

What Youll Do
Build our Data Engineering Function: Be the first dedicated Data Engineer and will be required to be opinionated about the warehouse architecture, tooling, standards, and best practices for how we work with data across the company.
Develop Data Pipelines: Design, build, and maintain data pipelines that transform company data into structured, queryable assets.
Enable Data-Driven Decisions: Partner with Engineering, Data Science, Product and Analytics teams to deliver trusted data foundations and actionable insights.
Create BI Dashboards: Build and maintain dashboards and reporting layers that support product, and operational decision-making.
Ensure Data Quality and Accessibility: Implement best practices for data modeling, governance, monitoring, and reliability.

Required Data Analyst
Description
We're transforming the way fleets operate by leveraging data, automation, and AI to power smarter mobility. As a Data Analyst, you'll play a key role in shaping product strategy and business decisions by turning complex data into actionable insights. You'll partner with Product, Engineering, and customer-facing teams to build scalable analytics solutions, define success metrics, and uncover opportunities that drive impact across our platform
What youll do:
Own the product analytics domain for key products and strategic initiatives, with a focus on user behavior and product engagement.
Design, build, and own our product analytics infrastructure (event tracking, taxonomy, instrumentation) from the ground up, primarily using Mixpanel.
Define and maintain a clean, scalable event-tracking taxonomy in partnership with Engineering and Product.
Analyze large-scale product and behavioral datasets to identify trends, opportunities, and business insights.
Design, build, and maintain dashboards and reporting solutions using Mixpanel and other modern BI tools.
Develop automated data pipelines and analytical workflows using Python and Airflow.
Partner closely with Product Managers to define KPIs and metrics (activation, retention, funnels, engagement), measure success, and support product decision-making.
Work with customer-facing teams to provide insights and occasionally participate in customer discussions and presentations.
Build internal tools and processes that improve data accessibility and operational efficiency.
Translate complex data findings into clear recommendations for both technical and non-technical stakeholders.

we are on a mission to create public transportation systems that provide far greater access to jobs, healthcare, and education. Our platform serves as the technology backbone for modern transit networks, transforming antiquated and siloed public transportation systems into smart, data-driven, and efficient digital networks. With hundreds of agency partners around the world, we are recognized as the leading transportation technology and service provider globally.
As a Software & Data Engineer at our company, you will play a central role in building and evolving the data infrastructure that powers one of the world's leading transportation platforms. You'll work with rich, complex transportation data - from ride bookings and payments to real-time operational signals - designing the pipelines and systems that turn raw data into clean, reliable, and actionable insight across the business. This is a high-ownership role on a talented and deeply motivated engineering team in Tel Aviv, where your work will directly shape how our company understands and improves its service for cities and riders around the world.
About the Role:
Design and build highly scalable, reliable data pipelines that serve clean, structured data across our company's engineering, product, and business teams - ensuring the entire organisation can trust the data it works with
Own the architecture of complex data models that translate messy, real-world transportation data - bookings, payments, driver activity, and more - into systems that are fast, efficient, and built to scale
Lead end-to-end development across the full data lifecycle: from architecture and design through to deployment, monitoring, and continuous improvement
Proactively monitor data quality and reliability, identifying and resolving discrepancies before they reach stakeholders - building the kind of data infrastructure people can depend on
Collaborate with a broad forum of engineers, analysts, and business stakeholders to identify data needs, design POCs, and ship scalable solutions that make a real difference to how our company operates
Contribute to the adoption and evolution of our modern data stack, including DBT, Airflow, Iceberg storage, and AWS big data tooling such as Glue, EMR, and Athena.