Jobs Data Engineer

We're looking for a Senior SysOps Engineer to join our friendly and professional team.

The platform is a high-traffic web service handling tens of millions of requests per day, with a data pipeline processing 50M+ user events daily that feeds both customer-facing analytics and billing. It runs on self-managed infrastructure across two datacenters, with a mix of long-lived legacy components and an active modernization program. 
 

Engagement: full-time (ideally) or part-time (20+ hours/week).
Location: UA/EU, remote.
 

Required Skills:

• 5+ years of experience as a SysOps Engineer / Infrastructure Engineer (or similar role).
• Strong expertise with OS: FreeBSD (preferred), Linux (Debian, Ubuntu), Jail, Docker, and ZFS optimization.
• Database experience: MariaDB/MySQL with master-master, master-slave replication, MyISAM, InnoDB, GTID.
• Experience with Redis & Sentinel: setup, replication, and failover strategies.
• Experience with Web-servers: Caddy, Lighttpd, Nginx.
• Knowledge of ElasticSearch high-load clusters (replication, scaling, performance tuning).
• Experience with Cloudflare (DNS management, caching, security configurations).
• Experience with Supervisord, Beanstalkd, RabbitMQ.
• Networking & security expertise: Strong understanding of network protocols, packet filtering (iptables, ipfw, pf).
• Proficiency in scripting & automation: Bash, Python, PHP (or similar).
• Experience with PowerDNS and DNS management strategies.
• English - B2 and higher (for effective communication with stakeholders).

Responsibilities:

• Maintain, manage, and improve the existing infrastructure and platform.
• Troubleshoot and resolve issues with critical platform components (ElasticSearch, Redis, FreeBSD, database replication, etc.).
• Maintain and update incident runbooks for the on-call teams.
• Automate system tasks and reduce manual repetitive work.
• Document and optimize deployment processes.
• Work on high-availability solutions for branded domains, database failover, and scaling improvements.

Will Be a Plus:

• Experience with high-load multi-source database replication, Orchestrator, and ProxySQL.
• Knowledge of high-load infrastructure solutions and best practices.

What we offer:
 

• Official B2B contract with a Canadian Company;
• Compensation for medical insurance (for our employees based in UA);
• Flexible working hours (start at 8.00-11.00 o'clock);
• Weekends according to the Ukrainian/Local calendar;
• Engaging projects with opportunities for career growth;
• Certifications, Udemy courses, Claude;
• Corporate events, team-building activities,
• Gifts and recognition from the company;
• A friendly, open, and supportive team culture without excessive bureaucracy.

Responsibilities

• Design and improve perception algorithms for autonomous driving applications.
• Develop solutions for 3D object detection, semantic segmentation, object tracking, and drivable area estimation.
• Create and optimize automated data labeling pipelines to improve dataset quality while reducing manual annotation efforts.
• Implement reliable multi-object tracking algorithms operating in 3D environments.
• Train, evaluate, and optimize large-scale deep learning models using extensive datasets and high-performance computing infrastructure.
• Validate developed solutions through testing in real autonomous vehicle platforms.

Requirements

• Master's or PhD degree in Computer Science, Robotics, Artificial Intelligence, or a related technical field (or equivalent industry experience).
• Strong practical experience with deep learning for at least one sensor type, such as cameras, LiDAR, or radar.
• Experience working with modern neural network architectures, including Transformer-based models.
• Solid programming skills in Python and C++.
• Ability to work collaboratively in a fast-paced engineering environment with a strong willingness to learn.

Nice to Have

• Previous experience in autonomous driving, ADAS, robotics, or computer vision.
• Familiarity with deployment and optimization frameworks such as TensorRT, ONNX Runtime, or LibTorch.
• Experience contributing to medium or large-scale software systems.
• Understanding of performance optimization for machine learning inference.

What We Offer

• Opportunity to work on advanced AI technologies shaping the future of mobility.
• Highly technical environment with minimal bureaucracy and fast decision-making.
• Flexible working hours and hybrid work options.
• Competitive compensation package.
• Long-term growth opportunities within an innovative engineering team.
• Equity or long-term incentive program.

Are you passionate about building reliable, scalable, and highly available production systems? Do you enjoy solving complex engineering challenges through automation, observability, and software engineering?
Optimove is looking for a Senior Site Reliability Engineer (SRE) to join our global SRE organization. In this role, you'll partner with engineering teams globally to improve the reliability, scalability, and operational excellence of our cloud platform.
As a Senior SRE, you'll lead engineering-driven reliability initiatives by building automation, improving deployment processes, advancing observability, and driving operational excellence across our production environment.

Responsibilities
 

• Reliability Engineering – Design and implement solutions that improve the reliability, availability, and scalability of our production platform while proactively identifying and eliminating operational risks.
• Automation & Platform Engineering – Build internal tools and automation that eliminate manual operational work, improve engineering productivity, and streamline production workflows.
• Observability – Improve monitoring, alerting, dashboards, and production visibility while driving initiatives that reduce alert fatigue, improve incident detection, and strengthen operational insights.
• Production Rollouts – Design, improve, and support production deployment processes using modern release strategies such as Canary, Blue/Green, and Feature Flags to ensure safe and reliable releases.
• Production Reliability & Incident Response – Lead the investigation and resolution of critical production incidents, perform root cause analysis, and implement long-term preventive improvements that improve platform resilience and reduce recurring issues.
• On-Call & Operational Excellence – Participate in the team's on-call rotation, ensuring reliable production operations. Respond to critical incidents, collaborate with engineering teams during service disruptions, and drive engineering improvements, automation, and operational best practices that reduce operational toil and prevent future incidents.
• Cloud & Infrastructure – Design, maintain, and improve our Kubernetes-based cloud platform, CI/CD pipelines, and production infrastructure running on GCP and AWS.
• Engineering Partnership – Collaborate closely with Software Engineers, DevOps, DBAs, and Product teams to improve reliability across the software development lifecycle and promote SRE best practices.
   

Requirements
 

• 5+ years of experience in Site Reliability Engineering, Platform Engineering, DevOps, or Infrastructure Engineering.
• Hands-on experience operating Kubernetes in production environments.
• Strong experience working with public cloud platforms (GCP or AWS).
• Strong programming and scripting skills (Python preferred; Go or Bash are a plus).
• Experience designing and building automation and internal engineering tools.
• Experience working with CI/CD pipelines and modern deployment methodologies.
• Hands-on experience with observability platforms such as Datadog, Prometheus, or Grafana.
• Strong understanding of Linux, networking, distributed systems, and cloud-native architectures.
• Excellent troubleshooting, debugging, and root cause analysis skills.
• Strong communication skills and experience collaborating with globally distributed engineering teams.
   

Advantages
 

• Experience with Infrastructure as Code (Terraform, Ansible, etc.).
• Experience with messaging and distributed technologies such as Kafka, Pub/Sub, or Redis.
• Experience supporting modern deployment strategies such as Canary, Blue/Green, or Feature Flags.
• Familiarity with OpenTelemetry and modern observability tooling.
• Understanding of Site Reliability Engineering principles, including SLIs, SLOs, and error budgets.
• Experience working in large-scale SaaS production environments.
• Relevant cloud or Kubernetes certifications (GCP, AWS, CKA, CKAD).
  
  Why Join Us?
  Join a team where Site Reliability Engineering is treated as an engineering discipline—not just an operations function. You'll work on large-scale cloud infrastructure serving enterprise customers while building automation, improving observability, and enabling engineering teams to deliver software safely and reliably.
• You'll collaborate with a global SRE organization using modern cloud-native technologies, Kubernetes, distributed systems, and large-scale SaaS workloads. You'll have the opportunity to lead impactful reliability initiatives, influence engineering best practices, and solve complex production challenges that directly improve the experience of both customers and engineering teams.

We are seeking a highly skilled and experienced Senior DevOps Engineer to join our dynamic team. The ideal candidate will have a strong background in Kubernetes, Terraform, ArgoCD, Continuous Integration (CI), Continuous Deployment (CD), developer toolsets, and Software Development Life Cycle (SDLC) best practices. This role requires a deep understanding of modern DevOps tools and practices, as well as a commitment to fostering a responsive, communicative, and collaborative environment. This role requires on-call duties.

Key Responsibilities:

• Develop and manage large scale production Kubernetes clusters in a cloud environment (AWS preferred).
• Deploy, manage, and monitor containerized applications using Kubernetes.
• Develop and manage infrastructure as code using Terraform.
• Design, implement, and maintain CI/CD pipelines to ensure efficient and reliable software delivery.
• Manage and optimize cloud infrastructure in AWS to support scalable and secure applications.
• Administer and optimize source code repositories and workflows in GitHub.
• Collaborate with development teams to enhance developer toolsets and streamline SDLC processes.
• Troubleshoot and resolve infrastructure and application issues.
• Implement best practices for security, reliability, and performance.
• Provide mentorship and technical guidance to junior engineers.
• Communicate effectively with cross-functional teams to understand requirements and deliver solutions.

Qualifications:

• Bachelor’s degree in Computer Science, Engineering, or a related field, or equivalent experience.
• 5+ years of experience in a platform engineering, DevOps or similar role.
• Extensive experience with Terraform for infrastructure as code.
• Experience with self-hosted Kubernetes clusters for container orchestration and ArgoCD.
• Proficiency in Golang or Python(or any other languages) for scripting and automation.
• Hands-on experience with GitHub for version control and collaboration. 
• In-depth experience with AWS cloud services.
• Excellent problem-solving skills and the ability to work under pressure.
• Exceptional communication skills, both verbal and written.
• Proven ability to work collaboratively in a team environment.
• Strong organizational skills and attention to detail.
• In depth networking knowledge.
• Hands-on experience with AI-assisted development tools, such as GitHub Copilot and Claude Code.

Preferred Qualifications:

• Experience with Github runners and other CI/CD tools and platforms.
• Knowledge of security best practices in cloud environments.
• Experience with observability tools such as Prometheus, and ELK and Grafana stacks- nice to have .
• Certification in AWS or Kubernetes and experience with Backstage is a plus.
• Experience with kOps is a plus.
• Knowledge of Cilium CNI is a plus.
• Experience with Jenkins is a plus.

We offer*:

• Flexible working format - remote, office-based or flexible
• A competitive salary and good compensation package
• Personalized career growth
• Professional development tools (mentorship program, tech talks and trainings, centers of excellence, and more)
• Active tech communities with regular knowledge sharing
• Education reimbursement
• Memorable anniversary presents
• Corporate events and team buildings
• Other location-specific benefits

*not applicable for freelancers

Cyber Harbor is a fast-growing Ukraine-based company founded by engineers and researchers who helped defend critical infrastructure during the war. Our work is shaped by real-world experience, and we build AI-powered systems designed to handle complex, high-stakes environments.

We are currently expanding and looking for a strong Data Engineer to help us design and build scalable pipelines for processing large volumes of both structured and unstructured data. These pipelines power comprehensive, interactive knowledge bases used in real-world operations. 

In this role, you will work closely with the core data processing workflows and collaborate daily with software engineers, AI/ML engineers, DevOps specialists, and the QA team. Because much of the work happens across different parts of the system, strong communication and the ability to collaborate effectively with other teams are essential.

What You Will Do

- Design and build ETL/ELT pipelines for large volumes of unstructured data using orchestrators such as Temporal, Prefect, Celery, or Airflow, along with distributed processing engines like Ray and Spark.
- Automate AI-related tasks including text extraction, summarization, OCR, named entity recognition, and embedding generation using various self-hosted models, including some developed in-house.
- Design data schemas and manage storage across multiple systems, including relational databases (PostgreSQL), NoSQL databases (Elasticsearch, Mongodb), vector search engines (Qdrant, Milvus), and graph databases (Neo4j).
- Set up and maintain messaging queues for distributed data processing using tools such as Kafka, RabbitMQ.
- Develop custom Python tools and logic to ensure high throughput, reliability, and fault tolerance in data pipelines.
- Containerize services with Docker and orchestrate deployments using Kubernetes, including on-premise environments.
- Build and maintain CI/CD pipelines to support reliable development and deployment workflows.
- Monitor infrastructure and pipeline health using Prometheus and Grafana, and manage centralized logging with the ELK Stack.

What You Need to Join Us

- Strong hands-on experience with SELF-HOSTED data engineering tools.
- Solid Python skills and the ability to build reliable, production-grade data workflows.
- Experience automating workflows that involve different AI models, including self-hosted ones.
- Good understanding of how modern search and RAG systems are designed and operate.
- Familiarity with messaging systems such as Apache Kafka, RabbitMQ.
- Strong understanding of relational databases (PostgreSQL) as well as other data systems such as Elasticsearch, Qdrant/Milvus, and Neo4j.
- Practical experience with Docker, Kubernetes, and CI/CD tools (GitHub Actions or GitLab CI).
- Familiarity with monitoring and observability tools such as Prometheus, Grafana, and the ELK Stack.
- Experience working with on-premise infrastructure environments.

Why Join Us

- Make a Real Impact: Our systems have already been validated in real-world, nation-state level operations.
- Right Place, Right Time: Work at the intersection of AI, large-scale data processing, and cybersecurity.
- Military Deferment: Available for full-time employees.
- Flexible Schedule: Remote-friendly environment focused on results rather than rigid hours.

–––––––––––––––––––––––––––––––Рідною–––––––––––––––––––––––––––––––

Cyber Harbor - українська компанія, заснована інженерами та дослідниками, які брали участь у захисті критичної інфраструктури під час війни. Ми спираємося на реальний практичний досвід і створюємо AI-powered системи для складних середовищ, де помилка може мати високу ціну.

Зараз ми розширюємо команду та шукаємо сильного Data Engineer, який допоможе нам проєктувати й розвивати масштабовані пайплайни для обробки великих обсягів структурованих і неструктурованих даних. Саме ці пайплайни є основою комплексних інтерактивних баз знань, що використовуються в реальних операційних процесах.

У цій ролі ви працюватимете з ключовими процесами обробки даних та щодня взаємодіятимете з software engineers, AI/ML engineers, DevOps specialists і QA командою. Значна частина задач лежить на стику кількох компонентів системи, тому для нас важливі сильні комунікаційні навички та вміння ефективно працювати з різними командами.

Що ви будете робити

• Проєктувати та розробляти ETL/ELT-пайплайни для обробки великих обсягів неструктурованих даних із використанням інструментів оркестрації, таких як Temporal, Prefect, Celery або Airflow, а також систем розподіленої обробки, зокрема Ray і Spark.
• Автоматизувати AI-related задачі, зокрема text extraction, summarization, OCR, named entity recognition та генерацію embeddings, використовуючи різні self-hosted моделі, у тому числі частково розроблені in-house.
• Проєктувати схеми даних і будувати логіку зберігання в кількох системах одночасно: реляційних базах даних (PostgreSQL), NoSQL-рішеннях (Elasticsearch, MongoDB), векторних пошукових системах (Qdrant, Milvus) і графових базах даних (Neo4j).
• Налаштовувати та підтримувати черги повідомлень для розподіленої обробки даних за допомогою таких інструментів, як Kafka та RabbitMQ.
• Розробляти кастомні Python-інструменти й внутрішню логіку, що забезпечують високу пропускну здатність, надійність і відмовостійкість data pipelines.
• Контейнеризувати сервіси за допомогою Docker та керувати розгортанням через Kubernetes, зокрема в on-premise середовищах.
• Будувати й підтримувати CI/CD pipelines для стабільних і передбачуваних процесів розробки та деплою.
• Відстежувати стан інфраструктури та пайплайнів за допомогою Prometheus і Grafana, а також підтримувати централізоване логування через ELK Stack.
   

Що нам важливо

• Сильний практичний досвід роботи з self-hosted інструментами для data engineering.
• Впевнене володіння Python і вміння будувати надійні data workflows production-рівня.
• Досвід автоматизації процесів, що включають роботу з різними AI-моделями, зокрема self-hosted.
• Розуміння принципів побудови та роботи сучасних search і RAG systems.
• Практичний досвід роботи з системами обміну повідомленнями, зокрема Apache Kafka та RabbitMQ.
• Сильне розуміння реляційних баз даних (PostgreSQL), а також інших систем зберігання й пошуку даних, зокрема Elasticsearch, Qdrant/Milvus і Neo4j.
• Практичний досвід роботи з Docker, Kubernetes і CI/CD-інструментами (GitHub Actions або GitLab CI).
• Знайомство з інструментами моніторингу та observability, такими як Prometheus, Grafana й ELK Stack.
• Досвід роботи з on-premise інфраструктурою.

Чому варто приєднатися

• Реальний вплив - наші системи вже використовуються в реальних операційних умовах.
• Сильний технічний контекст - ви працюватимете на перетині AI, обробки великих даних і кібербезпеки.
• Бронювання - доступне для full-time працівників.
• Гнучкий формат роботи - remote-friendly середовище з фокусом на результат, а не на формальний графік.

Inforce is a Software Development Company that provides a full range of top-quality IT services. Our mission is to develop first-class applications and Websites to provide our clients with the best solutions for maximizing their profits and converting their ideas into reality.
 

Why This Role Excites You

• Work on real-world data pipelines and data solutions.
• Build reliable data flows for international projects.
• Work with a modern data stack and contribute to technical decisions.
   

Key Responsibilities

• Build and maintain ETL/ELT pipelines in Python.
• Write and optimize SQL queries for data processing and reporting.
• Integrate data from ERP/CRM, REST APIs and client databases into DWH.
• Implement data quality checks and prepare data marts for BI dashboards.
• Work with Airflow/Dagster or similar orchestration tools.
• Document solutions and collaborate with Backend, ERP and Analytics teams.
   

What We're Looking For

• Strong Python and SQL skills.
• Solid understanding of ETL/ELT, DWH and data engineering principles.
• Experience with Git and working in a shared codebase.
• Ability to investigate problems independently, make and explain technical decisions.
• Good communication skills and a collaborative mindset.
• Comfortable working independently while keeping the team updated.
• English: Upper-Intermediate (B2) or higher.
   

Nice to Have

• Docker, Airflow/dbt.
• PostgreSQL, ClickHouse or BigQuery.
• Bash/Linux and basic cloud knowledge.
• Experience with BI tools.
• Experience in commercial or internship Data/Backend projects.
   

Why Join Us

• Commercial projects with international clients.
• Remote-friendly work environment.
• The company covers 50% of the cost of professional courses you need
• Paid sick leave and vacation days
• Corporate English classes

OMNICORE is an international product and service company specializing in e-commerce. We create, develop, and manage online businesses for leading retail players in the fashion industry, with a focus on clothing, footwear, and accessories.

We combine consulting, design, web development, content production, marketing, customer service, and operational management to deliver comprehensive and effective omnichannel e-commerce solutions.
For over nine years, we have been helping our partners grow their online businesses. Our clients include  ua.puma.com, adidas.ua, adidas.kz,  adidas.kg, the marketplaces md-fashion.ua, ultra-shop.com, frgroup.kz, frgroup.uz, and others.

Since 2022, the company has expanded its operations to the Republic of Kazakhstan. We provide a full range of services, including eCommerce-as-a-Service (EaaS) and 3PL solutions, becoming a regional fulfillment hub.

We are looking for a DevOps Engineer to strengthen our team.

Requirements:

• At least 3 years of experience as a DevOps Engineer / SRE;
• English – strong Intermediate or higher;
• Experience with HA and HL would be a plus;
• OS: Linux (Ubuntu, Debian, Alpine);
• Application support: PHP (required), JS;
• Infrastructure: Ansible, Terraform, Docker;
• Cloud providers: Hetzner Cloud (strongly required!), GCP;
• Databases:
  • MySQL (standalone, master-slave, Percona cluster)
  • PostgreSQL (standalone, master-slave, Patroni cluster)
  • MongoDB (standalone, replicaset)
  • Elasticsearch (standalone, cluster)
  • Redis (standalone, Sentinel, cluster)
• HTTP/Proxy/LB: NGINX, HAProxy, Varnish, Cloud-managed load balancers;
• CI/CD: GitOps, Bitbucket Pipelines, SonarQube, Dependency-Track;
• Programming: Python, Bash scripting (PHP is a plus);
• Observability: ELK / OpenSearch stack, Prometheus / Grafana stack, Alerts management;
• InfoSec/Security: DevSecOps principles, Vault, Teleport.

Working conditions:

• Full-time, remote format;
• A young team with a great sense of humor;
• Paid vacation (24 calendar days) and sick leave;
• Personal learning & development budget;
• Career growth opportunities;
• Up to 20% discounts on our partners’ products;
• 50% discount on corporate English learning with Preply;
• Payment in UAH, not tied to currency fluctuations;
• Work schedule: Mon–Fri, 10:00 – 19:00. We operate in the Eastern European Time Zone (EET).

OMNICORE is a place where you can become part of a team of professionals, unlock your potential, and grow within dynamic e-commerce projects for international fashion brands.

 Apply now!

Description
The Client is one of the major banks in the UK. The project focuses on migrating and modernizing data assets from legacy platforms to a Databricks-based data environment. The team works closely with the client to transform existing Teradata scripts into dbt models, implement scalable data pipelines and support data migration using internal tools and cloud services.

Requirements
Hands-on experience with dbt (data build tool) for data transformation and pipeline development.
Strong Python programming skills for data processing and scripting.
Practical experience working with Databricks in a data engineering or analytics environment.
Experience with Cloud Platforms (AWS or Azure).
Experience working with SQL-based systems, including migration from legacy platforms such as Teradata.
Understanding of data migration, ETL/ELT pipelines, and data transformation frameworks.
Ability to work collaboratively with technical leads and external stakeholders.
Good written and verbal English communication skills.
 

Job responsibilities
Develop, maintain, and execute dbt and Python scripts to migrate database tables and views and integrate them with Databricks.
Participate in data migration activities, ensuring reliable and efficient transformation of legacy data assets.
Work closely with Barclays stakeholders to operate and support DIH and other internal data migration tools.
Assist in the design and implementation of data transformation pipelines within the Databricks ecosystem.
Validate migrated datasets and ensure data quality, consistency, and completeness throughout the migration process.
Troubleshoot and resolve issues related to data transformation, pipelines, and integrations.
Contribute to documentation related to data migration processes, dbt models, and pipeline architecture.
Collaborate with cross-functional teams including data engineers, architects, and business stakeholders to deliver migration tasks.

Job Description
Implement the platform capabilities that enable disparate data sources to be combined, virtualized, standardized, and exposed through a consistent access model without requiring extensive physical consolidation.

Experience with technologies and platforms such as

• Microsoft Fabric, OneLake, Synapse, Azure Data Lake, Purview
• BigQuery, BigLake, Dataplex
• Athena, Redshift Spectrum, Lake Formation, Glue
• Data virtualization, federated query, semantic layer, or data fabric platforms
• Strong Python

Job Responsibilities

• Implementing data virtualization and federation capabilities
• Building federated query services
• Developing semantic and abstraction layers
• Creating reusable APIs and access services
• Performance tuning, scalability, reliability, and operational support
• Contributing to platform design and technology decisions through hands-on expertise

Department/Project Description
Build the core data engineering capability that enables WPP Open applications, AI agents, analytics products, and business workflows to securely discover, access, combine, govern, and activate data across enterprise systems, client environments, media platforms, and third-party providers.

We are seeking four senior engineering specialists who will be responsible for implementation and delivery of key platform capabilities. While architecture leadership is provided by the platform architecture team, these hires are expected to bring deep expertise, contribute to solution design, challenge assumptions, and guide implementation decisions based on industry experience.

Join an exciting journey to create a cutting-edge Consumer Data Lake for a leading global organization based in Europe. This platform will unify, process, and leverage consumer data from various systems, unlocking advanced analytics, insights, and personalization opportunities. As a Senior Data Engineer, you will play a pivotal role in shaping and implementing the platform's architecture, focusing on hands-on technical execution and collaboration with cross-functional teams.

Your work will transform consumer data into actionable insights and personalization on a global scale. Using advanced tools to tackle complex challenges, you’ll innovate within a collaborative environment alongside skilled architects, engineers, and leaders.

Key Responsibilities:

• Hands-On Development: Build, maintain, and optimize data pipelines for ingestion, transformation, and activation.
• Create and implement scalable solutions to handle diverse data sources and high volumes of information
• Data Modeling & Warehousing: Design and maintain efficient data models and schemas for a cloud-based data platform.
• Develop pipelines to ensure data accuracy, integrity, and accessibility for downstream analytics.
• Collaboration: Partner with Solution Architects to translate high-level designs into detailed implementation plans.
• Work closely with Technical Product Owners to align data solutions with business needs.
• Collaborate with global teams to integrate data from diverse platforms, ensuring scalability, security, and accuracy.
• Platform Development: Enable data readiness for advanced analytics, reporting, and segmentation.
• Implement robust frameworks to monitor data quality, accuracy, and performance.
• Testing & Quality Assurance: Implement robust security measures to protect sensitive consumer data at every stage of the pipeline
• Ensure compliance with data privacy regulations (e.g., GDPR, CCPA ..) and internal policies.
• Monitor and address potential vulnerabilities, ensuring the platform adheres to security best practices.

Requirements:

• Over 4+ years of experience showcasing technical expertise and critical thinking in data engineering.
• Hands-on experience with DBT and strong Python programming skills.
• Proficiency in Snowflake and expertise in data modeling are essential.
• Demonstrated experience in building consumer data lakes and developing consumer analytics capabilities is required.
• In-depth understanding of privacy and security engineering within Snowflake, including concepts like RBAC, dynamic/tag-based data masking, row-level security/access policies, and secure views.
• Ability to design, implement, and promote advanced solution patterns and standards for solving complex challenges.
• Familiarity with multiple cloud platforms (Azure or GCP preferred, with a focus on Azure).
• Practical experience with Big Data batch and streaming tools.
• Competence in SQL, NoSQL, relational database design (SAP HANA experience is a bonus), and efficient methods for data retrieval and preparation at scale.
• Proven ability to collect and process raw data at scale, including scripting, web scraping, API integration, and SQL querying.
• Experience working in global environments and collaborating with virtual teams.
• A Bachelor’s or Master’s degree in Data Science, Computer Science, Economics, or a related discipline.

Description

The Client is one of the major banks in the UK. This project is a strategic initiative to migrate legacy data infrastructure, including approximately 500 BTEQ scripts and 1,100 tables, to a modern cloud environment. GlobalLogic is establishing a dedicated Features Team to partner with the Client’s engineering leadership. Our team will focus on replatforming business logic, updating data pipelines and repointing SAS dependencies. Core technical requirements for the role include cloud stack knowledge, Python, SQL and DBT. We’re interested in problem solvers with the right mindset and can-do attitude to shape a strong team and build a a long-term collaborative partnership.

Requirements

To be successful in this role, you will need the following:

• Strong hands-on data engineering experience delivering production-grade solutions.
• Ability to design, implement and optimise complex data pipelines independently.
• Strong SQL and programming (Python preferred); capable of building reusable and scalable code.
• Experience with modern orchestration tools (e.g. Airflow, Step Functions, etc.).
• Hands-on experience on any cloud platform (AWS preferred or equivalent).
• Ability to proactively analyse existing processes, suggest improvements, and drive technical solutions end-to-end.
• Comfortable engaging with stakeholders, understanding business requirements, and translating them into technical design.
• Good written and verbal English communication skills.

Good to have:

• Experience with dbt Core for data transformations.
• Exposure to migrating legacy data platforms (Teradata, Hadoop, SAS) into modern cloud architectures.
• Familiarity with Databricks or similar platforms for advanced analytics.
• Understanding of data security, regulatory, and risk management principles in banking.

Job responsibilities

• Develop, maintain, and execute dbt and Python scripts to migrate database tables and views and integrate them with Databricks.
• Participate in data migration activities, ensuring reliable and efficient transformation of legacy data assets.
• Work closely with Barclays stakeholders to operate and support DIH and other internal data migration tools.
• Assist in the design and implementation of data transformation pipelines within the Databricks ecosystem.
• Validate migrated datasets and ensure data quality, consistency, and completeness throughout the migration process.
• Troubleshoot and resolve issues related to data transformation, pipelines, and integrations.
• Contribute to documentation related to data migration processes, dbt models, and pipeline architecture.
• Collaborate with cross-functional teams including data engineers, architects, and business stakeholders to deliver migration tasks.

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 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. 

The Client is the UK’s leading fee-free mortgage broker. They are seeking experienced Data Engineer to join client’s data team. This role focuses heavily on core data engineering, architecture, and pipeline delivery within established frameworks rather than the presentation layer. The ideal candidate will be responsible for designing, building and optimizing scalable ingestion-to-consumption patterns and modern data warehousing principles.

Requirements

Must-Have Skills:

• Python / PySpark for Data Engineering: Strong experience writing PySpark notebooks in Fabric, building data transformation/cleansing logic, and notebook-based pipeline development.
• Medallion Architecture: Proven expertise in designing and implementing Bronze/Silver/Gold layered ingestion-to-consumption patterns, incremental loading, and transformation logic.
• Dimensional Modelling: Strong knowledge of Kimball-style fact/dimension design, SCD (Slowly Changing Dimension) handling, and Gold-layer conformance.
• T-SQL & DDL Proficiency: Expertise in warehouse schema design, writing stored procedures, and performance tuning.
• Pipeline Development & Orchestration: Practical experience with Dataflows Gen2, Fabric pipelines, notebook orchestration, scheduling, and dependency management.
• Good written and verbal English communication skills.

Nice-to-Have Skills:

• Governance & Security Implementation: Exposure to Microsoft Purview integration, Entra ID mapping, and workspace/access control architecture.
• Power BI & Semantic Modelling: Basic knowledge of DAX, semantic model design, and row/column/object-level security (RLS/CLS/OLS).

Job responsibilities

• Data Pipeline & Framework Development: Design, build, and orchestrate robust end-to-end data pipelines using Dataflows Gen2, PySpark notebooks and native orchestration tools.
• Architecture & Storage Layer Management: Implement and maintain Medallion Architecture (Bronze, Silver, Gold layers), ensuring proper incremental loading strategies and layer-specific transformation logic.
• Data Warehousing & Dimensional Modelling: Build Kimball-style fact and dimension models, manage Slowly Changing Dimensions (SCDs), and ensure Gold-layer data conformance for analytics consumption.
• Data Transformation & Optimization: Write clean, modular Python/PySpark code and T-SQL/DDL logic for data cleansing, schema design, stored procedures, and query performance tuning.

Summary

Expert Data Engineer with 3+ years in Power BI Pro, Azure SQL, and complex ETL pipeline development. Skilled in DAX, Power Query, and Azure Synapse notebooks for advanced data analytics and performance tuning. Proven expertise in optimizing Azure Data Lake Storage with Parquet file techniques and managing large-scale backend data processing. Experienced in Agile methodologies, data warehousing, and software engineering best practices, delivering high-quality solutions in cross-functional teams.

Role Overview:
 

The Senior/Expert Data Engineer position is a contract, long-term engagement based in Ukraine, focused on delivering advanced data engineering solutions using Databricks, Power BI, and SQL. The role is embedded within a global consulting and auditing firm supported by a custom product engineering company. The candidate will join a cross-functional development team responsible for engineering innovative data experiences and solving complex business challenges for multinational organizations and scaling startups.

Key Responsibilities:

• Design, develop, and deploy Power BI solutions, including dashboards and reports that provide critical business insights.
• Create and implement robust data models optimized for performance and efficient query execution.
• Optimize Power BI reports and dashboards by improving query speed and data model efficiency.
• Contribute to the design, coding, configuration, and management of data ingestion processes, supporting both near real-time and batch ETL pipelines across multiple data storage systems.
• Perform performance tuning and optimization of complex SQL and DAX queries to enhance data processing efficiency.
• Develop, execute, and maintain data processing workflows using Azure Synapse notebooks.
• Manage and optimize data storage solutions within Azure Data Lake Storage (ADLS), focusing on Parquet file optimization techniques such as partitioning and compression.
• Identify platform gaps and implement improvements to enhance quality, robustness, maintainability, and speed.
• Cross-train team members on emerging technologies and continuously learn from peers to foster knowledge sharing.
• Contribute actively to the unit’s community-building activities, participate in conferences, and uphold best practices and excellence in engineering.

Projects:

The job description does not specify individual project names or dates. However, the candidate’s contributions span multiple projects involving the following contexts and responsibilities:

• Power BI Solution Development: Serving as the lead data engineer responsible for designing and deploying Power BI dashboards and reports, performing advanced data analytics, and implementing complex DAX calculations and Power Query transformations to support business decision-making.
• ETL Pipeline Engineering: Managing and optimizing complex ETL pipelines involving data ingestion, batch processing, and near real-time data flows across diverse data storages, utilizing Azure Data Factory and Azure Synapse Analytics.
• Data Storage Optimization: Overseeing data storage management in Azure Data Lake Storage, applying advanced Parquet file optimization techniques such as partitioning and compression to improve data retrieval and storage efficiency.
• SQL and DAX Performance Tuning: Leading efforts to optimize complicated SQL queries and DAX formulas to enhance report and dashboard performance.
• Azure Synapse Notebook Development: Developing and maintaining data processing workflows within Azure Synapse notebooks to support large-scale backend data processing and analysis systems.

Technologies, Tools, and Methodologies Used:

• Databricks
• Power BI Pro (Desktop and Service)
• DAX (Data Analysis Expressions)
• Power Query
• SQL (Azure SQL Database, Microsoft SQL Server)
• Azure Data Lake Storage (ADLS)
• Parquet file format with optimization techniques (partitioning, compression)
• Azure Synapse Analytics and Notebooks
• Azure Data Factory
• ETL and data integration processes
• Agile software development methodologies, including SCRUM

• Software engineering best practices: coding standards, code reviews, source control, build processes, testing, and operations

   

Additional Contributions and Skills:

• Strong problem-solving and analytical skills with meticulous attention to detail.
• Excellent communication skills, capable of presenting complex data clearly and concisely to stakeholders at various organizational levels.
• Experience collaborating within cross-functional teams and contributing to community-building and knowledge sharing.
• Demonstrated ability to learn new technologies quickly and independently.
• Proven track record of delivering high-quality software on large, complex, cross-functional projects.