דרושים » תוכנה » Data Scientist Engineer

We are seeking an experienced Data Science Team Lead to lead our data science and data engineering efforts and oversee a team of skilled data engineers. This role combines hands-on technical leadership and team management, with responsibilities that include building and scaling data infrastructure to power real-time pricing, large-scale data pipelines, and machine learning products.

You will lead the team through architecture decisions, development, and deployment of mission-critical systems-while growing and mentoring a high-performing team.

Responsibilities

Manage a team of data scientists and data engineers responsible for building robust, scalable, and high-performance data pipelines and infrastructure.
Design, build, and maintain distributed data processing workflows (batch & streaming).
Drive best practices for data quality, validation, testing, and observability.
Own and evolve data architecture in alignment with business and product goals.
Manage sprint planning, task breakdown, code reviews, and performance feedback for your team.
Contribute hands-on to key development tasks and architecture decisions.
Recruit, mentor, and grow the data science engineering team.

Required Senior Data Engineer - Big Data
Our Core Data Platform team:
We're a leading force in the ad tech industry, revolutionizing how brands connect with their audiences.
Our platform processes billions of ad impressions daily, generating massive datasets that drive our core business.
We thrive on innovation and seek a Data Engineer to help us build and scale the data infrastructure that powers our insights and analytics.
This is a unique opportunity to work with cutting-edge technologies and make a direct impact on our products.
What will you do?
As a Big Data Engineer, you'll be a key part of our data platform team, responsible for designing, building, and maintaining robust and scalable data pipelines. You'll work closely with data scientists, analysts, and server side engineers to ensure our data is reliable, accessible, and ready for analysis. Your expertise will be crucial in expanding our data warehouse and data lake capabilities, enabling us to deliver next-generation ad tech solutions.
Your mission will be to:
Develop and Optimize Data Pipelines: Design, build, and maintain ETL/ELT pipelines using Apache Spark to ingest, process, and transform large-scale datasets from various sources.
Manage Cloud Infrastructure: Architect and manage our data infrastructure primarily on Google Cloud Platform (GCP) or Amazon Web Services (AWS). This includes services like BigQuery, S3, GCS, EMR, and AirFlow.
Enhance Data Storage: Improve and manage our data warehouse and data lake solutions, ensuring data quality, consistency, and accessibility for business intelligence and machine learning applications.
Collaborate and Innovate: Partner with cross-functional teams to understand data needs and implement solutions that support new product features and business initiatives.
Ensure Data Integrity: Implement monitoring, alerting, and logging systems to maintain data pipeline health and ensure data accuracy.

Were looking for a Principal Backend & Data Engineer to own and evolve the core data-intensive backend architecture of our AI platform. This is a senior individual contributor role with broad architectural responsibility and deep hands-on impact.

You will be a technical authority in building scalable, high-performance backend and data systems that power our AI research engine - working closely with AI scientists, platform engineers, and product leaders. Beyond implementation, you will define technical direction, set engineering standards, and influence how we build and scale data-driven AI systems across the organization.

What Youll Do
Architecture & Technical Ownership

Own the architecture of core backend and data systems that support large-scale, AI-driven computation and inference.
Design and evolve high-performance analytical processing layers handling complex data workloads at scale.
Make and drive long-term architectural decisions across backend, data, and AI integration domains.
Define standards and best practices for performance, scalability, reliability, and data correctness.
Backend & Data Engineering

Design, implement, and optimize data-intensive backend services using Python.
Build and evolve analytical compute pipelines using technologies such as Polars, DuckDB, AirFlow, Iceberg, Spark and other ingestion and processing frameworks.
Collaborate closely with AI scientists to productionize algorithms and embed advanced intelligence into the platform.
Platform & Infrastructure

Architect and maintain containerized systems using Docker and Kubernetes.
Ensure systems are observable, debuggable, and operable in production environments.
Drive performance tuning and cost-efficiency across compute-heavy workloads.
Technical Leadership

Act as a technical authority and thought leader within the engineering organization.
Mentor senior engineers through design reviews, architectural guidance, and hands-on collaboration.
Serve as a force multiplier by unblocking complex technical challenges and raising the overall engineering bar.