BI & Data Platform Lead

The company is building a new BI and Data platform from the ground up and is hiring a BI & Data Platform Lead to own it technically. This is a senior, hands-on role spanning data architecture, data engineering, analytics engineering and BI — from evaluating and selecting the stack, through defining the target architecture and data models, to building the pipelines, semantic layer and initial dashboards and driving the platform into production.

The role sits inside the existing BI organisation and works directly with the Head of BI, engineering, product and business stakeholders. It is a builder role, not a reporting or dashboard-maintenance role.

Responsibilities

• Platform ownership — lead the technical implementation of the new BI/Data platform from design through production and organisational adoption; own deliverables, dependencies, risks and implementation decisions.
• Architecture & technology selection — participate in evaluating and selecting the data platform and supporting technologies; define the target BI/data architecture with the Head of BI and technology stakeholders, balancing scalability, reliability, security, performance and cost.
• Pipelines & ingestion — design and implement scalable ETL/ELT pipelines and automated data processes; define ingestion patterns for batch, near-real-time and real-time needs across operational databases, APIs, event streams and third-party systems.
• Modeling & semantic layer — design and build scalable data models, datasets, semantic layers and analytics-ready structures; define a consistent organisational data language, KPI definitions and a single source of truth.
• Standards & engineering practice — establish development standards for data modeling, transformation, testing, deployment, CI/CD and documentation.
• Data quality & observability — establish data quality, reconciliation, validation, lineage, monitoring and observability processes.
• Analytics delivery — build and maintain the initial dashboards, analytical solutions and self-service capabilities on the new platform; translate business requirements into scalable technical solutions and automate manual BI processes.
• Cross-team partnership — work with Engineering and Product so new platform capabilities emit the data analytics needs from day one; support the transition from the existing BI environment, and support advanced analytics, segmentation, predictive modeling and AI/data-science use cases.

• 5+ years in Data Engineering, BI Engineering, Analytics Engineering or Business Intelligence.
• Proven experience building — or significantly contributing to — a modern data/BI platform.
• Advanced SQL, with extensive hands-on work on large and complex datasets.
• Strong hands-on experience with ETL/ELT architectures, data pipelines and data transformation.
• Strong understanding of data warehouse architecture and dimensional / data modeling.
• Snowflake — hands-on within the last 3 years. This is the customer's primary requirement (Liran, Sep 2026). Experience with BigQuery, Redshift or Databricks is additive, not a substitute. Recency matters: screen the CV for Snowflake work in a 2023-or-later role, and confirm it in the interview.
• Experience with modern transformation and orchestration tooling: dbt and Airflow / Astronomer or equivalent.
• Experience with a BI platform: Looker, Power BI, Tableau or similar, including semantic-layer and standardised KPI framework design.
• Good Python skills for data processing, automation and integration.
• Experience integrating databases, APIs, event data and third-party sources.
• Strong grasp of data quality, governance, lineage, monitoring and analytical-engineering best practice.
• Understanding of batch vs. real-time / near-real-time data architectures.
• Ability to evaluate technologies and make architecture decisions on business requirements, scalability, maintainability and cost.
• Ability to independently own a project from architecture and design through implementation and production.
• Strong communication with both technical and business stakeholders; comfortable in a fast-changing environment where the platform, processes and standards are still being established.