Jobs Data Engineer

We are looking for a Senior DevOps Engineer with strong AWS, Terraform, Kubernetes, database, and infrastructure security experience to work with our fintech client.

The engineer should be able to independently own infrastructure projects, make technical decisions, communicate directly with client teams, and support the professional growth of other team members.

This is a hourly contractor role

Responsibilities

• Own infrastructure projects from technical design through implementation and production rollout.
• Design, automate, and maintain AWS infrastructure using Terraform.
• Develop and improve CI/CD pipelines.
• Maintain development, staging, and production environments.
• Operate, upgrade, and troubleshoot Kubernetes clusters, primarily AWS EKS.
• Maintain and troubleshoot database infrastructure, backups, replication, performance, and high-availability configurations.
• Implement infrastructure security best practices, access controls, secrets management, vulnerability monitoring, and security remediation.
• Implement and improve monitoring, logging, alerting, and observability.
• Participate in production incident response, root cause analysis, and preventive improvements.
• Review infrastructure changes and provide technical guidance to other engineers.
• Create and maintain clear technical and operational documentation.
• Communicate infrastructure changes, risks, incidents, and recommendations to client teams.

Requirements

• 7+ years of professional experience in DevOps, SRE, Platform Engineering, or a similar role.
• Strong hands-on experience with production AWS environments.
• Strong experience with Terraform and infrastructure-as-code practices.
• Production experience with Docker and Kubernetes.
• Experience managing and troubleshooting AWS EKS clusters.
• Experience building and maintaining CI/CD pipelines using GitHub Actions, Jenkins
• Strong Linux administration and troubleshooting skills.
• Scripting experience with Bash or Python.
• Practical experience with relational and NoSQL databases, including services such as PostgreSQL, MySQL, RDS, Aurora, MongoDB, or Redis.
• Understanding of database backups, replication, failover, migrations, performance monitoring, and high availability.
• Strong understanding of infrastructure and cloud security principles.
• Experience with AWS IAM, secrets management, encryption, network security, vulnerability remediation, and least-privilege access.
• Experience with monitoring and observability tools such as Prometheus, Grafana, CloudWatch, OpenTelemetry, or similar.
• Strong networking knowledge, including VPC, DNS, HTTP/HTTPS, SSL/TLS, TCP/IP, load balancers, firewalls, and VPNs.
• Experience with Git-based development and infrastructure change workflows.
• Understanding of SDLC, release management, incident management, and production change management.
• Ability to independently plan, own, and deliver technical projects.
• Experience reviewing work, mentoring engineers, and helping other team members grow.
• Written and verbal English communication skills, as the role involves regular collaboration with development teams.

Nice to Have

• AWS certifications such as AWS Certified Solutions Architect, DevOps Engineer, or Security Specialty.
• Kubernetes certifications such as CKA, CKAD, or CKS.
• Terraform Associate certification.
• Experience working in fintech or other regulated environments.
• Knowledge of PCI DSS, SOC 2, ISO 27001, GDPR, or similar security and compliance frameworks.
• Experience with Terragrunt and multi-account or multi-region AWS environments.
• Experience with AWS security services such as GuardDuty, Security Hub, WAF, Inspector, Config, and CloudTrail.

• Experience leading infrastructure migrations, disaster recovery, high-availability, or cost-optimisation projects.

   

Engagement

• Full-time contractor.
• Long-term engagement.
• Remote work.
• Direct collaboration with the client’s engineering teams.

The Defense Procurement Agency (DOT) is a national agency responsible for procuring ammunition, UAVs, military equipment, fuel, food, clothing, and other critical supplies for the Armed Forces of Ukraine and the Defense Forces.

Our mission: Strengthening Ukraine by ensuring reliable support for the Defense Forces while fostering the development of the national defense industry.

Our vision: To become the driving force behind the transformation of Ukraine's defense procurement ecosystem—not only operating the system, but continuously improving it.

We are looking for a Head of Data Governance to establish and lead the organization's enterprise Data Governance function. In this role, you will define the vision, policies, standards, and governance framework for managing data across the organization, ensuring high-quality, trusted, and well-governed data that enables informed decision-making and supports large-scale digital transformation initiatives.

Responsibilities

• Lead the design, implementation, and continuous improvement of the organization's Data Governance framework.
• Develop and maintain enterprise-wide data policies, standards, methodologies, and governance processes.
  Establish and enhance Master Data Management (MDM), Reference Data, Metadata Management, and Data Quality practices.
• Define data ownership, stewardship, governance roles, and accountability across business units.
• Develop data quality standards, monitoring processes, and governance controls.
• Collaborate with business stakeholders, analysts, architects, and engineering teams to define enterprise data requirements.
• Contribute to enterprise data models and integration requirements across corporate information systems.
• Prepare governance documentation, methodologies, standards, and best practices.
• Ensure Data Governance principles are embedded into the implementation of new enterprise systems and digital services.
• Build, lead, mentor, and develop the Data Governance team while driving collaboration across the organization.

Requirements

• Bachelor's degree in Information Technology, Applied Mathematics, Economics, Finance, or a related field.
• Proven experience in Data Governance, Data Management, Business Intelligence, Business Analysis, or related disciplines.
• Hands-on experience implementing or improving Data Governance, Master Data Management (MDM), Data Quality, or Metadata Management initiatives.
• Strong understanding of Data Governance principles, data lifecycle management, and enterprise data architecture.
• Experience developing enterprise policies, standards, governance frameworks, or methodological documentation.
• Experience collaborating with business and technology teams to define and implement enterprise data requirements.
• Understanding of enterprise platforms such as ERP, CRM, BI, Data Warehouse, or similar systems.
• Experience leading teams or coordinating cross-functional initiatives.
• Strong analytical thinking, structured problem-solving, and stakeholder management skills.
• English proficiency at Intermediate level or higher.

Nice to Have

• Experience with SQL, Power BI, or other Business Intelligence platforms.
• Experience implementing Business Glossary, Data Catalog, or Metadata Management solutions.
• Knowledge of DAMA-DMBOK, DCAM, or other Data Governance frameworks.
• Experience supporting enterprise digital transformation programs.

What We Offer

• Meaningful work that directly contributes to strengthening Ukraine's defense capabilities.
• Official employment with competitive salary and full social benefits.
• Professional development, learning opportunities, and career growth.
• Structured onboarding and dedicated mentorship.
• A collaborative, supportive, and mission-driven team.
• Modern office near the metro with reliable internet and equipped shelter.
• Opportunity to establish and scale an enterprise-wide Data Governance function within one of Ukraine's most strategically important organizations.

By joining our team, you will contribute to one of Ukraine's largest digital transformation initiatives in the defense sector and help build the future of defense procurement.

Ready to make a real impact? We'd love to hear from you. Apply today!

* By submitting your CV, you consent to the processing of your personal data in accordance with applicable legislation.

** Due to the high volume of applications, only candidates whose qualifications best match the position will be contacted.

Meet the YozmaTech

YozmaTech isn’t just another tech company – we’re a global team of go-getters, innovators, and A-players helping startups and product companies scale smarter and faster. We build dedicated development teams across 10+ countries, creating strong, long-term partnerships based on trust, transparency, and real impact. Here, every idea counts. We value people who are proactive, open-minded, and ready to grow. If you’re passionate about building meaningful products and want to join a team that feels like family – you’ll feel right at home with us.

Our client is a CX AI platform that enables enterprises to deliver intelligent, automated, and personalized customer experiences across all digital channels. Powered by advanced AI, large language models, and real-time decisioning, the client transforms customer interactions into proactive, context-aware journeys-boosting efficiency, empowering agents, and driving measurable business outcomes at enterprise scale. As a DevOps Engineer, you’ll keep our high-traffic production environments fast, reliable, and secure-and you’ll do it with modern tooling and a strong bias toward automation. We’re looking for someone who treats AI as a force multiplier: curious about new tools, quick to adopt them, and always looking for ways to use AI to eliminate toil, accelerate delivery, and improve operational quality. If you’re passionate about perfecting technology beyond your imagination and want to take part in the revolution of business automation while having a great time doing it – the client is the perfect place for you!

Key Requirements:
🔹 4+ years of experience as a DevOps/SRE/Platform engineer in a high-scale, high-traffic environment;
🔹 4+ years of experience with AWS solutions (EC2, RDS, VPC, S3, Lambda, CloudFront, IAM);
🔹 Hands-on experience with Docker and container orchestration; working knowledge of Kubernetes (EKS) and Helm;
🔹 Experience building CI/CD pipelines and GitOps flows (GitHub Actions, ArgoCD, or equivalents);
🔹 Hands-on experience with scripting languages (Bash/Python), and comfort using AI coding assistants to speed up script generation, tooling, and troubleshooting;
🔹 A demonstrated passion for learning and adopting AI tools to enable and optimize DevOps work-you actively experiment with new tools and bring them into daily practice;
🔹 Experience with both Linux and Windows-based systems, with an understanding of system performance and security;
🔹 Experience with source code management and infrastructure automation (GitHub, and IaC tools);
🔹 Experience managing and troubleshooting cloud and hybrid web environments;
🔹 Experience with database management (MySQL, Redis, Elasticsearch/OpenSearch);
🔹 English – Upper-Intermediate or higher.

Will be plus:
🔹 Experience with AIOps and using AI/ML to predict failures, automate root-cause analysis, and optimize resource allocation;
🔹 Experience with Kubernetes, CloudFormation, Terraform, and NewRelic;
🔹 Experience managing traffic and security with Cloudflare (WAF, Workers, CDN);
🔹 Experience with ELK, IIS, and Directory Services;
🔹 Familiarity with SAST/security scanning tools and shift-left security practices;
🔹 Knowledge of infrastructure as code and familiarity with DevOps cultural principles;

What you will do:
🔹 Build, maintain, and improve our CI/CD pipelines using GitHub Actions to support automated testing, linting, and security gates for daily, low-friction deployments;
🔹 Operate and evolve our GitOps workflow with ArgoCD as the source of truth for cluster state;
🔹 Manage various AWS environments across multiple accounts using Infrastructure as Code, and help optimize edge performance and security;
🔹 Run and troubleshoot Kubernetes (EKS) workloads and contribute to shared Helm charts that abstract complexity for developers while enforcing security and compliance standards;
🔹 Handle technical challenges around performance, scale, and security, and provide root-cause analysis for production incidents;
🔹 Leverage AI tools-coding assistants, AIOps, and automation-to accelerate delivery, script and tooling development, incident diagnosis, and routine operational workflows;
🔹 Continuously identify and automate away repetitive manual work, proposing improvements to reliability, observability, and developer experience;
🔹 Collaborate with the R&D team to optimize service performance, deployment, reliability, failover, and scale;
🔹 Maintain awareness of best industry practices regarding CloudOps, fast deployment, security, and monitoring tools;

Interview stages:
🔹 HR-interview;
🔹 Interview with managers;
🔹 Technical test/interview;
🔹 Final interview with engineering;
🔹 Short HR interview;
🔹 Reference Check;
🔹 Offer.

Why Join Us?

At YozmaTech, we’re self-starters who grow together. Every day, we tackle real challenges for real products – and have fun doing it. We work globally, think entrepreneurially, and support each other like family. We invest in your growth and care about your voice. With us, you’ll always know what you’re working on and why it matters.
From day one, you’ll get:
🔹 Direct access to clients and meaningful products;
🔹 Flexibility to work remotely or from our offices;
🔹 A-team colleagues and a zero-bureaucracy culture;
🔹 Opportunities to grow, lead, and make your mark.

After you apply

We’ll keep it respectful, clear, and personal from start to offer.
You’ll always know what project you’re joining – and how you can grow with us.

Everyone’s welcome

Diversity makes us better. We create a space where you can thrive as you are.

Ready to build something meaningful?

Let’s talk. Your next big adventure might just start here.

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

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: 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: 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