Director of Data Engineering

بيتح تكفا - إسرائيل

الراتب شهرياً: لم يكشف

تاريخ النشر: 03-11-2025

عدد الوظائف الشاغرة: 1 عدد الوظائف الشاغرة

سجل للتقديم

ملخص الوظيفة

Are you ready to build the data backbone behind AI-powered sports
Pixellot the global leader in AI-based automated sports production is transforming how games are captured produced and shared. Were looking for a hands-on leader who thrives on both building and leading someone who can architect code and guide the data domain to scale. Our systems power professional-grade broadcasting for leagues clubs and communities worldwide. To accelerate our next wave of AI and product innovation were hiring a hands-on Director of Data Engineering to architect lead and scale Pixellots data platform.

In this role youll set the data strategy and get your hands dirty building it creating the foundations that enable world-class analytics machine learning and GenAI applications across video product and business domains. Youll partner closely with Data Science/ML Product and Engineering. Early on youll roll up your sleeves to assess our current data landscape define the target architecture implement core pipelines and standards and build your team from the ground up creating the structure and culture for success.

If youve turned fragmented messy data into a high-reliability high-velocity data and ML platformand youre excited to do it again in the world of sports and videothis is the place for you.

As part of your role you will:

Be a hands-on technical leader building the first core components of the data platform while shaping the long-term strategy.
Lead our data technology strategy defining the vision architecture and operating model for Pixellots data platformbatch streaming and real-timealigned with company goals.
Lead and grow a department of data engineers setting direction and ensuring delivery at scale.
Audit existing data sources and flows designing a unified event taxonomy schemas and contracts across products and services while establishing standards for naming lineage governance and documentation.
Design and implement ingestion transformation and serving layers (lake/lakehouse warehouse feature store) setting up orchestration CI/CD observability and cost governance.
Partner with Data Science/ML to deliver reliable training/validation datasets model-ready features and automated re-training workflows for video and non-video signals.
Introduce data validation testing and monitoring (schema enforcement SLAs/SLOs anomaly detection lineage) to ensure trust in downstream analytics and models.
Research and implement emerging AI/GenAI tools and technologies applying an MVP/PoC-driven approach to accelerate innovation.
Work with Video Cloud and Product teams to integrate camera/sensor and app data aligning metrics experimentation and privacy/security requirements.
Build your team from the ground up creating the structure and culture for success.
Be a great listener who thrives on understanding team and business needs fostering collaboration and clarity across domains.

You should bring with you:

Extensive experience leading end-to-end data engineering initiatives in cloud environments.
Proven track record transforming fragmented data ecosystems into scalable reliable platforms supporting analytics and ML.
Strong hands-on skills in Python SQL and distributed processing (Spark or equivalent).
Expertise with modern data stacks: orchestration (Airflow or similar) transformation (dbt or equivalent) data warehouses (BigQuery/Snowflake/Redshift) lake/lakehouse (e.g. S3/GCS table formats) and CI/CD for data.
Experience designing event schemas data contracts and metadata/lineage frameworks; implementing data quality controls and cost optimization.
Demonstrated partnership with Data Science/ML teams to deliver training datasets features and production-grade data services.
Experience with AI/GenAI tools and ecosystems with the ability to evaluate implement and operationalize them for business and product use cases.
Excellent leadership stakeholder management and communication skills in a global setting. Fluent English.

Bonus points if you have:

Background with video/sensor data computer vision pipelines or sports tech.
Experience with streaming (Kafka/Pub/Sub) feature stores and MLOps (model registries experiment tracking re-training).
Familiarity with BI tooling (Looker/Tableau) and self-serve analytics enablement.
Multi-cloud (AWS & GCP) and Kubernetes/Docker exposure.

Why Youll Love Working Here:

Shape the data foundation that powers the global leader in AI-driven sports broadcasting.
Lead groundbreaking initiatives from reimagining architecture to deploying real-world systems used by teams and leagues worldwide.
Turn complex data and video into unforgettable sports moments making every fan experience smarter and more engaging.
Work with passionate innovators in a collaborative culture that values creativity ownership and impact.

Join the Team!

Ready to transform data into a competitive edge for AI in sports Apply now and help build the platform that powers how millions of fans experience the games they love.

Required Experience:

Director

If youve turned fragmented messy data into a high-reliability high-velocity data and ML platformand youre excited to do it again in the world of sports and videothis is the place for you.

As part of your role you will:

Be a hands-on technical leader building the first core components of the data platform while shaping the long-term strategy.
Lead our data technology strategy defining the vision architecture and operating model for Pixellots data platformbatch streaming and real-timealigned with company goals.
Lead and grow a department of data engineers setting direction and ensuring delivery at scale.
Audit existing data sources and flows designing a unified event taxonomy schemas and contracts across products and services while establishing standards for naming lineage governance and documentation.
Design and implement ingestion transformation and serving layers (lake/lakehouse warehouse feature store) setting up orchestration CI/CD observability and cost governance.
Partner with Data Science/ML to deliver reliable training/validation datasets model-ready features and automated re-training workflows for video and non-video signals.
Introduce data validation testing and monitoring (schema enforcement SLAs/SLOs anomaly detection lineage) to ensure trust in downstream analytics and models.
Research and implement emerging AI/GenAI tools and technologies applying an MVP/PoC-driven approach to accelerate innovation.
Work with Video Cloud and Product teams to integrate camera/sensor and app data aligning metrics experimentation and privacy/security requirements.
Build your team from the ground up creating the structure and culture for success.
Be a great listener who thrives on understanding team and business needs fostering collaboration and clarity across domains.

You should bring with you:

Extensive experience leading end-to-end data engineering initiatives in cloud environments.
Proven track record transforming fragmented data ecosystems into scalable reliable platforms supporting analytics and ML.
Strong hands-on skills in Python SQL and distributed processing (Spark or equivalent).
Expertise with modern data stacks: orchestration (Airflow or similar) transformation (dbt or equivalent) data warehouses (BigQuery/Snowflake/Redshift) lake/lakehouse (e.g. S3/GCS table formats) and CI/CD for data.
Experience designing event schemas data contracts and metadata/lineage frameworks; implementing data quality controls and cost optimization.
Demonstrated partnership with Data Science/ML teams to deliver training datasets features and production-grade data services.
Experience with AI/GenAI tools and ecosystems with the ability to evaluate implement and operationalize them for business and product use cases.
Excellent leadership stakeholder management and communication skills in a global setting. Fluent English.

Bonus points if you have:

Background with video/sensor data computer vision pipelines or sports tech.
Experience with streaming (Kafka/Pub/Sub) feature stores and MLOps (model registries experiment tracking re-training).
Familiarity with BI tooling (Looker/Tableau) and self-serve analytics enablement.
Multi-cloud (AWS & GCP) and Kubernetes/Docker exposure.

Why Youll Love Working Here:

Shape the data foundation that powers the global leader in AI-driven sports broadcasting.
Lead groundbreaking initiatives from reimagining architecture to deploying real-world systems used by teams and leagues worldwide.
Turn complex data and video into unforgettable sports moments making every fan experience smarter and more engaging.
Work with passionate innovators in a collaborative culture that values creativity ownership and impact.

Join the Team!

Ready to transform data into a competitive edge for AI in sports Apply now and help build the platform that powers how millions of fans experience the games they love.

Required Experience:

Director

اعرض المزيد

المهارات المطلوبة

Go
Lean
Management Experience
React
Node.js
إدارة العمليات
إدارة المشاريع
البحث والتطوير
تطوير البرمجيات
Team Management
GraphQL
Leadership Experience

قدم الآن

عن الشركة

Pixellot

See Pixellot's AI sports camera in action! Automatically live-stream every game from your venue directly to fans, families and coaches. No staff needed!

عرض صفحة الشركة عرض صفحة الشركة

التقديم التلقائي على الوظائف بـ AI

قدّم على عشرات الوظائف بنقرة واحدة