As a Senior ML Engineer you will join our Static AI team which develops state-of-the-art ML models that operate on millions of machines worldwide, making sub-second decisions to stop malware before it runs. We bring together cross-functional skill sets, including data science, ML engineering, and software engineering, to research, develop, ship, and support ML malware detection engines across Windows, Mac, and Linux machines and cloud environments.

What Will You Do?

Primary responsibilities include: 

• Data pipeline architecture: Design, build, and maintain scalable data pipelines to handle millions of data points from internal and external sources
• ML infrastructure: Develop and optimize the infrastructure required for training, evaluating, and deploying ML models at scale
• Cross-functional Collaboration: Work closely with Data Scientists and Software Engineers to translate research into production-ready detection engines
• System optimization: Build and improve analytics systems that learn from a wide variety of data sources to enhance our existing ML models
• Production support: Ensure the reliability and performance of ML malware detection engines across Windows, Mac, Linux, and cloud environments
• "Production experience" - good level of coding, tests, dealing with CI
• You will also be encouraged to write white papers, blogs, and articles or present in meetups / conferences (but only if you wish to)

What Skills and Knowledge Will You Bring?

Ideal candidates will have: 

• Degree in Computer Science or Mathematics, or equivalent experience
• Experience with collecting and building large datasets for training machine learning models
• Producing, deploying and running ML in production environments
• Experience working with Big data technologies, such as Spark/Databricks, Hadoop, and others 
• Ability to work collaboratively to translate business requirements into technical solutions
• Willingness and ability to work in a diverse, globally distributed team
• The ability to work on difficult problems independently
• Strong communication skills. Our team relies on strong communication, since we have a diverse and sometimes exclusive set of skills, yet our end product relies on all team members. Thus, we need our team members to be able to communicate with people outside our team (with a wide range of backgrounds/positions, product/support/engineering, …)
• A fiery determination and a strong team-player mindset - the team's defining trait is an 'all hands on deck' attitude

Experience in some of these areas is an advantage

• Experience in the cyber domain - security products, especially detection systems
• Cloud infrastructure (AWS) / MLOps experience
• Experience working with Infrastructure as code (IaC)
• AI tooling experience - We are an AI-oriented engineering team. We believe in automating the mundane so our developers can focus on high-level architecture and complex problem-solving. We provide the latest enterprise AI tools and encourage a culture of 'working smarter, not harder.

Why SentinelOne?

AI is redefining how the world operates and rewriting the rules of security in real time, and SentinelOne was built for this moment. From day one, we architected an AI-native platform designed to operate at machine speed, not as an add-on to legacy systems but as the foundation itself. If you want to build where innovation and impact move together, this is that place.

We invest in our Sentinels with comprehensive, competitive benefits designed to support you and your family:

• Enjoy flexible hybrid work in Prague (Karlin), Prague-based employees are required to work from the office at least two days per week.
• Stock & Bonuses: Grant of Restricted Stock Units with a 4-year vesting plan, annual performance-based bonuses, and an employee stock purchase plan.
• Time Off & Well-being: Flexible Time Off, on top of the standard 5 weeks vacation, flexible paid sick days, fully paid Short Term Sick/Nursing Leave, 16-week parental leave, grandparent leave, and additional company holidays.
• Insurance & Health: Pension Insurance Contribution, Premium life insurance, Private medical care (for you and +1), and a Global Employee Assistance Program.
• Work Perks: Monthly meal and well-being allowance, high-end MacBook/Windows laptop, work-from-home support, and in-office refreshments.
• Growth & Community: LinkedIn Learning, internal mentoring, educational support, generous referral bonuses, and optional company events (sports, BBQs, charity).

As a Senior Data Engineer, you will play a vital role in designing, building, and maintaining the data infrastructure that powers our cyber threat detection research. This infrastructure will enable data scientists and security researchers to make sense of petabytes of data and uncover the threats that matter. You will collaborate closely with cross-functional teams across the company — data scientists, security researchers, product managers, and engineers — to deliver innovative data solutions that help us build best-in-class threat detection and protect our customers.

What will you do?

Primary responsibilities include:

• Design, build, and maintain scalable data pipelines that process petabytes of security data.
• Develop production-grade pipelines, applying software engineering best practices.
• Operate big data infrastructure and cloud data warehouses with a focus on reliability and performance.
• Partner with data scientists and security researchers to deliver impactful data solutions.
• Ensure data quality, observability, and governance across the platform.

Ideal candidates will have:

• 4+ years of experience in data engineering, data architecture, and distributed systems
• Proficiency in programming languages such as Python (that we use), Java, Scala, or similar.
• Experience with cloud-based technologies such as AWS (our primary), GCP or Azure.
• Experience with deploying big data technologies such as Apache Spark, Hadoop, Hive, IceBerg, Trino.
• Familiarity with data warehousing concepts and technologies.
• Experience with data visualization tools such as Tableau, PowerBI, Grafana or similar.
• Strong problem-solving skills, with the ability to develop innovative solutions to complex problems.
• Excellent communication skills, with the ability to clearly present and explain complex data and models to technical and non-technical stakeholders.
• BS or higher degree in Computer Science, Statistics, Mathematics, or related field. Additional or directly relevant experience will be considered in lieu of a degree.
• Experience in leading cross-functional projects between R&D and product teams.

Why SentinelOne? 

AI is redefining how the world operates and rewriting the rules of security in real time, and SentinelOne was built for this moment. From day one, we architected an AI-native platform designed to operate at machine speed, not as an add-on to legacy systems but as the foundation itself. If you want to build where innovation and impact move together, this is that place.

We invest in our Sentinels with comprehensive, competitive benefits designed to support you and your family:

• Enjoy flexible hybrid work in Prague (Karlin), Brno (Clubco), or remotely across CZ/SK. Only Prague-based employees are required to work from the office at least two days per week.
• Stock & Bonuses: Grant of Restricted Stock Units with a 4-year vesting plan, annual performance-based bonuses, and an employee stock purchase plan.
• Time Off & Well-being: Flexible Time Off, on top of the standard 5 weeks vacation, flexible paid sick days, fully paid Short Term Sick/Nursing Leave, 16-week parental leave, grandparent leave, and additional company holidays.
• Insurance & Health: Pension Insurance Contribution, Premium life insurance, Private medical care (for you and +1), and a Global Employee Assistance Program.
• Work Perks: Monthly meal and well-being allowance, high-end MacBook/Windows laptop, work-from-home support, and in-office refreshments.
• Growth & Community: LinkedIn Learning, internal mentoring, educational support, generous referral bonuses, and optional company events (sports, BBQs, charity).

Be part of an inclusive, innovative workplace that values belonging, flexibility, and growth!

Become a Senior SRE for Bloomreach!

Join the newly form Datacraft team — the team building the next-generation data platform for Bloomreach Engagement. Datacraft owns three interconnected domains:

• Data Warehouses (~60%) — making Bloomreach data first-class in customer DWHs (Snowflake, BigQuery, Databricks). The strategic goal for 2026–27 is to use DWHs to exponentially accelerate data adoption.
• Loomi Analytics Agent (~20%) — evolving Loomi Analytics into an agentic analytics assistant that can explore data across systems, explain insights, and act on them.
• Dashboards & Analytics Stack (~20%) — moving Engagement reporting onto DWH-backed, modern analytics stacks (semantic layers, headless BI tools).

As a Senior SRE, you will be the reliability backbone of this AI-first data team. Your work will directly impact the deployments, pipelines, reliability, and observability of pipelines and services that hundreds of enterprise customers depend on — from data exports into Databricks and BigQuery, to the  AI agent Loomi uses to surface insights.

Datacraft is an AI-first team. We believe code is a commodity and expect every engineer to fluently use coding agents (e.g., Cursor, Claude Code, Copilot, Gemini CLI) as a core part of their daily workflow. The ability to leverage AI tooling to accelerate development, prototyping, and problem-solving is not optional — it's foundational. 

For candidates at the P3 / Senior SRE level, starting monthly compensation begins at 3 800 € gross, with the final offer tailored for each candidate based on their skills and experience. Stock options and a comprehensive benefits package are also included. Working in one of our Central European offices (Bratislava, Praha, Brno) or from home on a full-time basis, you'll become a core part of the Engineering team.

What challenge awaits you?

As a P3 (Senior) SRE at Bloomreach, you are an independent professional — expert in reliability engineering, able to decompose objectives into actionable infrastructure improvements, and lead initiatives end-to-end with minimal day-to-day guidance.

We need you to build and operate an ecosystem where data engineers can safely and efficiently develop, debug, and operate data-intensive jobs and services — spanning Kafka ingest pipelines, Iceberg data lakes, multi-DWH exports, Databricks deployment and orchestration (Airflow / Cloud Composer), and agentic AI workloads.

Your responsibilities

a. Platform reliability & observability

• Build and maintain the reliability ecosystem where engineers can safely develop, debug, and operate DataCraft services running on GCP and Kubernetes (DataProc, Cloud Composer, BigQuery, Snowflake/Databricks connectors).
• Ensure end-to-end observability across the full data platform — from Kafka ingest through GCS/Iceberg staging, Airflow orchestration, to Databricks and BigQuery destinations — enabling the team to catch missing loads, SLA breaches, and data drifts before customers notice, or costs drift.
• Drive scalability so services can scale vertically and horizontally based on operational and telemetric data (OpenTelemetry, Prometheus, Victoria Metrics).
• Maintain team health dashboards and alerting (Grafana, PagerDuty, Sentry).

b. Infrastructure as Code & deployments

• Own and evolve Terraform-based infrastructure for DataCraft services.
• Automate deployments, instance setup, and operational runbooks to eliminate manual/semi-manual steps.
• Maintain CI/CD pipelines (GitLab) with linters, security scans, and code quality checks, AI code reviews, enabling engineers to produce high-quality MRs.

c. Security & compliance

• Help the team fulfill security requirements for ISO and SOC2 audits by enforcing security principles: key distribution, key rotation, authorization & authentication at the service level, data encryption in transit, data isolation, resource limitations, and audit logs.
• Ensure data access controls are properly enforced across multi-DWH environments (BigQuery, Snowflake, Databricks).

d. Incident management & L3 support

• Participate in and drive L3 on-call rotation and incident resolution for DataCraft services.
• Contribute tooling for debugging, troubleshooting, and performance testing of data pipelines and orchestration layers.
• Use telemetry data and distributed tracing to navigate complex, distributed service architectures.

e. Agentic platform reliability

• Ensure reliability and observability of the Loomi Analytics Agent data infrastructure — LLM API gateway performance, MCP server health, and evaluation pipeline availability.
• Monitor and alert on data quality issues that could introduce inconsistencies or hallucinations in Loomi's responses — making the agent's data access patterns reliable and debuggable.

Our tech stack

Languages: Python (primary), Go, SQL Messaging & streaming: Apache Kafka Storage & databases: Databricks, BigQuery, Apache Iceberg, GCS, Mongo, Redis Data processing & orchestration: Apache Spark, DataFlow, Airflow / Cloud Composer Infrastructure: GCP, Kubernetes, Terraform AI / Agentic: LLM APIs, MCP, agent orchestration frameworks Observability: Grafana, Prometheus, Victoria Metrics, PagerDuty, Sentry, OpenTelemetry CI/CD & tooling: GitLab, Jira, Confluence AI coding agents: Cursor, Claude Code

Your qualifications

Professional experience

Impact

• You can articulate how your contributions transformed the way engineers work and fostered a strong SRE/DevOps culture.
• You can demonstrate how impactful reliability work connects to business success and customer outcomes.

Ownership

• You embrace the you build it, you run it principle — you love owning what you ship.
• You are cost-aware: effective vertical and horizontal autoscaling and detailed telemetry insights are how you demonstrate mindfulness of cloud spend.

Systematic approach

• Infrastructure as Code is the only thing that brings stability into chaos
• You design for failure: SLOs, error budgets, and runbooks are first-class artifacts, not afterthoughts.

Data-driven

• You use telemetry and metrics to give engineers actionable feedback on how applications and services behave.
• You can navigate complex data platform architectures using distributed tracing and debugging.

Technical skills

• Solid hands-on experience with GCP (BigQuery, DataProc, Cloud Composer, GCS) and Kubernetes.
• Experience with Python; Go is a strong advantage.
• Familiarity with data pipeline technologies (Kafka, Airflow/Cloud Composer, Spark, Iceberg) — you don't need to write ETL code, but you need to operate it reliably and know when something is wrong.
• Fluent use of AI coding agents (Cursor, Claude Code, Copilot, Gemini CLI, or similar) — you already use these tools daily to accelerate work.
• Comfortable with on-call rotation and 24/7 incident response.
• Remote-first mindset — you know how to be effective in distributed teams.
• You are able to learn and adapt — essential when exploring new tech or navigating our growing codebase.

Strongly preferred

• Experience operating single-DWH environments (Snowflak, Databricks or BigQuery).
• Familiarity with agentic/LLM workloads — API reliability, latency SLOs, trace observability for AI systems.
• Experience with open table formats (Iceberg, Delta Lake) in production environments.
• Exposure to data security and compliance in the context of customer-facing DWH integrations (consent, data retention, PII handling).

Personal qualities

• Ownership & accountability — you take issues from detection through to resolution and follow-up prevention.
• Systematic thinking — you identify root causes, not symptoms, and document your findings so the team learns.
• Collaboration & communication — you explain trade-offs and constraints clearly to both engineers and non-engineers.
• Bias for reliability — operational excellence (SLOs, oncall friendliness, proactive alerting) is not a chore, it's your craft.
• Continuous improvement mindset — you are comfortable iterating, revisiting assumptions, and improving incrementally.
• Comfortable operating remote-first in a distributed team across Central Europe.

Your success story

In 30 days:

• Get to know the DataCraft team, the company, and the most important processes.
• Set up your local and GCP development environment and complete the Engagement engineering onboarding.
• Understand the current state of DataCraft services: pipelines, orchestration, observability gaps, and on-call runbooks.

In 90 days:

• Start contributing to the L3 on-call rotation, handling incidents, troubleshooting, and debugging — which will sharpen your understanding of the platform and surface fresh improvement ideas.
• Deliver your first meaningful reliability improvement: an observability enhancement, a deployment automation, or an SLO definition for a key DataCraft service.

In 180 days:

• Own the reliability posture of at least one DataCraft domain end-to-end — able to independently design, operate, and continuously improve it.
• Drive measurable improvements in MTTR, alert signal-to-noise ratio, or deployment confidence across the team.
• Be a trusted reliability partner in architecture discussions — your input shapes how new DataCraft services are designed for operability from day one.

#LI-KP1

Become a Senior SRE for Bloomreach!

Join the newly form Datacraft team — the team building the next-generation data platform for Bloomreach Engagement. Datacraft owns three interconnected domains:

• Data Warehouses (~60%) — making Bloomreach data first-class in customer DWHs (Snowflake, BigQuery, Databricks). The strategic goal for 2026–27 is to use DWHs to exponentially accelerate data adoption.
• Loomi Analytics Agent (~20%) — evolving Loomi Analytics into an agentic analytics assistant that can explore data across systems, explain insights, and act on them.
• Dashboards & Analytics Stack (~20%) — moving Engagement reporting onto DWH-backed, modern analytics stacks (semantic layers, headless BI tools).

As a Senior SRE, you will be the reliability backbone of this AI-first data team. Your work will directly impact the deployments, pipelines, reliability, and observability of pipelines and services that hundreds of enterprise customers depend on — from data exports into Databricks and BigQuery, to the  AI agent Loomi uses to surface insights.

Datacraft is an AI-first team. We believe code is a commodity and expect every engineer to fluently use coding agents (e.g., Cursor, Claude Code, Copilot, Gemini CLI) as a core part of their daily workflow. The ability to leverage AI tooling to accelerate development, prototyping, and problem-solving is not optional — it's foundational. Working in one of our Central European offices (Bratislava, Praha, Brno) or from home on a full-time basis, you'll become a core part of the Engineering team.

What challenge awaits you?

As a P3 (Senior) SRE at Bloomreach, you are an independent professional — expert in reliability engineering, able to decompose objectives into actionable infrastructure improvements, and lead initiatives end-to-end with minimal day-to-day guidance.

We need you to build and operate an ecosystem where data engineers can safely and efficiently develop, debug, and operate data-intensive jobs and services — spanning Kafka ingest pipelines, Iceberg data lakes, multi-DWH exports, Databricks deployment and orchestration (Airflow / Cloud Composer), and agentic AI workloads.

Your responsibilities

a. Platform reliability & observability

• Build and maintain the reliability ecosystem where engineers can safely develop, debug, and operate DataCraft services running on GCP and Kubernetes (DataProc, Cloud Composer, BigQuery, Snowflake/Databricks connectors).
• Ensure end-to-end observability across the full data platform — from Kafka ingest through GCS/Iceberg staging, Airflow orchestration, to Databricks and BigQuery destinations — enabling the team to catch missing loads, SLA breaches, and data drifts before customers notice, or costs drift.
• Drive scalability so services can scale vertically and horizontally based on operational and telemetric data (OpenTelemetry, Prometheus, Victoria Metrics).
• Maintain team health dashboards and alerting (Grafana, PagerDuty, Sentry).

b. Infrastructure as Code & deployments

• Own and evolve Terraform-based infrastructure for DataCraft services.
• Automate deployments, instance setup, and operational runbooks to eliminate manual/semi-manual steps.
• Maintain CI/CD pipelines (GitLab) with linters, security scans, and code quality checks, AI code reviews, enabling engineers to produce high-quality MRs.

c. Security & compliance

• Help the team fulfill security requirements for ISO and SOC2 audits by enforcing security principles: key distribution, key rotation, authorization & authentication at the service level, data encryption in transit, data isolation, resource limitations, and audit logs.
• Ensure data access controls are properly enforced across multi-DWH environments (BigQuery, Snowflake, Databricks).

d. Incident management & L3 support

• Participate in and drive L3 on-call rotation and incident resolution for DataCraft services.
• Contribute tooling for debugging, troubleshooting, and performance testing of data pipelines and orchestration layers.
• Use telemetry data and distributed tracing to navigate complex, distributed service architectures.

e. Agentic platform reliability

• Ensure reliability and observability of the Loomi Analytics Agent data infrastructure — LLM API gateway performance, MCP server health, and evaluation pipeline availability.
• Monitor and alert on data quality issues that could introduce inconsistencies or hallucinations in Loomi's responses — making the agent's data access patterns reliable and debuggable.

Our tech stack

Languages: Python (primary), Go, SQL Messaging & streaming: Apache Kafka Storage & databases: Databricks, BigQuery, Apache Iceberg, GCS, Mongo, Redis Data processing & orchestration: Apache Spark, DataFlow, Airflow / Cloud Composer Infrastructure: GCP, Kubernetes, Terraform AI / Agentic: LLM APIs, MCP, agent orchestration frameworks Observability: Grafana, Prometheus, Victoria Metrics, PagerDuty, Sentry, OpenTelemetry CI/CD & tooling: GitLab, Jira, Confluence AI coding agents: Cursor, Claude Code

Your qualifications

Professional experience

Impact

• You can articulate how your contributions transformed the way engineers work and fostered a strong SRE/DevOps culture.
• You can demonstrate how impactful reliability work connects to business success and customer outcomes.

Ownership

• You embrace the you build it, you run it principle — you love owning what you ship.
• You are cost-aware: effective vertical and horizontal autoscaling and detailed telemetry insights are how you demonstrate mindfulness of cloud spend.

Systematic approach

• Infrastructure as Code is the only thing that brings stability into chaos
• You design for failure: SLOs, error budgets, and runbooks are first-class artifacts, not afterthoughts.

Data-driven

• You use telemetry and metrics to give engineers actionable feedback on how applications and services behave.
• You can navigate complex data platform architectures using distributed tracing and debugging.

Technical skills

• Solid hands-on experience with GCP (BigQuery, DataProc, Cloud Composer, GCS) and Kubernetes.
• Experience with Python; Go is a strong advantage.
• Familiarity with data pipeline technologies (Kafka, Airflow/Cloud Composer, Spark, Iceberg) — you don't need to write ETL code, but you need to operate it reliably and know when something is wrong.
• Fluent use of AI coding agents (Cursor, Claude Code, Copilot, Gemini CLI, or similar) — you already use these tools daily to accelerate work.
• Comfortable with on-call rotation and 24/7 incident response.
• Remote-first mindset — you know how to be effective in distributed teams.
• You are able to learn and adapt — essential when exploring new tech or navigating our growing codebase.

Strongly preferred

• Experience operating single-DWH environments (Snowflak, Databricks or BigQuery).
• Familiarity with agentic/LLM workloads — API reliability, latency SLOs, trace observability for AI systems.
• Experience with open table formats (Iceberg, Delta Lake) in production environments.
• Exposure to data security and compliance in the context of customer-facing DWH integrations (consent, data retention, PII handling).

Personal qualities

• Ownership & accountability — you take issues from detection through to resolution and follow-up prevention.
• Systematic thinking — you identify root causes, not symptoms, and document your findings so the team learns.
• Collaboration & communication — you explain trade-offs and constraints clearly to both engineers and non-engineers.
• Bias for reliability — operational excellence (SLOs, oncall friendliness, proactive alerting) is not a chore, it's your craft.
• Continuous improvement mindset — you are comfortable iterating, revisiting assumptions, and improving incrementally.
• Comfortable operating remote-first in a distributed team across Central Europe.

Your success story

In 30 days:

• Get to know the DataCraft team, the company, and the most important processes.
• Set up your local and GCP development environment and complete the Engagement engineering onboarding.
• Understand the current state of DataCraft services: pipelines, orchestration, observability gaps, and on-call runbooks.

In 90 days:

• Start contributing to the L3 on-call rotation, handling incidents, troubleshooting, and debugging — which will sharpen your understanding of the platform and surface fresh improvement ideas.
• Deliver your first meaningful reliability improvement: an observability enhancement, a deployment automation, or an SLO definition for a key DataCraft service.

In 180 days:

• Own the reliability posture of at least one DataCraft domain end-to-end — able to independently design, operate, and continuously improve it.
• Drive measurable improvements in MTTR, alert signal-to-noise ratio, or deployment confidence across the team.
• Be a trusted reliability partner in architecture discussions — your input shapes how new DataCraft services are designed for operability from day one.

#LI-KP1

The role

We’re looking for a Software Engineer with strong C++ expertise to join the team building and operating Nebius Data Platform — a distributed storage and a processing platform that acts as the company’s “source of truth” and the backbone of many internal (and some external) products.

Nebius Data Platform is a single multi-tenant ecosystem based on YTsaurus — instead of running separate HDFS/Kafka/HBase-style systems, we provide storage, compute, and analytics capabilities inside one platform.

Built on top of the open-source YTsaurus ecosystem, we run and extend our own Nebius distribution and develop significant in-house functionality (core and platform-level). We can design, implement, and roll out features end-to-end on our clusters without waiting for upstream approvals and contribute upstream when it makes sense.

At scale today, this includes~500 servers, ~20k CPU cores and ~10 PB of compressed data in our largest production cluster, supporting workloads ranging from business-critical pipelines and financial transactions to large-scale ML/LLM training datasets and compute.

What’s inside the platform

You’ll work on a system that includes (and ties together):

• Distributed Storage (Cypress): transactional semantics, tiered storage, erasure coding, replication, and strong reliability expectations.
• Compute & ETL: a cluster-wide job scheduler (tens of thousands of cores), MapReduce, YQL for SQL-like data processing, and SPYT (Spark over YTsaurus) for modern data engineering.
• Interactive analytics (CHYT): ClickHouse® instances spun up directly on compute nodes for fast SQL over data in-place.
• Dynamic Tables: low-latency NoSQL KV with distributed ACID transactions for OLTP-style workloads and feature stores.
• Orchestracto: workflow orchestration deeply integrated with the platform (Airflow-like, but platform-native).

What you’ll do

We’re looking for engineers who combine strong systems skills with product sense: understanding who uses the platform, why certain capabilities matter, and making pragmatic trade-offs to maximize impact. On our team, engineering work is expected to be connected to real users and outcomes — you’ll regularly align with internal stakeholders, clarify requirements, and help drive prioritization.

In this role, you will:

• Design and implement new functionality in YTsaurus core (C++) with production reliability in mind.
• Build and evolve platform-level capabilities: platform architecture and operating model—multi-cluster growth, shared primitives, and a consistent experience that scales with new teams and use cases.
• Improve end-to-end platform experience for internal (and external-facing) users: APIs, guardrails, debugging workflows, and automation.
• Own production quality: incident response / on-call rotation, root cause analysis, and turning learnings into durable fixes.

Example projects

• Roll out sharded YTsaurus masters (incl. Kubernetes operator support) and build automatic balancing of metadata across master cells (consensus groups) to remove control-plane bottlenecks and unlock 10–100x cluster growth.
• Make CHYT interactive SQL faster and more predictable at high load via performance work like data-skipping / min-max-style indexes and improved execution introspection.
• Turn Orchestracto into a platform product by defining the building blocks, developer experience, and governance for how teams create and share workflows.
• Scale and harden Parquet-on-S3 for native YTsaurus workloads by tackling replication/movement, consistent lifecycle semantics, and master-server metadata optimizations for performance and reliability.
• Design and ship complete, trustworthy audit trails for data changes (who/what/when) across heterogeneous storage and compute paths.

Tech stack

• Core: modern C++ (C++20, async + multithreaded primitives)
• Services & tooling: Go and Python (microservices, utilities, integration tests)

What we expect

• 5+ years of software engineering experience.
• Strong C++ skills (you’ll write core code).
• Working knowledge of Python and/or Go (you don’t have to be expert, but should be comfortable navigating them).
• Experience developing and/or operating high-load, distributed services.
• Production mindset: ability to use SSH, read logs/metrics/traces, and debug distributed systems behavior.
• Solid CS fundamentals: algorithms, data structures, concurrency basics.

Nice to have

• Experience with Big Data systems (YTsaurus/Hadoop/Spark/ClickHouse/Kafka-like ecosystems).
• Experience with multi-tenant platforms, schedulers, resource isolation, quotas, and reliability engineering.
• Strong performance engineering skills (profiling, lock contention, latency/throughput tradeoffs).

We conduct coding interviews as part of the process.

The role 

The Data Engineering team is responsible for building and maintaining robust data infrastructure that powers analytics, and business intelligence across Nebius. We design and implement scalable data pipelines, optimize data storage and processing, and enable data-driven decision making across the organization. The team works closely with product teams and business stakeholders to ensure alignment with company goals.We are looking for a Data Engineer to design, build, and maintain our data infrastructure and pipelines. You will work on processing large-scale datasets, optimizing data workflows, and enabling analytics capabilities that support our rapidly growing cloud platform.

Your responsibilities: 

• Design, develop, and maintain scalable data pipelines.
• Build and optimize data infrastructure.
• Implement data quality monitoring and validation frameworks.
• Optimize data storage, processing, and query performance for large-scale datasets.
• Design and implement data models for analytics and reporting use cases.
• Develop tools and automation to improve data engineering workflows and productivity.
• Ensure data governance, security, and compliance standards are met.
• Participate in on-call rotation to support production data systems.

Must-haves: 

• 3+ years of experience in data engineering or related roles.
• Experience building and maintaining data pipelines using orchestration tools (e.g., Airflow, Prefect, Dagster).
• Strong proficiency in SQL and solid programming skills in Python.
• Experience with distributed data processing frameworks (e.g., Apache Spark, or similar).
• Knowledge of data modeling principles and best practices.
• Understanding of data architectures and storage systems.

Nice-to-haves: 

• Experience with real-time data streaming platforms.
• Familiarity with Infrastructure as Code tools (Terraform, etc).
• Experience with containerization (Docker) and Kubernetes.
• Knowledge of data governance and privacy frameworks (GDPR, SOC2).
• Knowledge of data quality and observability tools (Great Expectations, etc.).

We conduct coding interviews as part of the process.

Role: Transcreation Executive

Location: Prague or any other city, Czech Republic (100% Remote)

Please submit your CV in English

About the role and team:

In today's fiercely competitive marketplace, achieving creative excellence across all eCommerce touchpoints is crucial. We are seeking a Transcreation Executive renowned for their outstanding work in the Beauty & Skincare sector to join our dynamic team. This is an exciting opportunity to elevate our brand's presence and impact across Europe. 

Our ideal candidate will excel in high-volume adaptation, ensuring compliance, consistency, and competitiveness. As a Transcreation Executive, you will manage multiple projects simultaneously, ensuring the brand consistency & quality from the initial concept through to execution and delivery. Experience in the beauty and e-commerce sectors is essential, along with proficiency in utilizing the necessary tools and software to manage complex projects efficiently.  

This role offers the chance to work with iconic beauty brands as we launch a groundbreaking Europe-wide eCommerce Content Factory. By integrating automation and AI, we aim to revolutionise content creation and set new digital standards for online beauty experiences. 

As a Transcreation Executive, you will be planning and organising translation and transcreation campaigns, liaising with the client brand managers and in-market-creatives (copywriters, transcreators, translators, and post-editors), tracking project progress (admin & financials), and using your expertise in cosmetics, beauty, and luxury to deliver transcreation work for our premium client, a global leader in beauty. 

What you will be doing: 

• Immersed in the brand and work closely with different stakeholders such as project managers, designers, and freelance linguists. 
• Coordinating the transcreation of e-commerce marketing assets across channels, ensuring brand consistency and adherence to retailers’ guidelines and specifications. 
• Responsible for the planning and execution of transcreation and machine translation/AI transcreation projects, from initial brief to final language QC of in-situ asset. 
• Required to plan projects at hand in a proactive manner, monitor progress, and solve problems that might arise. 
• Fast thinker and will be able to apply problem-solving techniques. 
• Discuss with the client the scope of work and, in agreement with the Transcreation Lead, manage and exceed client’s expectations. 
• Proactively identify areas for improvement and any areas where you can add value to anything outside of direct responsibilities related to projects. 
• Deliver the best possible international communication
• Conduct quality checks on transcreations at various project stages, collaborate with stakeholders and clients, build strong relationships with in-market creatives, and work with diverse talents globally.
• Work across all marketing channels and gain insights in other account teams such as production, digital, or on-site client teams.  
• Execute admin tasks such as raising purchase- and sales orders, centralising tone of voice and brand identity materials, building glossaries and maintaining and managing translation memories. 

What you need to be great in this role: 

• 1-3 years experience in localisation project management. 
• University degree in marketing, languages, business, or related field. 
• Expertise in and passion for beauty, cosmetics, or luxury industries. 
• English proficiency is required for our global operations. Being a native speaker of Czech, Hungarian, Slovak, Bulgarian, or Greek is desirable.
• Experience with CAT tools and Machine Translation. 

Req ID: 16477
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