Jobs Data Engineer

On behalf of our Client from the USA, Mobilunity is looking for a Data Platform Engineer.

Our client develops software that supports companies working in commercial fire protection and mechanical services with managing their field operations and expanding their businesses. As a growing technology company, they value accountability, thoughtful choices, and creating a tangible impact. They bring together people who are curious, collaborative, and open to different perspectives, while giving them the independence and support to address meaningful challenges. From the start, you’ll be trusted with real responsibilities, encouraged to explore better ways of working, and given room to develop as your role and experience grow.

The position focuses on building and improving large-scale batch and streaming data pipelines with Python, SQL, and AWS services including DMS and Kinesis.

You’ll be responsible for shaping the architecture of cloud-based data platforms, developing efficient ETL/ELT processes, improving CI/CD and Infrastructure-as-Code practices, and supporting the growth of less experienced engineers. AI-assisted development tools will also be part of the engineering workflow, with a strong focus on maintaining reliability, performance, and data accuracy across the platform.

As part of the Data Platform team, you’ll work on critical batch and real-time data processing systems that support advanced analytics used by thousands of commercial contractors. The role provides full ownership of complex data solutions, from architectural decisions through implementation and ongoing optimization. You’ll also have the opportunity to introduce modern AI-assisted development approaches and help other engineers develop their technical skills in a collaborative, quality-focused environment.

About You

You take responsibility for the systems you work on and stay engaged until a problem is fully resolved. When an issue appears, you’re willing to investigate beyond your immediate area of responsibility to identify the underlying cause and make sure it is properly addressed.

You care about building reliable, maintainable solutions and continuously look for opportunities to improve system performance, scalability, and efficiency. You approach challenges proactively, focus on delivering results, and are motivated by creating solutions that provide a positive experience for customers.

Key Responsibilities:

• Take the lead in developing, testing, and maintaining scalable Python solutions for data ingestion, transformation, and processing across both batch and streaming environments.
• Create and improve data models and transformation processes that support advanced analytics and changing business intelligence requirements while maintaining strong data quality and performance.
• Develop, optimize, and monitor high-throughput ETL/ELT pipelines using AWS DMS, Kinesis, and other data integration technologies.
• Investigate data pipeline failures and performance issues, identify their underlying causes, and introduce preventative measures to improve reliability and protect data integrity.
• Support junior engineers through mentoring and establish clear documentation practices for code, data models, and engineering processes to promote knowledge sharing and consistency.

Requirements:

• Strong Data Engineering Background: Hands-on experience designing and developing data engineering solutions, performing thorough code reviews, and working with complex, large-scale ETL/ELT pipelines.
• Cloud Data Platform Expertise: Extensive practical experience with enterprise cloud data platforms such as Amazon Redshift, Google BigQuery, or Snowflake, including knowledge of their architecture and approaches to performance optimization.
• Advanced Programming Proficiency: Expert-level skills in Python and SQL (including advanced optimization techniques in MySQL, Postgres, and SQL Server), coupled with extensive experience with complex transformations and a strong command of AWS services (DMS, S3, Airflow, Kinesis, DocumentDB, CloudWatch, Kubernetes, Glue).
• CI/CD & Infrastructure as Code: Experience designing and maintaining GitHub-based version control workflows and implementing advanced CI/CD processes for data infrastructure, together with a strong understanding of Infrastructure-as-Code practices and tooling.
• AI-Assisted Engineering: Practical experience working with AI development tools such as Claude Code, GitHub Copilot, or Cursor, combined with the ability to validate, test, review, and take responsibility for AI-generated output.
• Upper-intermediate to advanced English proficiency

In return we offer:

• The friendliest community of like-minded IT-people
• Open knowledge-sharing environment – exclusive access to a rich pool of colleagues willing to share their endless insights into the broadest variety of modern technologies
• English classes in 1-to-1 & group modes with elements of gamification
• Neverending fun: sports events, tournaments, music band, multiple affinity groups

Come on board, and let’s grow together!

N-iX is looking for a BI Engineer to join one of the biggest and strongest Data Units in Ukraine.

Our client is a US-based company that provides In-flight Internet and entertainment services to aircraft across the globe, serving commercial aircrafts. At this moment we cooperate on Business Intelligence, Data Analysis  and BigData directions and look for talents who can contribute to the complex data management and analysis projects.

Requirements:

• Proven hands-on experience with Tableau, including Tableau Desktop and Tableau Server
• Proven experience migrating BI reports and dashboards from Tableau to Power BI
• Hands-on experience with Power BI, including report and dashboard development
• Strong knowledge of SQL
• Experience with DAX and Power Query
• Knowledge of SQL Server Reporting Services (SSRS), SQL Server Integration Services (SSIS) and Paginated Reports
• Experience with Airflow
• Basic knowledge of Python
• Upper-intermediate English or higher

Responsibilities:

• Migrate existing BI reports and dashboards from Tableau to Power BI, ensuring that business logic, calculations, and reporting requirements are preserved.
• Analyze existing Tableau dashboards, reports, data sources, and business logic and translate them into Power BI solutions.
• Design, develop, and optimize Power BI reports and dashboards based on existing Tableau solutions and business requirements.
• Validate migrated reports against the original Tableau versions to ensure data accuracy, consistency, and functional parity.
• Convert business and information needs into effective, user-friendly reports and dashboards.
• Identify gaps, inconsistencies, and technical challenges during the migration process and propose appropriate solutions.
• Implement and optimize BI solutions to support reporting and analytical needs.
• Ensure the quality, accuracy, and performance of migrated and newly developed reports.

Nice to have:

• Experience with Snowflake, Databricks
• AI usage for Power BI report development and/or migration of reports between different BI Tools 

Project technology stack

The project currently utilizes a modern BI ecosystem centered around Tableau, SSRS, and Kibana for reporting and dashboarding, with data sourced from Snowflake. Data transformations are handled through DBT, while orchestration is supported via Airflow. As part of the BI modernization initiative, existing Tableau reporting solutions are being migrated to Power BI.

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

Technology stack

Snowflake, Snowflake SQL, Snowflake databases, schemas, tables, views, materialized views, Snowflake stored procedures, Snowflake UDFs using Python and SQL, Airflow, Python, Azure SQL Database, MS SQL DB, T SQL, ETL, ELT, layered architecture, Medallion architecture, dimensional modeling

Project overview

This project is centered on developing a data lakehouse with Snowflake and Azure SQL, including design, pipeline development, and query optimization.

Position overview

We are looking for a Senior Snowflake Developer with strong experience in Snowflake platform engineering, Airflow, Python, and data warehouse development. You will contribute to building scalable data pipelines, designing warehouse structures, and improving data processing performance.

Responsibilities

• Develop Snowflake data platform solutions
• Build and optimize Snowflake databases, schemas, tables, views, and materialized views
• Create Snowflake stored procedures and UDFs using Python and SQL
• Develop and maintain ETL and ELT pipelines in Snowflake
• Work with Airflow to orchestrate data workflows
• Design and build data warehouse solutions
• Apply layered architecture and Medallion architecture principles
• Implement dimensional modeling for analytical data structures
• Create tables, views, stored procedures, functions, indexes, and partitions in Azure SQL Database and MS SQL DB
• Optimize database performance and tune complex queries
• Use analytical and window functions to support data processing
• Collaborate in English across data project activities

Requirements

• 7+ years of overall IT experience
• 5+ years of experience in data projects
• Experience with Snowflake data platform engineering
• Experience with Snowflake SQL
• Experience with Snowflake databases, schemas, tables, views, and materialized views
• Experience with Snowflake stored procedures and UDFs using Python and SQL
• Experience with Airflow
• Experience with Python
• Experience with Azure SQL Database, MS SQL DB, and T SQL
• Experience creating tables, views, stored procedures, functions, indexes, and partitions
• Experience with performance tuning and complex queries
• Experience using analytical and window functions
• Experience building data warehouses
• Experience with layered architecture and Medallion architecture
• Experience with dimensional modeling
• Good English

Nice to have

• Experience with DBT
• Experience with Snowpark
• Experience with Snowflake CLI
• Experience with Master Data Management design and integration
• Experience with data quality testing, validation, and reconciliation
• Experience writing technical documentation
• Investment banking or asset management domain knowledge
• Experience with Claude AI in SDLC

Description

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.

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

Role Overview
We’re looking for a Data Engineer to build and scale our modern data platform. You’ll design pipelines that ingest and transform data from key wealth management systems into Snowflake, enabling analytics, reporting, and business insights across the firm.
You’ll work closely with analytics, finance, and operations teams to ensure data is reliable, well-modeled, and accessible.

Key Responsibilities

• Build and maintain scalable data pipelines into Snowflake
• Develop transformations using dbt (modeling, testing, documentation)
• Orchestrate workflows using Prefect
• Integrate SaaS platforms using Workato
• Ingest and integrate data from portfolio, client, financial, and enterprise systems
• Design data models for portfolio, client, and financial reporting
• Ensure data quality, lineage, and governance best practices
• Optimize performance and cost in Snowflake
• Occasionally support data visualization work in Tableau

Required Qualifications

• 5+ years of experience in data engineering
• Strong SQL skills and data modeling experience
• Hands-on experience with Snowflake
• Strong experience with dbt 
• Familiarity with ETL/ELT patterns and API-based ingestion
• Experience with orchestration tools (Prefect, Airflow, etc.)
• Develop solutions using Python for data engineering, automation, API integrations, and workflow development
• Experience working with cloud platforms, preferably Microsoft Azure
• Working knowledge of Tableau for data visualization

Nice to Have

• Experience integrating financial platforms (Addepar, Morningstar, etc.)
• Knowledge of data governance and regulatory environments.
• Experience with CI/CD for data workflows
• Understanding of financial/wealth management data is a plus

As a Data Engineer on the Enterprise Data & Intelligence team, you will design, build, and maintain the data pipelines and models that underpin Fourth’s single source of truth. Reporting to the Senior Data Engineer, you will gather and translate business requirements into reliable, well-tested data solutions on our Azure-based cloud platform. You will collaborate closely with analytics engineers and business stakeholders to scope, prioritise, and deliver data products that serve FP&A, Commercial, Product, and AI teams.

Responsibilities:

1. Data Pipeline Development & Optimisation

•Build, maintain, and optimise scalable ETL/ELT pipelines (batch and near-real-time) on Azure Data Cloud Platform (e.g., Data Lake, Microsoft Fabric, Azure Data Factory).

• Develop and refine data models to support BI reporting, analytics, and ML/AI use cases.

•Write efficient, well-documented T-SQL and PySpark code following team coding standards.

2. Data Quality, Testing & Governance

• Implement automated testing, data validation, and monitoring (SLAs, alerts) to ensure pipeline reliability.

• Contribute to data governance practices, including lineage tracking, metadata management, and quality controls.

•Support CI/CD pipelines for data assets, ensuring version control and reproducibility.

3. Requirements Scoping & Cross-Functional Collaboration

•Partner with analytics engineers to scope, refine, and prioritise data requirements from business stakeholders.

•Work with Analysts, BI Developers, Data Scientists, and business teams to translate requirements into production-ready data solutions.

•Provide input on data readiness for machine learning and analytics projects.

4. Platform Contribution & Continuous Improvement

• Contribute to the evolution of the ED&I data platform, including tooling, standards, and documentation.

• Stay current with emerging data engineering patterns and technologies; propose improvements to team processes.

• Leverage AI-driven development tools (e.g., generative-AI code assistants, automated data profiling) to accelerate delivery.

• Support performance tuning and cost optimisation across the data platform.

Requirements:

Experience: 3+ years in data engineering or a closely related role.

Education: Bachelor’s degree in Computer Science, Data Engineering, or a related field.

Technical Skills:

○Strong T-SQL skills and working proficiency in PySpark or Python for data processing.

○Hands-on experience with MS Azure Storage Explorer and SSMS.

○Hands-on experience with cloud-based data engineering services and orchestration tools (e.g., Azure Data Factory, Microsoft Fabric).

○Practical experience building ETL/ELT pipelines and dimensional or analytical data models.

○Familiarity with CI/CD practices in data engineering, including version control (Git) and automated testing.

Preferred Qualifications
• Experience with real-time or streaming data architectures.
• Experience with PowerShell, Apache Kafka, and/or KQL.
• Exposure to AI/ML workflows (feature engineering, data preparation for model training).
• Familiarity with Power BI or other BI/visualisation tools.
• Experience using AI productivity tools (e.g., ChatGPT, Claude, Copilot, Cursor) in day-to-day and data engineering tasks.
• Understanding of data security, privacy, and compliance considerations.

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
 

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!

Position Overview

We are looking for a Junior SRE / DevOps Engineer to join our infrastructure team and help support Kubernetes environments, CI/CD pipelines, application deployments, and production systems.

This role is a good fit for someone who already has basic hands-on experience with Linux, containers, Kubernetes, and CI/CD and wants to grow into an SRE / DevOps position.

Responsibilities

• Support Kubernetes-based environments.
• Assist with application deployments and CI/CD pipelines.
• Work with Jenkins pipelines.
• Support Java application build processes using Maven (mvn).
• Help troubleshoot deployment and infrastructure issues.
• Monitor applications and infrastructure.
• Work with logs, metrics, and alerts.
• Assist with infrastructure automation.
• Maintain technical documentation.
• Work with developers and senior DevOps/SRE engineers on production issues and improvements.

Required Skills

• Basic Linux administration skills.
• Basic understanding of Kubernetes.
• Understanding of Docker and containers.
• Basic experience with Jenkins or another CI/CD system.
• Basic understanding of Maven (mvn) and Java application build processes.
• Understanding of Git.
• Basic networking knowledge: DNS, TCP/IP, HTTP/HTTPS.
• Ability to read logs and troubleshoot basic application or infrastructure issues.
• Basic scripting skills with Bash or Python.
• Willingness to learn and work with production infrastructure.

Nice to Have

• Experience with Helm.
• Experience with Prometheus and Grafana.
• Basic knowledge of cloud platforms such as AWS, Azure, or GCP.
• Experience with Terraform or other Infrastructure-as-Code tools.
• Knowledge of Dremio.
• Basic understanding of Apache Arrow.
• Experience with PostgreSQL or object storage.
• Understanding of SRE concepts such as monitoring, alerting, availability, and incident response.

What We Expect

We do not expect a Junior engineer to know everything.

The important things are strong fundamentals, willingness to learn, and the ability to investigate problems instead of only following predefined instructions.

The engineer will work together with more experienced team members and gradually take more responsibility for CI/CD, Kubernetes, monitoring, and production infrastructure.

We're looking for a Senior Azure Platform Engineer to design and own the core Azure platform — landing zones, networking, API management, and Infrastructure as Code — that other engineering teams build on top of. You'll work within a platform engineering team responsible for secure, repeatable, and fully observable cloud foundations at enterprise scale.

Project
You'll build and evolve a multi-tenant Azure platform — landing zones, an API façade, and integration services — that underpins several client workloads, with security, observability, and DevOps automation designed in from day one.

Responsibilities

• Design and evolve Azure Landing Zones on a strict hub-and-spoke topology (never peer-to-peer), including VNet peering, UDRs, layered network segmentation, NSGs, WAF, private endpoints, and egress control
• Own Private DNS, Private Link, and hybrid DNS forwarding across the platform
• Build and govern Azure API Management as an architectural façade: products, versioning, revisions, policy expressions, backend abstraction, subscription and OAuth 2.0 enforcement, developer portal governance, and self-hosted gateways for on-premises backends
• Drive PaaS-first, Azure-default platform decisions across APIM, Logic Apps Standard, and Functions hosting, and explain the pattern behind every product choice
• Design modular, composable Terraform modules (Azure Verified Modules) that let new platform capabilities be added without re-platforming
• Build parameterised, multi-region and multi-instance Terraform blueprints, including configuration as code for APIM, Policy, monitoring, and DNS
• Own module versioning, release management, and golden-path onboarding templates other engineering teams can consume
• Implement automated platform testing, supply chain security for platform artefacts, and drift detection/reconciliation across instances
• Define SLOs/SLIs, health models, alerting standards, runbooks, and synthetic testing; build dashboards on Azure Monitor, Log Analytics, and Application Insights
• Harden the platform with Defender for Cloud, Entra ID managed identities, Key Vault, availability zones, and IaC-driven disaster recovery
• Integrate diagnostic settings and data connectors as code with the shared Sentinel SIEM, and implement policy as code (Azure Policy definitions, initiatives, exemptions) with compliance reporting
• Provide the private networking, identity, secrets, and observability foundation that async/event-driven workloads depend on, in partnership with the team owning messaging and event topology

• Bring ad hoc scripts and unmanaged integrations under version-controlled, reviewed, and gated DevOps pipelines, eliminating manual or scheduled-task execution outside the platform

   

Requirements

• 5+ years of experience in cloud infrastructure/platform engineering, with deep hands-on Azure expertise
• Strong knowledge of Azure Landing Zones, VNet peering, UDRs, and defence-in-depth networking (NSGs, WAF, private endpoints, egress control, Private DNS, Private Link, hybrid DNS forwarding)
• Hands-on experience with Azure API Management as a façade layer: products, versioning, revisions, policy expressions, OAuth 2.0/subscription enforcement, developer portal governance, self-hosted gateways
• Solid understanding of Azure Integration Services (APIM, Logic Apps Standard, Functions hosting) and the ability to justify pattern-driven product choices
• Advanced Terraform skills: modular design, Azure Verified Modules, environment promotion, feature-flagged components
• Experience building parameterised, multi-region/multi-instance IaC and golden-path onboarding templates for other teams
• Practical experience with Azure Monitor, Log Analytics, Application Insights, Defender for Cloud, and Sentinel SIEM integration
• Experience with policy as code, Entra ID managed identities, Key Vault, availability zones, and IaC-driven disaster recovery
• Strong analytical and communication skills, comfortable working cross-functionally with integration, security, and application teams

• Upper-Intermediate English or higher

   

What We Offer

• Transparent strategy and thoughtful management that keep everyone aligned
• Space for personal growth and career development without limits
• A culture of continuous learning: internal courses, workshops, and English classes twice a week
• Skill up events where we share experience and stay on top of trends
• Competitive perks: flexible schedule, a strong compensation package, support for professional certifications, and generous vacation policy
• Team spirit that thrives through regular events, gatherings, and celebrations

escription

Our client is one of the world’s leading medical companies, with more than 40 years of experience developing and manufacturing medical devices used across all continents.
Due to the healthcare nature of the products, the project follows strict quality, safety, and compliance requirements. Infrastructure and development processes must align with established standards and formal procedures to ensure the highest level of product quality and safety.

Requirements

Mandatory Skills
• CI/CD
• GitHub Actions
• Docker
• Python
• GitLab
• Technical English (documentation)
Good-to-Have Skills
• AWS
• JFrog
PowerShell

Job responsibilities

We are looking for a DevOps Engineer to support the migration of existing IT infrastructure and CI/CD processes from GitLab to GitHub.
The main responsibility will be the migration from GitLab to GitHub, including adaptation of existing CI/CD pipelines and Python scripts. The engineer will also develop new tools and scripts where GitHub does not provide equivalent functionality.
As the project is part of the medical/healthcare domain, infrastructure and CI/CD processes are subject to specific standards, limitations, and formal requirements. The engineer will need to understand and follow these requirements while implementing the migration.
The engineer will work as part of a team of four engineers under the guidance of an Architect.

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.

Location: Poland

🌍 Who we are:

Adaptiq is a technology hub specializing in building, scaling, and supporting R&D teams for high-end, fast-growing product companies in a wide range of industries.

🧩 About the Product:

Our client is a major online gaming operator building a next-generation transactional platform for user account management. This is a greenfield project designed to operate in a highly regulated, high-volume environment and support millions of concurrent users. The platform will process financial transactions in real time and must ensure high availability, sub-second performance, data integrity, security, and full auditability. One of the key engineering challenges is maintaining reliability and performance during extreme traffic spikes and peak events. 

🌟 About the Role:

We are looking for a Senior MLOps Engineer to design, build, and maintain scalable cloud infrastructure, real-time data pipelines, and production ML workflows. You will work with Infrastructure as Code, event-driven architectures, and the full ML lifecycle, including model deployment, monitoring, data governance, and reliability. You will collaborate closely with Data Engineers and Data Scientists to help design the new system, ensure data and ML workflows work reliably end to end, and understand how changes in data can affect downstream models. The role offers strong technical ownership and the opportunity to influence architecture, technology choices, and long-term system design.

📈 Key Responsibilities:

• Design, deploy, and maintain scalable cloud environments using Infrastructure as Code.
• Build and operate reliable real-time, event-driven data pipelines with fault tolerance and sub-second latency.
• Design and optimize storage backends and data lake infrastructure for both transactional and analytical workloads.
• Implement high-availability networking, API gateways, automated failovers, and zero-downtime routing.
• Integrate data validation, observability, and monitoring into data pipelines to ensure reliability and quickly identify issues.
• Develop and manage infrastructure for ML model training, validation, deployment, and inference.
• Automate the deployment and testing of containerized workloads running on Kubernetes.
• Collaborate with cross-functional teams to define ML governance and reliable end-to-end data flows.
• Drive long-term cloud scaling, FinOps and cost optimization, and disaster recovery planning.
• Provide technical leadership, participate in architecture reviews, and mentor team members on engineering best practices.

💻 Required Competence and Skills:

• 5+ years of experience in cloud infrastructure, data engineering, or distributed systems architecture.
• Proven expertise in infrastructure provisioning tools (e.g., Terraform), containerization (Docker, Kubernetes), and cloud platforms (AWS or GCP).
• Hands-on experience with distributed streaming platforms (Apache Kafka) and change data capture methodologies.
• Strong understanding of object storage architectures (e.g., S3), distributed data lakes, and SQL/NoSQL databases.
• Proficiency in Python and scripting (e.g., Bash) for automation and pipeline orchestration.
• Solid knowledge of ML workflows, data governance principles, and model lifecycle management.
• Ability to translate high-level architectural designs into detailed implementations with performance tuning.
• Excellent communication skills and experience collaborating with data scientists and engineering teams.

➕ Nice to Have:

• Background in fintech, iGaming, or other high-throughput, real-time transactional platforms.

🚀 Why Us:

- We provide 20 days of vacation leave per calendar year (plus official national holidays of a country you are based in).

- We provide full accounting and legal support in all countries we operate.

- We utilize a fully remote work model with a powerful workstation and co-working space in case you need it.