Senior Director - Data Platform and Cloud Services
At a glance
Director-level Data Engineering role at Samba. Warsaw · full-time · PLN 580,000–PLN 682,000 base.
dataroles summary, based on the employer's posting.
What you'll do
- Set the platform direction with the CTO and engineering leaders, tying architecture plans to business goals
- Move the data platform toward a cloud-native design that handles real-time and batch workloads across regions
- Build infrastructure for embeddings, vector search, recommendations and content discovery at scale
- Establish MLOps, governance, security, monitoring and data-quality practices for platform teams and users
- Grow platform and ML engineering teams, while coordinating work across data science, product and engineering
What you bring
- At least twelve years in data platform or infrastructure work, including five years in senior leadership
- You have led major platform transformations and built production embedding systems and vector databases
- You have grown engineering teams of more than twenty people
- Deep knowledge of modern data architectures, plus hands-on familiarity with the listed platform and infrastructure tools
Who this fits
This director-level role suits a senior technical leader who can set architecture direction while developing teams and delivering platform changes. It is based in Warsaw, Poland, with a hybrid arrangement.
From the employer
We're seeking a Senior Director to lead and transform our data platform and cloud services architecture. This role is not about incremental improvements – we need someone who can lead and execute a leap forward in our data infrastructure capabilities, positioning Samba at the forefront of TV data analytics and AI-driven insights.
What you’ll do:
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Define and execute a transformative vision for our data platform architecture that scales to billions of daily events
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Partner with CTO and engineering leadership to align platform strategy with business objectives
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Drive adoption of next-generation technologies including vector databases and ML-powered analytics
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Build strategic roadmaps that balance innovation with operational excellence
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Lead the evolution from current state to a modern, cloud-native data platform with embedded ML/AI capabilities
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Work with the team to deliver fault-tolerant, multi-region architectures supporting real-time and batch processing
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Build and maintain the services, platforms, and frameworks enabling Samba’s data engineering teams
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Architect embedding-based systems for content understanding, viewer similarity, and semantic search
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Deliver infrastructure for vector storage, indexing, and retrieval at scale (billions of embeddings)
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Champion best practices in data governance, security, and compliance (GDPR, CCPA)
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Evaluate and implement emerging technologies (streaming architectures, lakehouse patterns, ML platforms)
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Design platforms for embedding generation, storage, and serving at scale
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Implement vector search capabilities for real-time recommendations and content discovery
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Build infrastructure supporting multimodal embeddings (video, audio, text metadata)
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Enable self-service ML capabilities for data scientists and analysts
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Establish MLOps practices for embedding model lifecycle management
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Build and mentor a world-class team of platform engineers, ML engineers, and architects
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Foster a culture of innovation, experimentation, and continuous learning
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Establish clear career paths and growth opportunities for team members
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Drive cross-functional collaboration with data science, product, and engineering teams
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Establish SLAs and monitoring frameworks for internal and external clients
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Provide observability tools for Data Engineering and Data Science, including tools to enforce data quality
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Lead vendor relationships and technology partnerships
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Drive automation and self-service capabilities for internal customers
Strategic Leadership
Technical Architecture
ML/AI Infrastructure
Team & Organizational Development
Operational Excellence
Who you are:
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12+ years in data platform/infrastructure roles, with 5+ years in senior leadership
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Proven track record of leading large-scale platform transformations
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Experience building production embedding systems and vector databases
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History of building and scaling teams of 20+ engineers
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Deep expertise in modern data architectures (data mesh, lakehouse, streaming-first)
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Proficiency with, Stream processing (Kafka, Flink, Spark Streaming), Modern data warehouses/lakes (Snowflake, Databricks, BigQuery), Workflow management (Airflow, etc), Container orchestration (Kubernetes, EKS/GKE), Infrastructure as Code (Terraform, CloudFormation), ML platforms (MLflow, Kubeflow, SageMaker)
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Exceptional communication skills to articulate complex technical concepts to diverse audiences
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Strategic thinking with ability to balance long-term vision with short-term deliverables
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Strong business acumen to connect technical decisions with business outcomes
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Track record of influencing without authority across organizational boundaries
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Knowledge of privacy-preserving analytics and clean room technologies
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Contributions to open-source projects in ML infrastructure or vector search
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Advanced degree in Computer Science, Machine Learning, or related field