לוח משרות דרושים Business Intelligence בתל אביב יפו, לחיפוש זה נמצאו 23 משרות

Were looking for a Data Engineer to join our company. This is a hands-on, cross-functional role focused on owning and improving our data quality, pipeline reliability, and modeling infrastructure. Youll be responsible for managing and optimizing our DBT models, ETL processes, and data connectors - and will work closely with product, operations, and engineering teams to ensure data is accurate, consistent, and accessible.

You should be someone who thrives on autonomy, takes pride in clean and scalable solutions, and enjoys helping others get the data they need.

In this role you will
Architect our entire DBT project and data warehouse structure completely from scratch-a rare, high-impact opportunity
Lead data modeling efforts: Translating business needs into scalable, reliable data models
Build and monitor data pipelines and connectors from various internal and external systems
Ensure high standards of data quality, consistency, and documentation
Collaborate with engineering, product, and operations teams to understand needs and build data solutions
Proactively detect data issues and work to resolve them
Help define and improve internal data best practices and standards
Support data governance efforts and advocate for trustworthy, well-modeled data
You will be one of the pioneers of a new team - passion & energy is required

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 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 engineeing 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

Were looking for a Data Engineering Team Lead to take ownership of Ports data engineering team and help shape the future of agentic engineering portals. This is a hands-on leadership role: youll guide a team, drive technical direction, and help establish Ports data warehouse both for product use cases and for internal business analytics.

What youll do:

were building a platform by developers, for developers. As a Data Engineering Team Lead, youll balance leadership and data engineering work - setting technical direction while enabling your team to thrive.

Your responsibilities will include:

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 a shared data warehouse.
Identify and address performance bottlenecks within our data warehouse, optimize queries and processes, and enhance data retrieval efficiency.
Develop and provide a data backend for product facing features such as usage analytics, data insights and enabling an agentic context lake
Collaborate with cross-functional teams (product, R&D, analysts) to deliver actionable data solutions tailored to their needs.

We are seeking a Senior BI Engineer to serve as the primary interface and strategic analytics partner between Data Engineering / DWH teams, management, and business leaders. In this strategic role, you will work closely with leadership and business partners to translate business objectives into actionable data solutions, establish analytics standards and best practices, and lead experimentation across core business processes. You will also plan, prioritize, and manage analytics initiatives and roadmaps, ensuring the timely delivery of insights and solutions that drive informed decision-making across Marketing, Sales, Finance, Support, and Customer Success.

Key Responsibilities

Serve as the primary interface and analytics partner between Data Engineering / DWH teams and business stakeholders
Translate business needs into analytics requirements, specifications, roadmaps, and prioritized backlogs
Collaborate with Data Engineers on DWH requirements, data models, and pipelines
Plan, coordinate, and track analytics initiatives and projects to ensure timely delivery and alignment with business objectives
Support stakeholders in understanding, interpreting, and using ingested and production data
Define and own analytics standards, metrics, and best practices across the company
Design, execute, and analyze experiments to optimize core business processes
Define dashboard requirements and deliver impactful dashboards and insights
Work with Systems, Product, and R&D teams to map data sources, address data gaps, and improve data quality

We are looking for a hands-on Data Engineer to join engineering team and take ownership of core data processes within one of our product teams.

You will design and maintain reliable ETL pipelines, connect to external data sources, and help build scalable data foundations for product features, analytics, and AI-driven capabilities. This is a great opportunity to own meaningful data processes end-to-end and work closely with product, engineering, and data stakeholders.


Your Ownership Will Include

Design, build, and maintain end-to-end ETL pipelines for production use.
Work with large-scale cloud usage data from different sources and formats.
Build data flows using Apache Spark and Databricks or similar technologies.
Structure data using Data Lake / Lakehouse concepts, including Bronze, Silver, and Gold layers.
Integrate with external APIs and data sources.
Prepare and model data for product features, analytics, and AI-related capabilities.
Ensure data quality, reliability, and observability across pipelines.
Collaborate closely with backend engineers, data analysts, and product stakeholders.