Senior Director – Data Platform, Cloud Services

Jobtailor; Warszawa; On-site; PLN 350,000 - 520,000; Full time

Job summary

Jobtailor seeks a senior Data Platform Architect to scale a cloud-native data platform handling billions of events daily. You will work with the CTO to align architecture with business goals, driving vector databases and ML analytics adoption.

Lead strategic roadmaps, multi-region fault-tolerant designs, and a growing team of data engineers and ML engineers, translating complex tech into tangible business impact.

Qualifications

• 12+ years in data platform/infrastructure roles, with 5+ years in senior leadership.
• Proven track record of leading large-scale platform transformations.
• Experience building production embedding systems and vector databases.
• History of building and scaling teams of 20+ engineers.
• Deep expertise in data mesh, lakehouse, streaming-first architectures.

Responsibilities

• Define and execute a transformative vision for a cloud-native data platform.
• Partner with the CTO and engineering leadership to align strategy with business goals.
• Drive adoption of vector databases and ML-powered analytics.
• Build strategic roadmaps balancing innovation with operational excellence.
• Lead evolution to modern platforms with embedded ML/AI capabilities.
• Deliver fault-tolerant, multi-region architectures for real-time and batch processing.

Skills

Data Platform Architecture

Vector Databases

ML Platforms

Stream Processing

Team Leadership

Education

Advanced Degree in Computer Science

Advanced Degree in Machine Learning

Tools

Kubernetes

EKS

GKE

Airflow

MLflow

Kubeflow

SageMaker

CloudFormation

Job description

• Define and execute a transformative vision for Samba’s data platform architecture scaling to billions of daily events
• Partner with the CTO and engineering leadership to align platform strategy with business objectives
• Drive adoption of vector databases and ML-powered analytics
• Build strategic roadmaps balancing innovation with operational excellence
• Lead evolution to a modern, cloud-native data platform with embedded ML/AI capabilities
• Deliver fault-tolerant, multi-region architectures supporting real-time and batch processing
• Build and maintain services, platforms, and frameworks for data engineering teams
• Architect embedding-based systems for content understanding, viewer similarity, and semantic search
• Deliver infrastructure for vector storage, indexing, and retrieval at billions-of-embeddings scale
• Champion data governance, security, and compliance, including GDPR and CCPA
• Evaluate and implement streaming architectures, lakehouse patterns, and ML platforms
• Design platforms for embedding generation, storage, and serving
• Implement vector search for real-time recommendations and content discovery
• Build infrastructure for multimodal embeddings across video, audio, and text metadata
• Enable self-service ML capabilities for data scientists and analysts
• Establish MLOps practices for embedding model lifecycle management
• Build and mentor a team of platform engineers, ML engineers, and architects
• Foster innovation, experimentation, and continuous learning
• Establish career paths and growth opportunities
• Drive collaboration with data science, product, and engineering teams
• Establish SLAs and monitoring frameworks for internal and external clients
• Provide observability and data-quality enforcement tools for Data Engineering and Data Science
• Lead vendor relationships and technology partnerships
• Drive automation and self-service capabilities for internal customers

Requirements

• 12+ years in data platform/infrastructure roles, with 5+ years in senior leadership
• Proven track record of leading large-scale platform transformations
• Experience building production embedding systems and vector databases
• History of building and scaling teams of 20+ engineers
• Deep expertise in modern data architectures (data mesh, lakehouse, streaming-first)
• Proficiency with stream processing (Kafka, Flink, Spark Streaming)
• Proficiency with modern data warehouses/lakes (Snowflake, Databricks, BigQuery)
• Proficiency with workflow management (Airflow, etc.)
• Proficiency with container orchestration (Kubernetes, EKS/GKE)
• Proficiency with Infrastructure as Code (Terraform, CloudFormation)
• Proficiency with ML platforms (MLflow, Kubeflow, SageMaker)
• Exceptional communication skills to articulate complex technical concepts to diverse audiences
• Strategic thinking with ability to balance long-term vision with short-term deliverables
• Strong business acumen to connect technical decisions with business outcomes
• Track record of influencing without authority across organizational boundaries
• Knowledge of privacy-preserving analytics and clean room technologies
• Contributions to open-source projects in ML infrastructure or vector search
• Advanced degree in Computer Science, Machine Learning, or related field

Core Competencies

Demonstrates expertise in architecting and scaling modern data platforms with embedded ML/AI capabilities, while ensuring data governance and compliance. Proven ability to lead large teams and drive strategic initiatives that align technical solutions with business objectives.

Highest-signal resume keywords

• Data Platform Architecture
• Vector Databases
• ML Platforms
• Stream Processing
• Team Leadership

ATS Optimization Keywords

Hard Skills

• Data Mesh
• Lakehouse
• Streaming-First Architectures
• Embedding Systems
• Kafka
• Flink
• Spark Streaming
• Snowflake
• Databricks
• Terraform

Soft Skills

• Exceptional Communication
• Strategic Thinking
• Business Acumen
• Influencing Without Authority
• Fostering Innovation

Certifications & Qualifications

• Advanced Degree in Computer Science
• Advanced Degree in Machine Learning

Industry Keywords

• Data Governance
• GDPR
• CCPA
• Privacy-Preserving Analytics
• Clean Room Technologies

Tools & Technologies

• Kubernetes
• EKS
• GKE
• Airflow
• MLflow
• Kubeflow
• SageMaker
• CloudFormation