Jobs Data Engineer

We are looking for a TechOps Engineer to take full ownership of domain infrastructure, DNS management, Cloudflare optimization, server administration, and process automation. 

If you have hands-on experience with domain registrars, a solid understanding of networking, and a drive to work on large-scale projects – we'd love to connect.

What you'll do:
 

• Register, renew, and manage domains in bulk across multiple projects.
• Work with registrars such as Namecheap, GoDaddy, GCore, and others.
• Configure DNS, Cloudflare, SSL certificates, CDN, and reverse proxying.
• Procure, set up, and maintain VPS/VDS and hosting environments.
• Track renewals, process payments, and maintain technical documentation.
• Automate repetitive tasks using scripts and APIs.
• Ensure high availability and stability of the entire technical infrastructure.
  
  Must-have:
   
• 1.5–2+ years of experience with domains and DNS management.
• Hands-on experience with multiple domain registrars.
• Strong knowledge of Cloudflare (or similar CDN services).
• Experience with DNS, SSL, proxying, and hosting control panels.
• Basic scripting skills in Python and/or JavaScript for automation.
• Experience working with REST APIs and basic Linux/VPS administration.
  
  Nice-to-have:
   
• Background in affiliate marketing, iGaming, AdTech, or SaaS.
• Familiarity with Keitaro, Binom, or other tracking platforms.
• Experience with anti-detect browsers, proxy networks, and large-scale domain portfolio management.
  
  What We Offer
   
• Competitive salary.
• Office-based position in Kyiv.
• Standard working schedule: 09:00–18:00.
• Opportunity to work on high-load infrastructure projects using modern technologies.
• Collaborative team, fast decision-making, and minimal bureaucracy.
• Professional growth in a technically challenging environment.

• We are building a next generation cross asset data fabric, which will bring together disparate data sources for the global bank. It will enable industry leading analytics, reporting and data science solutions. There are multiple streams within application covering Reporting, Data and Analytics.

   

• Responsibilities:

  This role is for a Senior Business Intelligence (BI) Developer to create reporting framework and set up the ground work for creation of Tableau reporting via Dashboards and scheduled reporting. The ideal candidate will help to ensure highest level of quality of a product being developed while working very closely with different stakeholders spread across globally
  Candidate will work independently and is highly self-motivated. Applies skills and knowledge of the business to test creative solutions to meet client and business needs.

   

• Mandatory Skills Description:

  - Strong SQL and Data Analyst experience.
  - Python skills
  - Proven experience as a BI developer/Data Engineer
  - Background in data warehouse design (e.g., dimensional modeling) and data mining
  - Understanding of database management systems, online analytical processing (OLAP) and ETL (Extract, transform, load) framework
  - Team player, good on communication with Business Analysts or Traders, - Highly Motivated, quick learner, general interest in Equity/Equity - Derivatives Trading Business. Experience in Risk Department (Risk area).
  - Exposure to Equities business
  - Must have worked in Agile min 2+ years
  - Must have good analytical & logical skills
  - Strong interpersonal, oral and written communication

   

• Nice-to-Have Skills Description:

  - Experience in Tableau
  - Understanding of Big Data concepts and technologies, enabling effective handling and analysis of large datasets
  - Concepts (HDFS,Spark,Hive,Impala)

   

• Languages:
  • English: B2 Upper Intermediate

Наш клієнт, Growe, провідна консалтингова компанія та група сервісів у сфері iGaming і розваг. Вони створюють стратегії, що працюють, та рішення, які масштабуються. Поєднуючи стратегічне бачення з практичним досвідом, Growe допомагає бізнесам орієнтуватися в динамічній індустрії, відкривати нові можливості, виходити на нові ринки та досягати сталого зростання.

Ідеально для тих, хто прагне:

• Проєктувати, розробляти та підтримувати масштабовані й надійні пайплайни даних за допомогою Airflow;
• Проєктувати та оптимізувати таблиці й запити в Athena, забезпечуючи високу продуктивність та оптимізацію витрат;
• Розробляти та підтримувати трансформації даних у dbt, створюючи повторно використовувані, тестовані та добре документовані моделі даних;
• Оптимізувати процеси обробки даних з точки зору продуктивності, надійності та ефективності витрат;
• Автоматизувати розгортання та конфігурацію інфраструктури за допомогою Terraform;
• Забезпечувати якість, цілісність і консистентність даних через моніторинг, валідацію, тестування та обробку помилок;
• Співпрацювати з командами Analytics, BI та Engineering для розуміння потреб у даних і розробки ефективних рішень;
• Оперативно виявляти та усувати проблеми з пайплайнами та якістю даних.

Досвід, який стане твоєю перевагою:

• Від 3 років досвіду в Data Engineering, включаючи практичний досвід побудови та підтримки ELT-пайплайнів;
• Сильні знання Python, SQL, включаючи моделювання даних, оптимізацію запитів і продуктивності;
• Практичний досвід роботи з Airflow для оркестрації workflow та розробки DAG;
• Практичний досвід роботи з dbt для трансформації та тестування даних, а також побудови модульних моделей даних;
• Практичний досвід роботи з AWS S3 та Athena, а також хороше розуміння архітектури Data Lake;
• Досвід роботи з Terraform для автоматизації та розгортання інфраструктури.

Ми цінуємо:

• Сильні аналітичні навички, здатність вирішувати складні задачі та увага до деталей;
• Здатність працювати самостійно та водночас ефективно взаємодіяти з командою;
• Проактивність і бажання постійно навчатися та професійно розвиватися.

Наші клієнти пропонують конкурентні переваги для підтримки вашого професійного та особистого зростання, зокрема:

• Орієнтація на здоров’я та добробут;
• Глобальне медичне страхування;
• Можливості для зростання;
• Програми бенефітів (компенсація спорту / стоматології / психолога тощо);
• Бонуси за досягнення результатів;
• Динамічне робоче середовище.

Долучайся — і нехай твоя історія зростання розпочнеться.

English version:

Our client, Growe, is a leading business advisory and services group in iGaming and Entertainment. Сreators of strategies that work and solutions that scale. Combining strategic vision with hands-on expertise, Growe helps businesses navigate the fast-evolving industry, seize new opportunities, enter new markets, and achieve sustainable growth.

Perfect for those who aim to:

• Design, develop, and maintain scalable and reliable data pipelines using Airflow;
• Design and optimize Athena tables and queries, ensuring efficient performance and cost-effectiveness;
• Develop and maintain data transformations in dbt, building reusable, testable, and well-documented data models;
• Optimize data workflows for performance, reliability, and cost-efficiency;
• Automate infrastructure provisioning and configuration using Terraform;
• Ensure data quality, integrity, and consistency through monitoring, validation, testing, and error handling;
• Collaborate with Analytics, BI, and Engineering teams to understand data requirements and deliver effective data solutions;
• Troubleshoot and resolve data pipeline and data quality issues in a timely manner.

Experience you’ll need to bring:

• 3+ years of experience in Data Engineering, with hands-on experience building and maintaining ELT pipelines;
• Strong Python and SQL skills, including data modeling, query optimization, and performance tuning;
• Hands-on experience with Airflow for workflow orchestration and DAG development;
• Practical experience with dbt for data transformation, testing, and modular data modeling;
• Hands-on experience with AWS S3 and Athena, and a solid understanding of data lake architectures;
• Experience with Terraform for infrastructure provisioning and automation.

It’s a perfect match if you have those personal features:

• Strong analytical and problem-solving skills with attention to detail;
• Ability to work independently while collaborating effectively within a team;
• Proactive mindset and willingness to continuously learn and improve.

Our clients offer competitive benefits to support your professional and personal growth, including:

• Health & Wellness Focus;
• Global Medical Coverage;
• Growth Opportunities;
• Benefits Programs (compensation for the gym/stomatology/psychological service & etc.);
• Performance-Driven Rewards;
• Dynamic Work Environment.

Apply, and let your growth journey begin.

Are you passionate about building cutting-edge, AI-ready data platforms from the ground up? We are looking for a Senior Data Engineer to join our Data Engineering Team and lead high-impact, greenfield initiatives.

You will work on building modern cloud-native data platforms, migrating on-premises legacy systems to the cloud, and laying the architectural foundation for AI-ready data infrastructure.

In this role, you will collaborate closely with Machine Learning, Data Science, and Product teams, serving as a key technical contributor and thought leader. You will also drive R&D efforts around agentic AI architectures, event-driven systems, and LLM-ready data pipelines — turning architectural concepts into production-grade solutions.

Responsibilities:

• Design and build scalable, cloud-native data platforms from greenfield to production
• Implement near-real-time ingestion pipelines using event-driven patterns
• Define and enforce platform standards, including Data Lake / Lakehouse principles, medallion architecture, and data contracts
• Refactor and optimise existing Spark and PySpark scripts for performance and maintainability
• Introduce best practices for code quality, testing, and CI/CD across data pipelines
• Drive adoption of AI tooling and agentic workflows within the data engineering team
• Ensure data quality, observability, and reliability across all pipelines and platforms

• Develop self-service tooling and microservices to simplify platform usage for other teams

   

Requirements:

• 5+ years of professional experience in Data Engineering
• Strong Python and SQL development skills for pipeline development and optimisation
• Proficiency in Apache Spark / PySpark, including query optimisation and performance tuning
• Hands-on experience with Databricks (preferred) or Snowflake
• Experience with at least one major cloud provider: Azure (preferred), AWS, or GCP
• Experience with stream processing technologies (Kafka, Spark Structured Streaming)
• Solid understanding of ETL/ELT patterns, data modelling (dimensional, Data Vault), and data warehousing
• Experience with orchestration tools (Apache Airflow, Azure Data Factory, or equivalent)
• Knowledge of Infrastructure as Code (Terraform or equivalent)
• Understanding of production-grade system requirements: reliability, scalability, observability, and performance

• Upper-Intermediate English level

   

Will be a plus

• Familiarity with RAG pipeline design and LLM integration patterns
• Knowledge of data governance frameworks and tools (Unity Catalog, Apache Atlas, or similar)
• Experience with dbt for data transformation and modelling

• Familiarity with MLflow, Feature Stores, or ML platform integration

   

Personal profile

• Self-driven and proactive in identifying improvements
• Comfortable working in a fast-paced, innovative environment
• Strong problem-solving mindset with attention to detail
• Open to experimenting with emerging technologies and approaches

_____________________________________________________________

Ти захоплюєшся створенням передових, AI-ready дата-платформ з нуля? Ми шукаємо Senior Data Engineer, щоб ти приєднався(-лася) до нашої команди Data Engineering та очолив(-ла) масштабні, інноваційні ініціативи з нуля.

Ти працюватимеш над побудовою сучасних хмарних дата-платформ, міграцією локальних (on-premises) легасі-систем у хмару та створенням архітектурного фундаменту для AI-ready дата-інфраструктури.

У цій ролі ти тісно співпрацюватимеш з командами Machine Learning, Data Science та Product, виступаючи ключовим технічним експертом та лідером думок. Також ти вестимеш R&D-роботи над agentic AI-архітектурами, подієво-орієнтованими системами та LLM-ready дата-пайплайнами — перетворюючи архітектурні концепції на готові до продакшену рішення.

Обовʼязки:

• Проєктувати та створювати масштабовані, хмарні дата-платформи від концепції до продакшену
• Реалізовувати пайплайни для майже реального часу (near-real-time ingestion) з використанням подієво-орієнтованих патернів
• Визначати та впроваджувати стандарти платформи, включно з принципами Data Lake / Lakehouse, медальйонною архітектурою та дата-контрактами
• Рефакторити та оптимізувати наявні скрипти на Spark та PySpark для підвищення продуктивності та зручності підтримки
• Запроваджувати найкращі практики якості коду, тестування та CI/CD для дата-пайплайнів
• Сприяти впровадженню AI-інструментів та agentic-підходів у команді дата-інженерів
• Забезпечувати якість, спостережуваність (observability) та надійність усіх пайплайнів і платформ

• Розробляти self-service інструменти та мікросервіси, що спрощують використання платформи іншими командами

   

Вимоги:

• 5+ років комерційного досвіду в Data Engineering
• Сильні навички розробки на Python та SQL для створення та оптимізації пайплайнів
• Впевнене володіння Apache Spark / PySpark, включно з оптимізацією запитів та налаштуванням продуктивності
• Практичний досвід роботи з Databricks (бажано) або Snowflake
• Досвід роботи з принаймні одним великим хмарним провайдером: Azure (бажано), AWS або GCP
• Досвід роботи з технологіями потокової обробки даних (Kafka, Spark Structured Streaming)
• Глибоке розуміння ETL/ELT-патернів, моделювання даних (dimensional, Data Vault) та побудови дата-складів
• Досвід роботи з інструментами оркестрації (Apache Airflow, Azure Data Factory або аналогами)
• Знання Infrastructure as Code (Terraform або аналогів)
• Розуміння вимог до продакшен-рішень: надійність, масштабованість, спостережуваність, продуктивність

• Рівень англійської — Upper-Intermediate

   

Буде плюсом:

• Знайомство з проєктуванням RAG-пайплайнів та патернами інтеграції LLM
• Знання фреймворків і інструментів для data governance (Unity Catalog, Apache Atlas або подібних)
• Досвід роботи з dbt для трансформації та моделювання даних

• Знайомство з MLflow, Feature Stores або інтеграцією з ML-платформами

   

Особистий профіль:

• Самомотивованість та проактивність у пошуку покращень
• Комфортна робота у швидкому та інноваційному середовищі
• Сильне аналітичне мислення та увага до деталей
• Відкритість до експериментів з новими технологіями та підходами

Join the Dataforest Team!

We are actively expanding our team and looking for strong new talent to join our ranks. If you are a Data Engineer seeking a friendly team, a healthy working environment, and a flexible schedule — you have found the right place to send your CV!

You'll be a great fit if you have:

- 2+ years of experience with Python;
- 2+ years of experience as a Data Engineer;
- Experience with Pandas;
- Experience with SQL DB / NoSQL (Redis, Mongo, Elasticsearch) / BigQuery;
- Familiarity with Amazon Web Services;
- Experience with Kafka;
- Knowledge of data algorithms and data structures is a MUST;
- Working with high volume tables 10m+.

What you'll do:

- Create ETL pipelines and data management solutions (API, Integration logic);
- Different data processing algorithms;
- Involvement in creation of forecasting, recommendation, and classification models.

Would be a plus:

- Experience with Spark (pyspark);
- Experience with Airflow;
- Experience in statistics;
- Knowledge of DS and Machine learning algorithms.

We ensure your growth with:

- Great networking opportunities with international clients, challenging tasks;
- Building interesting projects from scratch using new technologies;
- Personal and professional development opportunities;
- Competitive salary fixed in USD;
- Paid vacation and sick leaves;
- Flexible work schedule;
- Friendly working environment with minimal hierarchy;
- Team building activities, corporate events.

We're looking for a part-time Data Engineer / Data Scientist to support projects and other initiatives. You'll work closely with our existing team to develop new features and resolve data-related issues, picking up work as our current engineer's capacity is limited.

Tech stack: Snowflake, Python, Prefect

Nice to have:

- Experience with data parsing

- Experience with restaurant industry data and metrics

- Experience with API integrations

Requirements:

- Strong database/SQL skills (Snowflake preferred)
- Prefect

- AI/ML experience is a plus

- Part-time availability with some overlap with US business hours

Start: ASAP

We are looking for a Senior Data Engineer with specialized domain expertise in fraud detection, Anti-Money Laundering (AML), or transaction-monitoring systems to establish data-quality foundations for decision engines.

Our client is a fast-growing European FinTech company in the Business Spend Management space - providing corporate cards and related financial products to SME and mid-sized businesses across the EU and UK in a regulated environment.
You will embed directly into a product squad as a hands-on Individual Contributor (IC). 

Key Responsibilities:

• Architect and build robust data-quality frameworks specifically designed to power decision engines.
• Design, scale, and maintain reliable, high-throughput production data pipelines.
• Build infrastructure and workflows that enable fast, seamless deployment of fraud and transaction-monitoring rules.
• Bring deep domain knowledge in Fraud, AML, and Transaction Monitoring to production data engineering workflows.
• Multiply the output and quality of your squad while sharing data engineering patterns and best practices across the organization.

Requirements:

• Strong, senior-level 5+ years expertise in Python for data engineering and production pipeline development.
• Experience/background in Fraud, AML, or Transaction-Monitoring systems.
• Proven track record of establishing data-quality foundations for automated decisioning systems.
• Extensive experience building production data pipelines and supporting rapid rule deployment workflows.

Nice-to-Have Skills:

• Hands-on experience with Airflow, SQL, PostgreSQL, and Google BigQuery (standard stack for data/analytics workloads).
• Experience working in hybrid cloud environments (AWS primary + GCP analytics).
• Familiarity with modern engineering workflows (Linear, GitHub, Notion, Slack) and AI-assisted development (Claude Code, GitHub Copilot).

N-iX is a global software development service company that helps businesses across the globe create next-generation software products. Founded in 2002, we unite 2,400+ tech-savvy professionals across 40+ countries, working on impactful projects for industry leaders and Fortune 500 companies. Our expertise spans cloud, data, AI/ML, embedded software, IoT, and more, driving digital transformation across finance, manufacturing, telecom, healthcare, and other industries. Join N-iX and become part of a team where your ideas make a real impact.

We are looking for a Lead Data Engineer to join our team and contribute to one of Europe's leading online automotive marketplaces, serving 30+ million monthly users across 18 countries.

As a Lead Data Engineer, you will lead a team of data engineers and analysts, partnering closely with business stakeholders and senior analysts to translate marketplace analytics needs — from web & app tracking to marketing performance — into robust data models and pipelines that power the company's key business decisions.

This role sits closer to the business than a typical data engineering position. The Data Platform Engineering team owns the underlying platform and infrastructure, so you'll focus on understanding analytics use cases, shaping data models, and enabling analysts and stakeholders to answer their most important business questions.

Responsibilities:

• Lead and mentor a team of data engineers, providing technical direction as well as people leadership.
• Partner with business stakeholders and senior analysts to gather requirements and translate business KPIs and OKRs into data models and pipelines.
• Design, build, and maintain scalable data models that support marketplace analytics, including web/app tracking and marketing use cases.
• Write and optimize complex SQL to transform and model data for analytics consumption.
• Build and troubleshoot code-based data pipelines using Python, Spark, and Airflow, jumping in hands-on when needed while guiding the wider engineering team's pipeline work.
• Champion data quality by implementing and maintaining data testing practices across the team's pipelines.
• Evaluate and apply semantic layer concepts to make data more accessible and consistent for business users.
• Explore and adopt AI tooling provided by the company to improve team productivity and data workflows.
• Act as a bridge between the Data Platform Engineering team (who own infrastructure) and the business, ensuring analytics needs are well understood and delivered.
• Deliver on product requirements on time while keeping tech debt and redundancy to a minimum, following best practices and standards.
• Keep yourself and stakeholders aligned with clear, ongoing visibility into project status, surfacing risks early along with a plan and timeline for resolving them.

Requirements:

• Proven experience leading a data engineering team — this role requires genuine people leadership, not just senior-level technical skills.
• Strong ownership mindset, with a track record of delivering reliably on time while minimizing tech debt and redundancy and adhering to best practices and standards.
• 5+ years of hands-on experience in Data Engineering.
• Hands-on experience building data pipelines with Python and Spark — the project's pipelines are code-based (not SQL/dbt-based) — with the ability to jump in and contribute directly when needed, as well as a deep enough understanding to follow and guide what other engineers on the team are building.
• Hands-on experience with Airflow for orchestrating data pipelines.
• Proficiency with Git for version control.
• Strong SQL skills, with the ability to write and optimize complex queries (experience with any SQL dialect is fine — prior exposure to Athena specifically is not required).
• Solid data modeling skills, with experience designing models that serve analytics and business intelligence use cases.
• Excellent communication skills, with the ability to engage business stakeholders and senior analysts to gather requirements and understand KPIs/OKRs.
• Familiarity with data testing practices and tools.
• Familiarity with AI tooling for data engineering workflows.
• English proficiency at B2/C1 level or higher.

Nice to have:

• Experience with marketplace analytics, including web & app tracking and a good understanding of marketing/business metrics.
• Previous experience working with a semantic layer.
• Experience with AWS — the project runs on an AWS data lake, so this is an advantage, though equivalent experience with other cloud providers is also fine given the transferable concepts.

Шукаємо у команду Senior DevOps / SRE Engineer (Remote).

Якщо ви маєте бажання працювати в невеликому колективі разом із сильною командою, радо розглянемо ваш відгук! Ми шукаємо не лише сильного DevOps Engineer, а й інженера із досвідом Site Reliability Engineering (SRE), який готовий брати на себе технічне лідерство, ділитися знаннями та допомагати розвиватися іншим членам команди. Націлені на довгострокову співпрацю з компенсацією, що базуватиметься на вашому досвіді роботи.
 

Завантаженість: повна зайнятість — 40 год/тиждень. Робота віддалена. Оплата погодинна.
 

Стек технологій:

- Scripting: Bash | Python | Makefile

- Containers and Orchestration: Kubernetes | Docker | GKE

- Infrastructure as Code (IaC): Terraform | Ansible

- CI/CD & Automation: GitHub Actions | CircleCI | TravisCI

- Cloud Providers & IaaS: AWS | GCP | Azure | Hetzner

- Databases: SQL | NoSQL (PostgreSQL, Redis…)

- Authorization and Security: OpenSSL

- Observability and Monitoring: Prometheus | Grafana | ELK Stack (Elasticsearch, Logstash, Kibana)

- Operating Systems: Linux
 

Site Reliability Engineering (SRE):
- SLI / SLO / SLA | Incident Response | Root Cause Analysis (RCA) | - High Availability | Capacity Planning | Disaster Recovery | 
- Performance Optimization | Reliability Engineering | 
 

Буде плюсом:

- Infrastructure Management: Developing and implementing infrastructure, configuration, and code branching strategies.

- Quality Assurance & Testing: Conducting integration, regression, UI/UX, API, load/stress, and other types of testing.

- Bug Tracking & Issue Management: Identifying, documenting, and tracking software defects and bugs.

- Performance & Optimization: Monitoring and analyzing quality metrics to identify areas for improvement.

- Automated Testing: Experience with automated testing frameworks such as Selenium, Appium, JMeter, etc.

Mentoring & Leadership:
- Досвід менторингу Junior/Middle інженерів, проведення code review, технічних обговорень, knowledge sharing та допомоги команді у професійному розвитку.
 

Вимоги до кандидата:

- Досвід роботи DevOps Engineer та практичний досвід Site Reliability Engineering (SRE)
- Досвід побудови та підтримки високодоступних production-систем із високими вимогами до reliability.

- Досвід роботи з Kubernetes у production-середовищі

- Розуміння принципів високої доступності, масштабування та відмовостійкості систем

- Досвід побудови та підтримки CI/CD процесів

- Англійська мова — Intermediate+

- Уміння слідувати code conventions

- Здатність навчатися

- Здатність наполегливо працювати

- Критичне мислення

- Витривалість

- Спроможність лаконічно та чітко пояснювати свою думку

- Бажання ділитися знаннями, проводити менторинг та допомагати розвиватися іншим членам команди

- Відданість нашим проєктам

- Прозорість
 

Що отримаєте:

- Віддалені умови роботи

- Удосконалення навичок планування та продуктивності

- Робота у вимогливому, але дружньому середовищі серед A-гравців

- Регулярний зворотний зв'язок і допомога в плануванні вашого навчального процесу та кар'єрного зростання

- Незалежність від місцевого ринку та долучення до глобальної економіки

- Підвищення рівня володіння англійською мовою

- Корпоративні навчання, технічні воркшопи та тренінги для постійного підвищення кваліфікації

Level: Senior Engagement: Long-term contract Location: Europe (EU / EEA / UK), remote Working hours: EU business hours, shifted 2–3 hours later to ensure daily overlap with US West Coast (PST/PDT) mornings

About the Client

Our client is a leading enterprise data platform company building an open, high-performance data lakehouse for AI and analytical workloads. The platform combines an intelligent SQL query engine, an AI-ready semantic layer, and an open catalog built on Apache Iceberg — enabling Fortune 500 companies across finance, energy, manufacturing, and logistics to unify, query, and govern data at massive scale across cloud and on-premise sources.

About the Role

We are looking for a Senior SDET to lead the design of automated test frameworks and testing strategy for a large-scale distributed data platform. You will own the quality of the query engine, connectivity layer, and backend services end-to-end — from framework architecture through CI/CD infrastructure across all major clouds — and mentor middle engineers on the team.

This is a data-heavy, backend-focused role. We are not looking for web/UI QA engineers — the work centers on validating distributed query execution, data correctness at scale, connectivity drivers, and backend microservices.

Responsibilities

• Architect, design, and evolve automated test frameworks in Python / pytest for backend services, REST APIs, and distributed data components.
• Define testing strategy for new features and platform components — coverage, risk assessment, and quality gates.
• Own end-to-end, integration, performance, and regression testing covering SQL query execution, data correctness at scale, and platform APIs.
• Lead performance and load testing efforts with JMeter, including workloads over JDBC / ODBC / Arrow Flight drivers.
• Design and validate large-scale data testing scenarios — query plans, result correctness across heterogeneous data sources, metadata consistency, and behavior under high concurrency.
• Own CI/CD test pipelines in Jenkins — architect, maintain, and continuously improve.
• Provision and manage test environments in Kubernetes (GKE / EKS / AKS) across GCP, AWS, and Azure using Docker; drive automation and reproducibility.
• Investigate complex, cross-layer failures and drive root-cause analysis with engineering.
• Mentor middle SDETs, review test designs, and set quality standards across the team.
• Partner with US-based development leads on shift-left practices, testability, and release readiness.

Required Qualifications

• Education: B.S. or M.S. in Computer Science, Computer Engineering, or a related technical field.
• Programming: Strong proficiency in Python, including pytest, with deep understanding of OOP, software design principles, and test framework architecture.
• SQL & Data: Advanced SQL skills and strong understanding of relational and analytical data systems, including query execution internals.
• Data-intensive testing experience: Demonstrated experience testing data-intensive systems — query engines, ETL/ELT pipelines, streaming platforms, or analytical databases. Candidates with only web/UI QA backgrounds are not a fit.
• Testing experience: 5+ years in backend/system test automation, with demonstrated ownership of test strategy and infrastructure.
• CI/CD & DevOps: Solid experience architecting and maintaining Jenkins pipelines and test environments.
• Containers & Orchestration: Strong working knowledge of Docker and Kubernetes (running workloads, debugging pods, deploying complex environments).
• Cloud: Hands-on experience with at least one major cloud (GCP, AWS, or Azure); exposure to more than one is a strong plus.
• Version Control: Confident with Git / GitHub workflows and code review practices.
• English: Upper-Intermediate or higher (B2+) — daily written and verbal communication with a US-based engineering team.
• Availability: Able to work EU hours with a 2–3 hour shift toward US West Coast time to ensure daily overlap with the client team.
• Leadership: Prior experience mentoring engineers, defining test strategy, or leading a QA/SDET function.

Desired Skills

• Deep experience testing REST APIs and backend microservices at scale.
• Hands-on with distributed computing frameworks (e.g., Apache Spark, Kafka) and MPP SQL query engines (e.g., Presto, Trino, or similar).
• Strong understanding of modern data lakehouse concepts, open table formats (Apache Iceberg), and data warehousing.
• Experience with data connectivity drivers: JDBC, ODBC, Arrow Flight.
• Performance testing with JMeter or comparable load-testing tools at production scale.
• Kubernetes on managed services (GKE / EKS / AKS) and multi-cloud exposure.
• IaC tools such as Terraform.
• Deep understanding of query plan generation, query acceleration / materializations, and metadata integrity in distributed data systems.
• Prior experience leading a QA/SDET function in a data-platform or database engineering environment.
  Please note: We can consider only candidates currently residing in the EU, EEA, or the UK.

Level: Middle Engagement: Long-term contract Location: Europe (EU / EEA / UK), remote Working hours: EU business hours, shifted 2–3 hours later to ensure daily overlap with US West Coast (PST/PDT) mornings

About the Client

Our client is a leading enterprise data platform company building an open, high-performance data lakehouse for AI and analytical workloads. The platform combines an intelligent SQL query engine, an AI-ready semantic layer, and an open catalog built on Apache Iceberg — enabling Fortune 500 companies across finance, energy, manufacturing, and logistics to unify, query, and govern data at massive scale across cloud and on-premise sources.

About the Role

We are looking for a Middle-level Software Engineer to work on the core query engine of a large-scale distributed data platform. You will develop features across query planning, optimization, and execution, contribute to performance-critical components, and help evolve the platform's ability to process massive analytical workloads across heterogeneous data sources.

This is a systems-level, backend engineering role focused on distributed data processing internals — not application development or CRUD services.

Responsibilities

• Develop and maintain features across the query engine — planning, optimization, execution, and data access layers.
• Write high-quality, performance-conscious code in Java and/or C++.
• Work with SQL semantics, query plans, and execution operators over large-scale distributed data.
• Integrate with columnar formats, open table formats, and connectivity drivers used across the platform.
• Contribute to CI/CD pipelines and automated testing — participate in build, test, and release workflows in Jenkins.
• Deploy and validate work in Kubernetes (GKE / EKS / AKS) across GCP, AWS, and Azure using Docker.
• Debug complex issues spanning query planning, distributed execution, memory management, and I/O.
• Collaborate closely with US-based engineering teams on design reviews, code reviews, and technical decisions.

Required Qualifications

• Education: B.S. or M.S. in Computer Science, Computer Engineering, or a related technical field.
• Programming: Strong proficiency in Java or C++, with solid OOP and software design fundamentals. Candidates comfortable with both are especially valued.
• SQL & Data: Strong SQL skills and solid understanding of relational and analytical data systems, including query execution concepts.
• Data processing systems experience: Hands-on experience with data processing systems — query engines, distributed databases, ETL/ELT frameworks, or analytical platforms.
• Engineering experience: 3+ years in backend/systems software engineering.
• CI/CD & DevOps basics: Practical experience with Jenkins pipelines and modern development workflows.
• Containers: Working knowledge of Docker and basic Kubernetes (running workloads, debugging pods, kubectl fluency).
• Cloud: Comfortable operating in at least one major cloud (GCP, AWS, or Azure).
• Version Control: Confident with Git / GitHub workflows.
• English: Upper-Intermediate or higher (B2+) — daily written and verbal communication with a US-based engineering team.
• Availability: Able to work EU hours with a 2–3 hour shift toward US West Coast time to ensure daily overlap with the client team.

Desired Skills

• Experience with Apache Arrow (columnar in-memory format).
• Familiarity with Apache Calcite (SQL parsing, planning, optimization framework).
• Exposure to Gandiva or LLVM-based expression compilation.
• Experience with open table formats — Apache Iceberg, Delta Lake, or Hudi.
• Familiarity with distributed computing frameworks (e.g., Apache Spark, Kafka) and MPP SQL query engines (e.g., Presto, Trino, or similar).
• Understanding of query planning, optimization, and execution internals.
• Experience with data connectivity drivers: JDBC, ODBC, Arrow Flight.
• Kubernetes on managed services (GKE / EKS / AKS) and multi-cloud exposure.
• IaC tools such as Terraform.
• Experience with performance profiling and optimization of latency-sensitive systems.
  Please note: We can consider only candidates currently residing in the EU, EEA, or the UK.
  Please note: We can consider only candidates currently residing in the EU, EEA, or the UK

Level: Middle Engagement: Long-term contract Location: Europe (EU / EEA / UK), remote Working hours: EU business hours, shifted 2–3 hours later to ensure daily overlap with US West Coast (PST/PDT) mornings

About the Client

Our client is a leading enterprise data platform company building an open, high-performance data lakehouse for AI and analytical workloads. The platform combines an intelligent SQL query engine, an AI-ready semantic layer, and an open catalog built on Apache Iceberg — enabling Fortune 500 companies across finance, energy, manufacturing, and logistics to unify, query, and govern data at massive scale across cloud and on-premise sources.

About the Role

We are looking for a Middle-level SDET to design and maintain automated tests for a large-scale distributed data platform. You will validate the correctness, performance, and reliability of the query engine, connectivity layer, and backend services across all major clouds.

This is a data-heavy, backend-focused role. We are not looking for web/UI QA engineers — the work centers on validating distributed query execution, data correctness at scale, connectivity drivers, and backend microservices.

Responsibilities

• Develop and maintain automated tests in Python / pytest for backend services, REST APIs, and distributed data components.
• Write end-to-end, integration, and regression tests covering SQL query execution, data correctness, and platform APIs.
• Support performance and load testing with JMeter, including workloads over JDBC / ODBC / Arrow Flight drivers.
• Validate data-intensive scenarios — query plans, result correctness across data sources, metadata consistency, and behavior under concurrency.
• Contribute to CI/CD test pipelines in Jenkins — configure, maintain, and troubleshoot.
• Provision and manage test environments in Kubernetes (GKE / EKS / AKS) across GCP, AWS, and Azure using Docker.
• Investigate failures across the stack — query engine, distributed services, drivers, infrastructure — and drive them to resolution with engineering.
• Collaborate with US-based developers on testability and quality gates.

Required Qualifications

• Education: B.S. or M.S. in Computer Science, Computer Engineering, or a related technical field.
• Programming: Strong proficiency in Python, including pytest, with a solid grasp of OOP and software design principles.
• SQL & Data: Strong SQL skills and solid understanding of how relational and analytical data systems work.
• Data-intensive testing experience: Hands-on experience testing data-intensive systems — query engines, ETL/ELT pipelines, streaming platforms, or analytical databases. Candidates with only web/UI QA backgrounds are not a fit.
• Testing experience: 3+ years in backend/system test automation or SDET roles.
• CI/CD & DevOps basics: Practical experience with Jenkins pipelines and deploying/maintaining test environments.
• Containers: Working knowledge of Docker and basic Kubernetes (running workloads, debugging pods, kubectl fluency).
• Cloud: Comfortable operating in at least one major cloud (GCP, AWS, or Azure).
• Version Control: Confident with Git / GitHub workflows.
• English: Upper-Intermediate or higher (B2+) — daily written and verbal communication with a US-based engineering team.
• Availability: Able to work EU hours with a 2–3 hour shift toward US West Coast time to ensure daily overlap with the client team.

Desired Skills

• Experience testing REST APIs and backend microservices at scale.
• Familiarity with distributed computing frameworks (e.g., Apache Spark, Kafka) and MPP SQL query engines (e.g., Presto, Trino, or similar).
• Understanding of modern data lakehouse concepts, open table formats (Apache Iceberg), and data warehousing.
• Experience with data connectivity drivers: JDBC, ODBC, Arrow Flight.
• Performance testing with JMeter or comparable load-testing tools.
• Kubernetes on managed services (GKE / EKS / AKS) and multi-cloud exposure.
• IaC tools such as Terraform.
• Understanding of query plan generation, query acceleration / materializations, and metadata integrity in distributed data systems.
  Please note: We can consider only candidates currently residing in the EU, EEA, or the UK

Level: Senior Engagement: Long-term contract Location: Europe (EU / EEA / UK), remote Working hours: EU business hours, shifted 2–3 hours later to ensure daily overlap with US West Coast (PST/PDT) mornings

About the Client

Our client is a leading enterprise data platform company building an open, high-performance data lakehouse for AI and analytical workloads. The platform combines an intelligent SQL query engine, an AI-ready semantic layer, and an open catalog built on Apache Iceberg — enabling Fortune 500 companies across finance, energy, manufacturing, and logistics to unify, query, and govern data at massive scale across cloud and on-premise sources.

About the Role

We are looking for a Senior Software Engineer to design, build, and own significant components of the core query engine of a large-scale distributed data platform. You will lead work across query planning, optimization, and execution — driving architectural decisions, mentoring middle engineers, and pushing the platform's performance and scalability boundaries across all major clouds.

This is a systems-level, backend engineering role focused on distributed data processing internals — not application development or CRUD services.

Responsibilities

• Architect, design, and implement significant components of the query engine — planner, optimizer, execution operators, memory management, and data access layers.
• Write and review high-quality, performance-critical code in Java and/or C++.
• Own end-to-end delivery of features from technical design through production rollout.
• Drive performance optimization work — profiling, benchmarking, and eliminating bottlenecks in latency- and throughput-sensitive paths.
• Integrate deeply with columnar formats, open table formats, and connectivity drivers.
• Mentor middle engineers, lead code reviews, and set technical standards for the team.
• Contribute to CI/CD architecture and quality processes across Jenkins, containerization, and multi-cloud deployment (GCP, AWS, Azure via Kubernetes / Docker).
• Debug complex, cross-layer issues spanning query planning, distributed execution, memory management, and I/O.
• Partner with US-based engineering leads on design reviews, architectural decisions, and roadmap execution.

Required Qualifications

• Education: B.S. or M.S. in Computer Science, Computer Engineering, or a related technical field.
• Programming: Strong proficiency in Java or C++, with deep understanding of OOP, systems design, memory management, and concurrency. Candidates strong in both are especially valued.
• SQL & Data: Advanced SQL skills and strong understanding of query execution internals — planning, optimization, and operator implementation.
• Data processing systems experience: Demonstrated experience building or extending data processing systems — query engines, distributed databases, ETL/ELT frameworks, or analytical platforms.
• Engineering experience: 5+ years in backend/systems software engineering, with a track record of owning significant components.
• CI/CD & DevOps: Solid experience with Jenkins and modern engineering workflows.
• Containers & Orchestration: Strong working knowledge of Docker and Kubernetes.
• Cloud: Hands-on experience with at least one major cloud (GCP, AWS, or Azure); exposure to more than one is a strong plus.
• Version Control: Confident with Git / GitHub workflows and rigorous code review practices.
• English: Upper-Intermediate or higher (B2+) — daily written and verbal communication with a US-based engineering team.
• Availability: Able to work EU hours with a 2–3 hour shift toward US West Coast time to ensure daily overlap with the client team.
• Leadership: Prior experience mentoring engineers, leading technical designs, or owning components end-to-end.

Desired Skills

• Deep experience with Apache Arrow (columnar in-memory format).
• Hands-on experience with Apache Calcite (SQL parsing, planning, optimization framework).
• Experience with Gandiva or LLVM-based expression compilation and code generation.
• Experience with open table formats — Apache Iceberg, Delta Lake, or Hudi.
• Deep familiarity with distributed computing frameworks (e.g., Apache Spark, Kafka) and MPP SQL query engines (e.g., Presto, Trino, or similar).
• Deep understanding of query planning, optimization (cost-based, rule-based), and execution internals.
• Experience with data connectivity drivers: JDBC, ODBC, Arrow Flight.
• Kubernetes on managed services (GKE / EKS / AKS) and multi-cloud exposure.
• IaC tools such as Terraform.
• Track record of performance optimization at the systems level — profiling, vectorization, cache/memory-conscious design.
• Prior experience contributing to open-source data infrastructure projects.
  Please note: We can consider only candidates currently residing in the EU, EEA, or the UK

We are looking for a Senior Data Engineer.

About the project:

Our customer is the European online car market with over 30 million monthly users, with a market presence in 18 countries. As a Senior Data Engineer, you will play a pivotal role in shaping the future of online car markets and enhancing the user experience for millions of car buyers and sellers.

Requirements:

• 5+ years of experience in data engineering
• Expertise in AWS services ( Glue, Athena, etc.)
• Proficiency in Python, PySpark, GCP
• Experience with Snowflake, DBT, SQL, Airflow
• Experience with Qlik to AWS Datalake (nice to have)
• Solid experience in the usage of the AI tools for development (Claude Code, Codex, and similar)
• Experience with AI-native migration
• English - Upper-Intermediate+
• Experience in building and maintaining data pipelines
• Experience in building data platforms, not just using them
• Proficiency in data modeling techniques and best practices

Responsibilities:

• Work on migration from Snowflake to the client’s service
• Propose improvements, be actively involved in team discussions and decision-making, and drive initiatives
• Building an AI-native data migration capability
• Work closely with a team of Senior Engineers, Product & Project Manager and Data Analysts

About the Role
 

We are looking for a Senior Infrastructure Engineer to join a growing engineering team responsible for building, maintaining, and improving highly available cloud infrastructure supporting large-scale production systems.

This role combines infrastructure engineering, site reliability engineering (SRE), cloud operations, and automation. You will help ensure platform reliability, optimize cloud environments, improve observability, automate operational processes, and collaborate closely with software engineering teams to deliver resilient cloud-native solutions.
 

The ideal candidate is a hands-on infrastructure engineer who enjoys solving complex production challenges, improving system reliability, and building scalable automation.
 

Responsibilities

• Design, build, and maintain scalable, highly available cloud infrastructure.
• Improve reliability, fault tolerance, and performance across distributed systems.
• Lead production incident response, root cause analysis, and post-incident improvements.
• Develop monitoring, alerting, and automated recovery solutions.
• Optimize infrastructure performance and capacity planning.
• Build automation to reduce manual operational effort.
• Collaborate with engineering teams to improve deployment pipelines and platform reliability.
• Contribute to infrastructure-as-code and GitOps practices.
• Support cloud-native applications running in Kubernetes environments.
• Participate in on-call rotations supporting production services.
• Mentor engineers and promote infrastructure best practices.
• Continuously improve operational processes, observability, and system resilience.
   

Required Qualifications

• 5+ years of experience in Infrastructure Engineering, Site Reliability Engineering (SRE), or DevOps.
• Strong experience with AWS cloud services.
• Hands-on experience with Infrastructure as Code (Terraform, CloudFormation, or similar).
• Experience supporting production Kubernetes environments.
• Strong Linux administration skills.
• Experience with Docker and containerized workloads.
• Familiarity with CI/CD pipelines and deployment automation.
• Experience working with cloud-native distributed systems.
• Knowledge of monitoring and observability tools such as Prometheus, Grafana, or OpenTelemetry.
• Programming or scripting experience with Python, Go, Bash, or similar languages.
• Solid understanding of networking, security, authentication, APIs, and load balancing.
• Experience with incident management and disaster recovery practices.
• Strong communication, collaboration, and problem-solving skills.

Nice to Have

• Experience with Kafka or other messaging platforms.
• Experience with GitOps workflows.
• Knowledge of API Gateway technologies.
• Experience with Java and Spring Framework.
• Strong database administration or performance tuning experience.
• Experience mentoring engineers and leading infrastructure initiatives.
   

Benefits

• A competitive salary and flexible compensation package
• Professional development tools (mentorship program, tech talks and trainings)
• Medical insurance
• Free corporate English classes and speaking clubs with a native speaker