Jobs Data Engineer

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.

• 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

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

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

In a partnership with one of global consulting companies, we’re looking for a Senior AWS Cloud Platform Engineer 

The role is responsible for implementing the initial configuration of a large data team’s AWS cloud accounts in a federated data-mesh structure, including interfacing with the

central platform team ensuring the approach is aligned with platform standards and maintains clear boundaries of responsibility between data-team and platform-team.

The areas for configuration include but may not be limited to console governance, cost management, monitoring & observability configuration and security.

The role will additionally be expected to document their work thoroughly and autonomously, with a view to hand-over operational management of the platform and

account to data-team members at the conclusion of the contract. This will include clear delivery of training where appropriate.

Must have

• 5+ years AWS experience

• Deep expertise in Core AWS Services (Identity and access management, VPC

& Networking, Security and Storage)

• Strong scripting or coding skills in Python, Go, Bash etc.

• IaC CloudFormation, CDK, other IaC tools considered eg Terraform

• Observability (CloudWatch, Grafana)

• Audit logging (AWS CloudTrail, Centralising logging, Log retention and

compliance)

• CI/CD Automation and DevOps experience, particularly using Github Actions

• FinOps/AWS cost management experience

• Security governance

• Experience supporting analytics or ML platforms

• Significantly important - Data Platforms experience: ETL Processes, Data Injections, SageMaker, Mash Solution

• Experience with AWS analytics services, AWS Redshift, AWS MWAA, AWS

Desirable

• LakeFormation and SageMaker Unified Studio

• Cloud platform network management experience

• AWS Certified DevOps Engineer – Professional or AWS Certified Solutions

Architect - Professional

• Familiarity with AWS ‘well-architected’ framework and other relevant materials• Exposure to data engineering specific AWS tooling, particularly data-sharing

solutions

• AWS Redshift DBA experience

RESPONSIBILITIES

Backend Pipelines & Data Processing

• Build and maintain backend pipelines that consume data from Kafka, apply business logic/ETL, and produce reliable outputs at scale.
• Implement and optimize event-driven architectures (producers/consumers, streaming patterns, batching where relevant).
• Design systems around high volume / high throughput requirements (autoscaling, high availability, resilience).

Database & Performance (Postgres-heavy)

• Own data modeling and performance work in PostgreSQL: query tuning, indexing strategies, schema design, troubleshooting slow queries
• Work with additional data stores as needed (e.g., Redis) based on system needs.

Full-Stack Contribution (light frontend)

• Contribute occasionally to frontend needs in React (new pages, small UI fixes).

Production Engineering

• Build/operate services in a true production environment:
  • observability (logs/metrics/tracing), debugging, reliability improvements
  • performance profiling and bottleneck analysis

TECHNICAL REQUIREMENTS

Backend & Architecture

• TypeScript + Node.js (production experience)
• NestJS (strong preference, used as the main backend framework)
• Strong experience designing backend systems at high scale:
  • autoscaling, HA, performance, resilience, failure modes
• Strong knowledge of event-driven systems:
  • Kafka-based ingestion/streaming, producers/consumers, pipelines, batching concepts

Data Stores

• PostgreSQL / SQL proficiency (deep skills required: schema modeling, query optimization)
• Kafka (hands-on experience strongly preferred)
• Redis (working knowledge)

Infrastructure

• Experience working in AWS + Kubernetes environments (production familiarity expected)

Observability

• Practical experience with logs, metrics, tracing to monitor and debug production systems.

Nice-to-Have

• Security domain familiarity (application security / runtime protection / vulnerability management) — advantage, not mandatory
• Prior work in data-intensive security platforms or similar high-scale systems

AI Tooling Expectations

• Oligo strongly encourages AI-assisted development (primarily Claude; some Cursor).
• They have automation and AI-supported workflows (including AI-assisted code review) and value engineers who can work effectively in that environment.

Main requirements

dbt, Google BigQuery, Python, SQL, Git

Requirements

Position name: Data Engineer (Mid-Level)

Level: Mid-Level

Hard skills requirements:

• Hands-on experience with dbt (models, tests, documentation)
• Experience with Google BigQuery
• Solid Python skills for data engineering
• Strong SQL and data modeling
• Production data pipeline experience
• Git and collaborative development workflows

Soft skills requirements:

• Strong English — written and verbal
• Cross-functional communication
• Ownership mindset — takes accountability end-to-end
• High motivation to learn and grow in a startup environment

Office/Remote: Remote — any location

Project tasks:

• Build and maintain ELT data pipelines for game and product data
• Develop, test, and document dbt models following analytics engineering best practices
• Work with Google BigQuery for analytics, optimization, and cost efficiency
• Write clean Python for data processing and automation
• Ensure data quality, reliability, and consistency across datasets
• Monitor pipelines, troubleshoot issues, take ownership of fixes end-to-end
• Contribute to data architecture decisions in a fast-paced startup environment

English level: Upper-Intermediate / Advanced

Phoenix Games is a technology company building next-generation iGaming and Web3 products for a global audience. We leverage AI, cloud technologies, blockchain, and advanced analytics to create intelligent, data-driven gaming experiences.

As we continue to scale, we're looking for Data Engineer / Data Scientist to help us build modern data infrastructure, develop machine learning solutions, and turn massive volumes of data into actionable insights.

What You'll Do

• Design, build, and maintain scalable data pipelines and ETL/ELT processes.
• Develop and optimize data warehouses and data lake architectures.
• Collect, clean, and transform large datasets from multiple sources.
• Build predictive models, recommendation systems, and analytical solutions.
• Apply machine learning techniques to improve player engagement, fraud detection, personalization, and business intelligence.
• Design dashboards and reporting solutions for business stakeholders.
• Collaborate with Product Managers, Engineers, and BI teams to define data-driven strategies.
• Optimize data processing performance and ensure data quality.
• Implement monitoring, validation, and governance for data pipelines.
• Research and evaluate new AI and machine learning technologies.

Tech Stack

• Python
• SQL
• PostgreSQL
• Snowflake / BigQuery / Redshift
• Apache Airflow
• Spark
• Pandas
• NumPy
• Scikit-learn
• TensorFlow / PyTorch
• MLflow
• Docker
• Kubernetes
• AWS / Azure / GCP
• Git
• Power BI / Looker / Tableau

Requirements

• 2+ years of commercial experience in Data Engineering, Data Science, or Machine Learning.
• Strong Python programming skills.
• Advanced SQL knowledge.
• Experience building scalable data pipelines.
• Experience with cloud data platforms.
• Strong understanding of data modeling and database design.
• Experience with machine learning algorithms and model evaluation.
• Experience working with large datasets.
• Familiarity with Docker and cloud environments.
• Strong analytical and problem-solving skills.
• Upper-Intermediate English or higher.

Nice to Have

• Experience with LLMs, Generative AI, or AI agents.
• Knowledge of real-time data streaming (Kafka, RabbitMQ).
• Experience with feature engineering and MLOps.
• Experience with fraud detection or recommendation systems.
• Familiarity with blockchain analytics or Web3 ecosystems.

What We Offer

• Fully remote work from anywhere in Europe.
• Long-term B2B cooperation.
• Competitive salary paid in EUR or USD.
• Annual salary reviews.
• Performance-based bonus program.
• Annual company bonus.
• 25 paid vacation days.
• Paid sick leave.
• Flexible working hours.
• Home office budget.
• Laptop or equipment allowance.
• Learning & development budget for courses, certifications, conferences, and books.
• English language lessons.
• Private health insurance.
• Mental health support program.
• Sports and wellness compensation.
• Team-building activities and international company retreats.
• Opportunity to work on AI, Web3, blockchain, and large-scale data platforms.
• Clear career growth opportunities within a rapidly expanding international product company.

Why Join Phoenix Games?

At Phoenix Games, data is at the core of every product decision. You'll work with modern technologies, solve complex data challenges, and help build intelligent systems that power the next generation of online gaming.

If you're passionate about data engineering, machine learning, and creating impactful AI-driven solutions, we'd love to hear from you.

We are seeking a proactive Senior Data Engineer to join our vibrant team. As a Senior Data Engineer, you will play a critical role in designing, developing, and maintaining sophisticated data pipelines, Ontology Objects, and Foundry Functions within Palantir Foundry. The ideal candidate will possess a robust background in cloud technologies, data architecture, and a passion for solving complex data challenges.

Key Responsibilities:

• Collaborate with cross-functional teams to understand data requirements, and design, implement and maintain scalable data pipelines in Palantir Foundry, ensuring end-to-end data integrity and optimizing workflows.
• Gather and translate data requirements into robust and efficient solutions, leveraging your expertise in cloud-based data engineering. Create data models, schemas, and flow diagrams to guide development.
• Develop, implement, optimize and maintain efficient and reliable data pipelines and ETL/ELT processes to collect, process, and integrate data to ensure timely and accurate data delivery to various business applications, while implementing data governance and security best practices to safeguard sensitive information.
• Monitor data pipeline performance, identify bottlenecks, and implement improvements to optimize data processing speed and reduce latency. 
• Troubleshoot and resolve issues related to data pipelines, ensuring continuous data availability and reliability to support data-driven decision-making processes.
• Stay current with emerging technologies and industry trends, incorporating innovative solutions into data engineering practices, and effectively document and communicate technical solutions and processes.

Tools and skills you will use in this role:

• Palantir Foundry
• Python
• PySpark
• SQL
• TypeScript

Required:

• 5+ years of experience in data engineering, preferably within the pharmaceutical or life sciences industry;
• Strong proficiency in Python and PySpark;
• Proficiency with big data technologies (e.g., Apache Hadoop, Spark, Kafka, BigQuery, etc.);
• Hands-on experience with cloud services (e.g., AWS Glue, Azure Data Factory, Google Cloud Dataflow);
• Expertise in data modeling, data warehousing, and ETL/ELT concepts;
• Hands-on experience with database systems (e.g., PostgreSQL, MySQL, NoSQL, etc.);
• Proficiency in containerization technologies (e.g., Docker, Kubernetes);
• Effective problem-solving and analytical skills, coupled with excellent communication and collaboration abilities;
• Strong communication and teamwork abilities;
• Understanding of data security and privacy best practices;
• Strong mathematical, statistical, and algorithmic skills.

Nice to have:

• Certification in Cloud platforms, or related areas;
• Experience with search engine Apache Lucene, Webservice Rest API;
• Familiarity with Veeva CRM, Reltio, SAP, and/or Palantir Foundry;
• Knowledge of pharmaceutical industry regulations, such as data privacy laws, is advantageous;
• Previous experience working with JavaScript and TypeScript.

About the company:

Softermii (https://www.softermii.com/) is an outsourcing/outstaffing company with more than 11 years of experience in web and mobile application development with a team of more than 120 specialists from 6 countries.

We have withstood multiple challenges, such as COVID-19 pandemic and war aggression against Ukraine, we have secured sustainable development processes, saved all our projects and jobs. Even more – we’re constantly growing.     

Every day we add new project to our portfolio in the following areas of expertise:

• Healthcare
• Real estate
• Livestream E-commerce
• Fintech (WealthTech, Capital Trading)
• Real-Time Communications (RTC)

In addition, we develop 2 of our own solutions that help our customers get faster applications for video or audio calls (https://www.softermii.com/solutions/vidrtc) or an application for real estate with 3D visualization (https://www.softermii.com/solutions/apartmii)

Company’s mission:

Softermii: Succeed Without (L) imitations

We will turn any idea into a valuable product.

Our plans as a company:

We want to move from a regular outsourcing business to an ecosystem of outsourcing, education, and product development companies.

Over the years, we have arrived at a highly personalized working model with transparent workflows. This model allows us to create software products that meet our clients’ goals with precision.

We operate in an AI-assisted development environment, where engineering thinking, logical validation, and responsibility for business outcomes are more important than simply writing code.

________________________________________________________________________________________________________________________________________________________________

📲Project:

The technology platform in the field of commercial real estate, which helps the company find, evaluate and purchase "last mile" objects throughout the United States. The platform combines data, analytics, risk models and investment algorithms to accelerate and automate the decision-making process in real estate investments.

Type of cooperation: Full-time.

‼️Work schedule: 1:00РM-8:00PM CET (After the start of cooperation, it can be discussed)

Team👨‍💻: 3-4 data engineers and analytics on the client side

⚡️Your responsibilities on the project will be:

• Build and maintain SQL views, stored procedures, and transformation logic that convert raw source data into clean, reliable financial, operational, and portfolio analytics;
• Develop and maintain data warehouse objects following dimensional modeling best practices – fact tables, dimension tables, and SCD patterns;
• Work within our AWS environment – including Redshift as our core data warehouse and supporting infrastructure on S3 and Athena;
• Extend and maintain Python-based pipelines supporting data ingestion, validation, automation, and output delivery;
• Support quarterly and ad hoc reporting runs – troubleshoot issues, validate outputs, and coordinate with finance and asset management teams on discrepancies
• Maintain data lineage documentation, calculation logic, and DDL registries so the team always knows what runs, why, and how;
• Use Git for version control – branching, reviewing, and merging code changes following team standards;
• Build BI-ready views consumed by dashboards and downstream reporting tools
• Help extend our data lake infrastructure as new data products and business domains are onboarded;
• Leverage AI coding tools (such as Claude Code or similar) to accelerate development, improve code quality, and document logic more effectively.

🕹Tools we use: Git, Figma, AI-assisted dev tools (Claude Code, Etc).

🗞Our requirements to you:

• 2+ years of hands-on SQL experience – comfortable writing complex queries, CTEs, window functions, and aggregations
• Solid understanding of data warehousing concepts – fact/dimension modeling, SCD Type 1/2, ETL vs ELT.
• 2+ years of hands-on experience with a modern cloud DWH (Redshift, Snowflake, BigQuery, Databricks SQL, or similar) 
• Experience building or migrating a production project in dbt Core (the free/CLI version, not dbt Cloud)
• Familiarity with Git – branching, pull requests, merge conflicts, meaningful commit messages
• Comfort using AI coding assistants (Claude Code, GitHub Copilot, or similar) as part of a modern development workflow
• Strong attention to detail – the outputs you produce inform real business decisions
• Strong English communication skills – В2/C1 level 

🗞Nice to Have:

• Familiarity with Microsoft Fabric or the broader Microsoft data stack (Azure Data Factory, Synapse, Power BI)
• Familiarity with data management principles – data quality frameworks, data lineage tracking, and metadata management
• Familiarity with real estate finance concepts – NOI, Cap Rate, IRR, fund structures
• Experience with Yardi, MRI, or other property management / accounting systems
• Exposure to Airflow or similar orchestration tools
• Understanding of GAAP / accrual accounting basics
• Working knowledge of Python for data pipelines – file I/O, scripting, automation and validation (not required, but a strong plus)
• Experience reading or reconciling financial statements – P&L structure, GL account hierarchies, balance sheet vs income statement concepts
   

👨‍💻Who will you have the opportunity to meet during the hiring process (stages):
call, HR interview, Technical interview on the client side, Final interview

🥯What we can offer you:

• We have stable and highly-functioning processes – everyone has their own role and clear responsibilities, so decisions are made quickly and without unnecessary approvals. 
• You will have enough independence to make decisions that can affect not only the project but also the work of the company.
• We are a team of like-minded experts who create interesting products during working hours and enjoy spending free time together.
• Do you like to learn something new in your profession? We will be happy to pay 50% of the cost of courses/conferences.
• Do you want an individual development plan? We will form one especially for you + you can count on mentoring from our seniors and leaders.
• Do you have a friend who is currently looking for new job opportunities? Recommend them to us and get a bonus.
• Do you want to volunteer? We will add you to a chat, where we can get a bulletproof vest, buy a pickup truck or send children's drawings to the front.
• And we have the most empathetic HRs (who also volunteers!). So we are ready to support your well-being in various ways.

👨‍🏫A little more information that you may find useful:

- our adaptation period lasts 3 months, this period of time is enough for us to understand each other better;

- there is a performance review after each year of our collaboration where we use a skills map to track your growth;

- we really have no boundaries in the truest sense of the word – we have flexible working day is up to you.
 

Of course, we have a referral bonus system. So if you have a friend who likes our job opening, you can give us their telegram contact, and we in turn will thank you with a bonus if we start working with them!

We are seeking a skilled ML/AI Engineer to join our team and deliver cutting-edge ML/AI models in the ASR domain and legal insights more broadly. The core of this role is building, deploying, and serving ML models in production. 

A key part of this role is speech engineering — prior ASR/speech experience is not a must, but a willingness to learn and grow into this domain is essential. Experience with LLM-based solutions and agentic flows is an advantage, not a requirement. 

What you’ll do: 

• Build, deploy, and serve ML models in production — the core of the role — optimizing inference performance, latency, and efficient GPU utilization. 
• Support and extend our speech solutions, including 3rd-party ASR integrations and self-hosted ML models. 
• Evaluate and optimize key ASR/ML metrics such as WER, latency, F1 score, EER, and DER. 
• Secondary: Integrate LLMs and agentic flows into production solutions where they add value, including fine-tuning existing models. 

What you’ll bring: 

Core (required): 

• Solid background in machine/deep learning, with 4+ years of experience. 
• Strong Python skills and experience working in Linux environments. 
• Familiarity with deep learning libraries (e.g., PyTorch, TensorFlow) and training workflows. 
• Experience with MLOps pipelines and serving/deploying models in production. 
• Experience optimizing models for inference, including GPU acceleration. 
• Experience with Docker, gRPC, and serverless / micro-services architectures on cloud infrastructure (AWS/GCP/Azure). 
• Experience with real-time / streaming systems and low-latency processing (e.g. streaming pipelines, live sessions). 

Nice to have (secondary / optional): 

• Experience building and productizing agentic flows and AI-driven solutions (1+ year). 
• Familiarity with LLM / agent orchestration frameworks such as CrewAI, AWS Bedrock, Temporal, AgentCore, or LiteLLM. 
• Prior ASR / speech experience — not required; willingness to learn this domain is what matters most. 

What makes Verbit unique? 

Our team of 250 professionals builds AI-driven solutions that help the world’s leading organizations get real value from their audio and video content. We serve high-end customers across the Legal, Media and Education markets with a next-generation verbal-intelligence platform that brings AI into the core of their workflows. 

Our in-house technology combines advanced LLMs, GenAI capabilities and speech AI to power everything from legal-tech automation and real-time insights to intelligent media and learning workflows. Beyond transcription or accessibility, Verbit provides actionable intelligence: smart summaries, analytics, search, knowledge extraction, legal-deposition insights and more. 

With more than 3,000 global customers relying on Verbit—including top law firms, universities, enterprises and media organizations—we’re building the future of how speech data is processed, understood and used. 

We’re a group of: 

• Tech-savvy individuals who are always open to more growth and learning opportunities 
• Adaptable and flexible people who thrive in a fast-paced, startup environment 
• Creative minds who rethink and question how to outperform past results 
• Effective communicators who can promote and represent Verbit’s tech and brand 

About the Project

Our client is an industry pioneer, allowing individuals the freedom to purchase official state lottery tickets online via our website and mobile app. We are dedicated to creating a fun and secure way for people to play the lottery conveniently from their homes or mobile devices. We understand that building a world-class company starts with a world-class team. If you're looking to join a fast-growing tech company that values work-life balance, feedback, and growth.

The role is primarily backend-oriented.

Approximate split:

• 70% Backend / Data Engineering
  • 30% Power BI / Frontend Reporting

Required skills:

Must Have

• 5 years of experience as a BI Developer, working with ETL processes and data warehouse architecture.
• Educational Background: Bachelor’s degree in industrial engineering and management, Computer science, Information Systems, or a related field.
• Strong command of SQL, including performance tuning, optimization and complex SQL queries.
• Solid experience in ETL development using SQ. Databricks - advantage.
• Experience with cloud data platforms (e.g., Azure Data Lake, Snowflake).
• Hands-on experience building dashboards and reports in Power BI.
• Excellent understanding of data modelling concepts and business KPIs.
• Familiarity with Agile methodologies and tools like Jira.
• Open to candidates worldwide

Nice to Have

• Proficiency in Python for scripting and data manipulation.
• Knowledge of data governance and compliance best practices.

Scope of work:

• Design, develop, and maintain scalable ETL processes and data warehouse structures.
• Write and optimize complex SQL queries to ensure high performance and reliability across large datasets.
• Leverage Python and Databricks for advanced data transformation, orchestration, and automation tasks.
• Build and maintain Power BI dashboards and reports to visualize key business metrics.
• Collaborate with stakeholders to translate business requirements into scalable data models and visualizations.
• Ensure data integrity, governance, and performance optimization across BI systems.
• Participate in Agile ceremonies and use Jira to manage tasks, sprints, and deliverables.
• Contribute to best practices in BI development and data modelling.

It is revolutionizing how robots operate in factories — not through rigid programming or teaching by human demonstration, but with smart perception and AI intelligence. We are a team of 4 motivated people with +25 years of experience in industry and robotics. Our mission is to make robots smarter and more flexible, enabling batch-size-1 automation for surface treatment economically. Our technology helps factories in Europe to remain competitive with intelligent robotics.

We are now looking for a Senior Machine Learning Engineer with technical excellence and entrepreneurial drive to join us in developing the next generation of AI-driven robotic systems!

Tasks

• End-to-End ML Systems: Design, implement, and train state-of-the-art AI models for perception and control of robot arms.
• Data Pipelines & ML Ops: Collect real-world data from factory deployments to optimize model training and update models in the field.
• Simulation & Synthetic Data: Work and improve simulation-based tooling (e.g., NVIDIA Newton Physics Engine) for physical AI and scalable synthetic data generation.
• Model Development: Build ML components across perception and policy pathways, including video models, multimodal encoders, world models, and diffusion/transformer architectures.
• Systems Integration: Work with real-world, multimodal datasets (vision, force/torque, tactile) and ensure models operate reliably under real-time constraints on physical hardware.
• Evaluation & Iteration: Test models in realistic environments, analyze failures, and refine for stability, latency, and robustness.

Requirements

• Background: Master's Degree and more than 3 years of professional experience or a (almost) finished PhD in Robotics, Computer Science, or a related field.
• Deep experience: Hands-on work with reinforcement learning (RL) and imitation learning within physics simulations.
• Software Engineering: Strong proficiency in Python and ideally Rust; ability to write clean, modular, and performance-optimized code for distributed workloads using AI agents.
• Real-World Mindset: Proven track record of deploying models on physical robotic manipulators and handling noisy, temporal, or large-scale datasets.Soft Skills: Entrepreneurial drive, solution-oriented mindset, high agency and the ability to take direct responsibility in a fast-paced startup environment.

Benefits

• Impact: The unique opportunity to rethink industrial automation for batch-size-1 with cutting-edge AI to maintain European manufacturing sovereignty.
• Growth: Challenging tasks and impactful projects alongside experts in a high-growth VC-funded startup.
• Ownership: opportunity to actively shape the company's technical direction; potential shares in the company.
  
  Must have skills !!!
• Background: Master's Degree and more than 3 years of professional experience or a (almost) finished PhD in Robotics, Computer Science, or a related field.
• Deep experience: Hands-on work with reinforcement learning (RL) and imitation learning within physics simulations.
• Software Engineering: Strong proficiency in Python and ideally Rust; ability to write clean, modular, and performance-optimized code for distributed workloads using AI agents.
• Real-World Mindset: Proven track record of deploying models on physical robotic manipulators and handling noisy, temporal, or large-scale datasets.Soft Skills: Entrepreneurial drive, solution-oriented mindset, high agency and the ability to take direct responsibility in a fast-paced startup environment.