Data Engineering Team Lead

About Port

At Port.io, we are building an open and flexible Agentic Engineering Platform for modern engineering organizations. Following our recent $100M Series C funding round, we are in a phase of rapid hypergrowth with strong enterprise momentum.

We act as the central nervous system for engineering, enabling platform teams to unify their stack and expose it as a governed layer through golden paths for developers and AI agents.

By combining rich engineering context, workflows, and actions, we help organizations transition from manual processes to autonomous, AI-assisted engineering workflows while maintaining control and accountability.

As a product-led company, we believe in building world-class platforms that fundamentally shape how modern engineering organizations operate.

Why we’re looking for you:

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

What you’ll do:

At Port, we’re building a platform by developers, for developers. As a Data Engineering Team Lead, you’ll 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.
  
  

• 2+ years of experience leading a team, balancing people management with hands-on technical leadership.
• 5+ years of experience in Data Engineering, designing and operating scalable data platforms and pipelines.
• Strong expertise in data warehousing, data modeling (including dimensional modeling and SCDs), and building ETL/ELT pipelines at scale.
• Hands-on experience with modern data platforms and tooling, including technologies such as Snowflake, Databricks, BigQuery, Redshift, Airflow, dbt, Fivetran, Airbyte, or similar.
• Expert-level SQL skills and experience working with large-scale datasets, including CDC-based architectures and NoSQL databases.
• Strong software engineering skills, including experience with Python and modern backend development practices.
• Experience building reliable, governed, and high-quality data systems, including data quality, governance, semantic layers, and metric definitions.
• Experience enabling analytics and business decision-making through BI and reporting tools such as Tableau, Looker, Metabase, or Qlik.
• Strong analytical thinking and the ability to translate complex data into actionable insights for technical and business stakeholders.
• Proven ability to collaborate effectively with product managers, analysts, engineers, and business stakeholders to deliver end-to-end data solutions.
• Excellent communication and documentation skills.
• Fluent Hebrew and English.
  
  

• Experience with streaming and real-time data technologies such as Kafka or Kinesis.
• Experience with cloud-native infrastructure, containerization, and orchestration technologies such as Docker and Kubernetes.
• Experience with Node.js, TypeScript, or Golang.
• Experience building data infrastructure that supports AI, machine learning, or agent-based products.