Jobs Data Engineer

AI Systems Engineer / AI Infrastructure Architect

We are building a fully integrated AI operating system for business automation, infrastructure management, knowledge systems, ERP integration, AI agents, and local AI runtime orchestration.

This is not a simple chatbot project.

The system combines:
- multi-agent AI architecture
- local and external LLM orchestration
- infrastructure automation
- vector memory and RAG
- ERP/CRM integration
- governance and security layers
- AI workflow execution
- deterministic YAML-based architecture
- self-hosted infrastructure
- monitoring, logging, and orchestration systems

MAIN STACK

Infrastructure:
- Proxmox
- Ubuntu Server
- Docker / Podman
- PostgreSQL
- Redis
- Loki / Prometheus / Grafana
- Keycloak
- Vaultwarden / Vault
- Caddy / Nginx
- TrueNAS / S3 storage

AI Runtime:
- Ollama
- vLLM
- OpenAI
- Anthropic
- Groq
- HuggingFace
- Whisper
- Coqui TTS
- Stable Diffusion

Business Systems:
- Odoo ERP
- Nextcloud
- OnlyOffice
- FreePBX
- Gitea / GitHub

Knowledge Architecture:
- Vector databases
- RAG pipelines
- embeddings
- document parsing
- YAML architecture systems
- long-term AI memory

WHAT YOU WILL WORK ON

- Build and structure AI agent systems
- Design deterministic YAML architectures
- Develop orchestration layers for AI agents
- Build connectors for APIs and internal services
- Integrate local and external AI models
- Create scalable backend services using Python
- Build infrastructure automation and monitoring
- Work on AI memory and retrieval systems
- Develop secure multi-service architectures
- Build internal tooling and automation systems

REQUIRED SKILLS

Strong:
- Python
- FastAPI
- async Python
- APIs and integrations
- Linux
- Git
- Docker
- PostgreSQL
- AI/LLM integrations
- structured engineering mindset

Very valuable:
- RAG systems
- vector databases
- Ollama / vLLM
- Proxmox
- infrastructure automation
- Redis / queues
- AI agents
- workflow orchestration
- security architecture
- Odoo integrations

IMPORTANT

We are not looking for:
- pure frontend developers
- prompt-only AI builders
- people who only use no-code tools
- pure vibe coders without system understanding

We are looking for someone who:
- understands architecture
- can structure complex systems
- thinks in layers and abstractions
- can work independently
- can evolve with the project long-term

PROJECT DIRECTION

The goal is to build:
- an AI-native business operating system
- self-hosted AI infrastructure
- deterministic AI workflows
- scalable AI agents
- centralized governance and monitoring
- internal AI-first tooling

Most inference should run locally using open models.
External APIs are used only where necessary.

The project is already running on real infrastructure and is actively expanding.

Looking for a Data Engineer to join the Dataforest team. If you are looking for a friendly team, a healthy working environment, and a flexible schedule ‒ you have found the right place to send your CV.

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

Optional skills (as a plus):
• Experience with Spark (pyspark);
• Experience with Airflow;
• Experience with Kafka;
• Experience in statistics;
• Knowledge of DS and Machine learning algorithms..

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

We offer:

• Great networking opportunities with international clients, challenging tasks;

• Building interesting projects from scratch using new technologies;

• Personal and professional development opportunities;

• Competitive salary fixed in USD;

• Paid vacation and sick leaves;

• Flexible work schedule;

• Friendly working environment with minimal hierarchy;

• Team building activities, corporate events.

About the Role

We are hiring a skilled Data Engineer / BI Engineer to support and maintain our healthcare organization’s data warehouse and reporting infrastructure.

This role is ideal for someone who enjoys solving data issues, maintaining ETL pipelines, improving reporting systems, and ensuring business stakeholders always have access to reliable, accurate data.

You’ll primarily focus on maintaining existing data pipelines and BI systems while supporting reporting needs across multiple healthcare and finance platforms.

Responsibilities

Data Engineering

• Maintain, monitor, and troubleshoot existing ETL/data pipelines
• Debug pipeline failures and investigate data discrepancies
• Support integrations from multiple external platforms into the internal data warehouse
• Write and optimize SQL queries for data validation and issue investigation
• Update database views, filters, and transformations based on evolving business requirements
• Ensure data accuracy, consistency, and timely delivery across systems

BI & Reporting

• Develop and maintain reports and dashboards using Microsoft Fabric and Power BI
• Modify existing reports based on stakeholder feedback
• Create new reporting solutions when needed
• Ensure reporting logic aligns with underlying data structures and business requirements
• Collaborate with internal stakeholders to gather and refine reporting needs

Maintenance & Support

• Handle ad-hoc technical and reporting requests from leadership and internal teams
• Provide ongoing support for existing data and BI systems
• Document issues, fixes, and system updates
• Participate in regular check-in meetings with leadership

Requirements

Must-Have Skills

• Experience with data engineering, ETL pipelines, and data warehouse maintenance
• Strong SQL skills for querying, debugging, and data investigation
• Hands-on experience with Power BI
• Experience with Microsoft Fabric or similar BI/data platforms
• Experience working with cloud platforms such as Azure, AWS, or GCP
• Understanding of data integrations and external API/data source connections
• Ability to work independently and manage ongoing maintenance/support tasks

Nice to Have

• Experience in the healthcare domain
• Familiarity with EHR/EMR systems such as:
  • ChartMeds
  • Credible
• Experience with finance or HR platforms such as:
  • Planful
  • Dayforce

Work Environment

• Remote collaboration via MS Teams and email
• Mostly asynchronous communication
• Flexible part-time engagement with required overlap with the US team

What We’re Looking For

• Strong problem-solving mindset
• Attention to detail and data accuracy
• Reliable communicator who can work independently
• Someone comfortable handling maintenance, support, and continuous improvement work

We are looking for a Senior Data Engineer to join our team. This is not a standard ETL role. We are building a dynamic data ecosystem where AI is deeply integrated - both as a productivity multiplier and as a core component of our data processing logic for identity data enrichment and data scoring.

You will own the infrastructure that handles over 10,000 executions per minute, ensuring stability, scalability, and data integrity. You will work with a modern stack on Google Cloud Platform, utilizing Cloud Functions and Kubernetes.

We are looking for an engineer who improves infrastructure, automates everything, and is eager to implement LLM-based logic directly into high-load data flows.

Responsibilities

• AI-Driven Data Scoring: Design and implement pipelines that utilize LLMs to analyze and score identity data in real-time. You will integrate AI models directly into the decision-making loop, balancing accuracy with latency and cost.
• Own the Data Architecture: Architect scalable data solutions using GCP and Python. You will manage data storage and retrieval using BigQuery and Apache Iceberg to support querying of TBs of data.
• Heavy Data Processing: Utilize Apache Spark for data transformations and batch processing when lightweight cloud functions are not enough.
• Manage High-Load Orchestration: Maintain and optimize our system instances. It involves complex dataflows, custom Python nodes, and performance tuning for 10k+ execs/minute.
• Release Lifecycle (CI/CD): Take ownership of the deployment process, ensuring that updates to pipelines and infrastructure are released safely with proper testing and rollback strategies.
• Database Optimization: Manage PostgreSQL performance under heavy load, optimizing complex queries and indexing strategies.
• Active AI Usage: Use Claude Code and other AI engineering tools to accelerate your own development, refactoring, and testing processes.
• Incident Resolution: Proactively monitor the system. When alerts fire, you investigate the root cause—whether it’s a database lock or an LLM hallucination—and fix it permanently.
   

Requirements

• 4-5+ years of experience in Data Engineering or Backend Engineering with a strong data focus.
• Production AI Integration: Experience integrating LLMs (OpenAI, Anthropic, Gemini) into production applications via API. You understand latency, token limits, and how to structure data for AI scoring.
• Expertise in GCP: Understanding of Google Cloud Platform (Cloud Functions, IAM, Networking).
• Strong Python: You write clean, efficient, and testable code. You are comfortable building custom logic where standard tools fall short.
• Big Data Stack: Experience with BigQuery, Apache Spark, and modern table formats like Apache Iceberg.
• Kubernetes (K8s): Experience deploying and scaling services in containerized environments.
• Workflow Automation: Understanding of workflow orchestration tools at a deep technical level. N8N is a big part of our domain, so familiarity with it is highly valuable.
• PostgreSQL Mastery: Proven ability to handle heavy write/read loads and optimize schemas.
• English: B2+ (Upper-Intermediate) or higher.
   

Culture & Mindset

• Self-improvement: You are a fast learner. You don't fear AI replacing you; you master it to replace your manual tasks.
• Ownership: You treat the Identity domain as your own business. If a scoring model drifts or a pipeline slows down, you notice it and fix it without being asked.
• Internal Locus of Control: You take responsibility for outcomes. If an external API fails, you build a fallback mechanism instead of just blaming the provider.
• Get It Done: You prioritize shipping value. You know when to use a simple script and when to build a complex architecture.

Openness: You share knowledge freely. If you find a better way to prompt the AI for scoring, you share it with the team.

Are you a Senior Backend Engineer passionate about building scalable AI-driven systems? Join us at Sigma Software to work on a cutting-edge platform that transforms how large-scale engineering organizations manage and analyze complex technical data.

This is a remote position with flexible locations across Europe, Ukraine, and LATAM. You will be part of an innovative team leveraging AI, semantic graphs, and distributed processing to deliver impactful solutions.

At Sigma Software, we value expertise, creativity, and collaboration. Why join us? You will work with advanced technologies, contribute to mission-critical projects, and be part of a company recognized for excellence and innovation.
 

Customer

Our customer operates in the AdTech industry, delivering advanced technology solutions that optimize advertising performance and audience targeting. While the name is confidential, the organization is known for leveraging cutting-edge AI and data-driven strategies to enhance campaign effectiveness and deliver measurable business impact.
 

Project

We are developing a next-generation AI-powered Knowledge Base and Gap Analysis platform for SysML-based engineering environments. The system enables large-scale engineering organizations to ingest, structure, analyze, and reason over complex MBSE artifacts and technical documentation. It supports both cloud and secure classified environments, improving traceability, identifying gaps, and enhancing decision-making in mission-critical projects.

Responsibilities

• Design and develop scalable AI-powered backend systems for SysML-based engineering environments
• Build and maintain distributed data ingestion and ETL pipelines for large-scale engineering artifacts and technical documentation
• Develop and optimize LLM-powered workflows for metadata extraction, semantic analysis, and entity resolution
• Implement AI agents and multi-agent orchestration workflows
• Design and improve RAG-based architectures and semantic retrieval pipelines
• Develop graph-based knowledge representation and traceability analysis solutions
• Work with graph databases, graph processing libraries, and semantic relationship modeling
• Build and optimize distributed data processing workflows using Apache Spark
• Collaborate with cross-functional engineering teams to integrate AI capabilities into platform services
• Design scalable and high-performance APIs and backend services
• Improve system reliability, scalability, observability, and performance across distributed environments
• Participate in architecture discussions and technical decision-making processes
• Contribute to cloud-native infrastructure and deployment workflows
• Support deployments in secure, air-gapped, or classified environments when required
• Create and maintain technical documentation and engineering best practices
  
  Requirements
• At least 5 years of commercial experience in Software Engineering, Data Engineering, or AI systems development
• Strong production experience with Go, Rust, Scala or Python
• Hands-on experience building distributed and scalable systems
• Practical experience with LLM-based applications and AI integrations
• Experience building AI agents and multi-agent systems
• Strong understanding of RAG architectures and semantic retrieval workflows
• Hands-on experience with graph technologies, graph libraries, or graph databases
• Experience with Apache Spark and distributed data processing
• Strong understanding of ETL pipelines and large-scale data ingestion workflows
• Experience with cloud-native infrastructure and distributed environments
• Practical experience with backend platform development and API integrations
• Good understanding of semantic search, entity resolution, and metadata extraction
• Experience working with highly scalable and high-performance systems
• Strong problem-solving and communication skills
• Upper-Intermediate level of English
   

Will be a plus:

• Background in Data Engineering
• Experience with Knowledge Graphs and graph-based semantic modeling
• Familiarity with MBSE or SysML environments
• Experience supporting air-gapped or classified environments
• Experience with vector databases and embedding pipelines
• Experience with Kubernetes and cloud platforms such as AWS, GCP, or Azure

The company is a leading product-based organization and the premier 'end-to-end' provider of data and trading technology across foreign exchange, financial, and futures markets. Its proprietary low-latency gateways empower international corporations and Tier-1 banks to execute global transactions with industry-leading speed and precision.
 

Company is looking for a Data Infrastructure Engineer for a high-impact, foundational role. In this capacity, you will serve as the primary authority on the big-data engine that drives our real-time and historical analytics. Your expertise will be critical in analyzing liquidity, fill ratios, and market impact.

      Requirements:

• Deep knowledge of at least one industry-leading Big Data or Time-Series database (e.g., ClickHouse, InfluxDB, or ScyllaDB/Cassandra).
• Proven experience managing "high-velocity" data environments (streaming ticks, execution logs, and order book events).
• Strong proficiency in writing and optimizing complex queries for massive datasets (billions of rows).
• Extensive experience in a Linux-heavy environment with a focus on system-level performance and low-latency tuning.

• Ability to translate business metrics into efficient data structures without necessarily writing application-level code.

   

  Nice to have:

• Experience in the financial industry (FIX protocol, FX trading, etc.).
• Background in high-performance hardware/software integration.
• Experience with scripting for automation (Python, Bash).
  
  Responsibilities:
• Evaluate and select the optimal Big Data/NoSQL engine to handle high-frequency FX market data and trade execution logs.
• Own the end-to-end installation, configuration, scaling, and long-term maintenance of the database environment.
• Build and tune complex time-series queries (calculating metrics like Effective Spread and Last Look Hold Times) to ensure sub-second responses for real-time monitoring tools.
• Act as the subject matter expert, training GUI developers and team members on best practices for efficient data retrieval and interaction with the data layer.
  
   Benefits:
• Standard working hours: 9-18. 
• 15 working days + public holidays weekends.
• 10 days of sick leave.
• Medical insurance compensation.
• Equipment.
• Salary reviews once a year.
  
  The market moves in milliseconds—your career should move just as fast. Send your CV.
   

POSITION OVERVIEW

Our US customer is seeking a skilled Data Engineer / BI Engineer to maintain and develop their data warehouse and reporting infrastructure. This is primarily a maintenance and support role focused on ensuring the reliability and effectiveness of our data pipelines and business intelligence reporting systems.

RESPONSIBILITIES

Data Engineering (Primary Focus)

• Maintain and debug existing data pipelines that extract data from multiple external platforms.
• Monitor and troubleshoot data pipeline issues to ensure data accuracy and timely delivery.
• Update and manage database views and filters as business requirements evolve.
• Investigate data quality issues and perform SQL queries to diagnose problems.
• Support data integration from multiple sources into the Care House data warehouse.

Business Intelligence & Reporting

• Develop and maintain BI reports in Microsoft Fabric on the Azure stack.
• Create new reports and dashboards as needed.
• Update and modify existing Power BI reports based on stakeholder feedback.
• Ensure reports accurately reflect underlying data structures and business logic.
• Collaborate with stakeholders to understand reporting requirements.

Maintenance & Support

• Respond to ad-hoc queries and requests from the Lead and her team.
• Provide ongoing technical support for existing systems and processes.
• Document issues, resolutions, and system changes.
• Participate in check-in meetings with leadership.

REQUIRED SKILLS & EXPERIENCE

• Data Engineering: Experience with data pipelines, ETL processes, and data warehouse maintenance.
• BI/Analytics Tools: Proficiency with Microsoft Fabric and Power BI.
• Database Management: Strong SQL skills for querying, debugging, and data investigation.
• Cloud Platforms: Experience with Azure stack (preferred) or other cloud platforms (AWS, GCP).
• Data Integration: Experience with external data sources and API integrations.
• Healthcare Domain Knowledge: Experience with healthcare systems and EHR platforms is a plus.

DATA SOURCES

• Electronic Health Record systems (e.g., ChartMeds, Credible).
• Finance platforms (e.g., Planful, Dayforce).
• SQL databases and data lakes.
• Data Warehouse: Care House (internal data warehouse).

WORK ENVIRONMENT & COLLABORATION

• Part-time: 80 hours per month.
• Schedule: Mon – Fri 9-5 (US EST) overlap with team at least 2-3 hours.
• Team Structure: Work independently on assigned tasks with support from experienced team members.
• Communication: Primarily asynchronous via email and MS Teams.

Якщо знаєш коли використати StatefulSet а коли Deployment, і розумієш різницю між HPA та ReplicaSet - тоді запрошуємо у команду.
А якщо ще й спиш спокійно коли у тебе spot instances у продакшені - ми точно знайдемо спільну мову.

Про проект
Mabrook — це AI-powered social entertainment платформа, що поєднує відео, live-контент, ігрові механіки та маркетплейс в одному продукті. Платформа будується з AI як core-частиною — персоналізація, real-time взаємодія та безпека інтегровані на рівні продукту.

Що будеш робити
 

• CI/CD pipelines: розвивати shared pipeline library, додавати security scans, прискорювати builds
• Infrastructure as Code: писати Terraform модулі для нових сервісів і environments
• Kubernetes magic: оптимізувати resource limits, налаштовувати autoscaling, розбиратися з networking
• Monitoring & Alerting: створювати дашборди які показують що насправді відбувається, а не “все зелене”
• Security: додавати vulnerability scanning, secrets management, network policies
• Performance: load testing, capacity planning, оптимізація під вірусне навантаження
• Multi-regional deployment: users з Бразилії не хочуть чекати 300ms latency з US
• Database high availability: тестувати failover сценарії о 3 ночі не входить в обов‘язки, але backup restoration - входить
• Advanced monitoring: distributed tracing, APM, cost optimization

Що треба знати (hard skills)

Must have:
Kubernetes - твій другий дім:

• GCP досвід (Essential): впевнена робота з Google Cloud Platform, розуміння IAM, VPC та специфіки GKE.
• Розумієш різницю між Deployment, StatefulSet, DaemonSet і знаєш коли що використати
• HPA vs ReplicaSet vs manual scaling - не просто букви
• ConfigMaps, Secrets, PV, PVC - працював з усім цим в бойових умовах
• Знаєш що таке liveness/readiness probes і навіщо вони потрібні
• Helm charts не викликають панічної атаки

GitOps або принаймні хочеш розібратися:
 

• ArgoCD, FluxCD або щось схоже бачив не тільки в туторіалах
• Розумієш ідею “Git as a source of truth”
• Не боїшся YAML файлів (їх буде багато)

Infrastructure as Code:
 

• Terraform - писав щось крім “hello world” прикладів
• Розумієш modules, state management, backends
• Знаєш навіщо потрібен terraform plan перед apply

CI/CD pipelines:
 

• GitLab CI, GitHub Actions, Jenkins - працював хоча б з одним
• Розумієш stages, artifacts, cache, dependencies
• Docker build optimization - не просто копіювання з StackOverflow

Linux і scripting:
 

• Bash scripting на рівні “не тільки ls і cd”
• Розумієш filesystem, processes, networking basics
• SSH, tmux, grep, awk - друзі, а не незнайомці

Networking basics:
 

• TCP/IP, DNS, load balancing - розумієш як це працює
• Firewall rules, security groups - налаштовував в продакшені
• Ingress, Services у Kubernetes - не магія для тебе

Nice to have:
 

• Monitoring tools: Prometheus, Grafana, Loki або подібні
• Security tools: Trivy, SonarQube, security scanning
• Databases: PostgreSQL, MongoDB - базове розуміння
• Message queues: Kafka, RabbitMQ
• Розумієш що таке distributed tracing і навіщо він потрібен
• Чув про FinOps і cost optimization (GCP bills можуть бути fun)
   

Soft skills (теж важливо)
 

• Самостійність: можеш розібратися сам коли щось незрозуміло (документація, Google, експерименти)
• Комунікація: вмієш пояснити девелоперу чому його pod використовує 4GB RAM замість 512MB
• Проактивність: бачиш проблему - фіксиш, а не чекаєш поки хтось скаже
• Англійська: документація, Stack Overflow, error messages - все це англійською (read/write обов’язково)
• Українська: команда спілкується українською

Бонуси які роблять тебе ідеальним кандидатом
 

• Колись налаштовував multi-regional deployment
• Розумієш різницю між metrics, logs і traces
• Чув про SRE practices і не вважаєш це buzzword
• Писав документацію яку люди реально читали
• Маєш досвід з high-load проектами (соцмережі, стрімінг, e-commerce)
• Знаєш що таке chaos engineering (і можливо навіть практикував)
• Можеш пояснити дитині що таке Kubernetes (це складніше ніж здається)

Що тебе НЕ чекає (чесно)
-Legacy монолітна Java система з 10-річним technical debt
-Deployments через FTP (ні, серйозно, ні)
-“Просто зроби deploy” без документації і доступів
-Prod доступи у всіх підряд
-Мануальні deployments по 100 разів на день
-On-call duty кожного тижня (поки що взагалі нема)

Що пропонуємо:
+Цікавий проект на стадії активного росту - будуєш інфраструктуру “з нуля” по сучасним практикам
+Сучасний tech stack - GCP, Kubernetes, GitOps, Infrastructure as Code
+Самостійність і довіра - ти експерт у своїй області, мікроменеджмента не буде
+Можливість впливати на архітектурні рішення - твоя думка важлива
+Remote робота - працюй звідки зручно
+Гнучкий графік - головне результат і комунікація
+Можливість рости - від middle до senior/lead у процесі розвитку проекту
+Адекватна команда - без токсичності і драм

Технічне середовище:
 Всі конфіги в Git (GitOps)

• Code review є нормою
• Документація пишеться і підтримується
• Автоматизація > ручна робота
• Security - не “потім додамо”

P.S.
Якщо ти дочитав до кінця і подумав “звучить цікаво, але я не впевнений що підходжу на 100%” - все одно відгукнись. Ідеальних кандидатів не існує, а мотивація і здатність вчитися часто важливіші за знання всіх нюансів GCP.
Якщо ж ти прочитав і подумав “pfff, це ж легко, я можу більше” - тоді точно пиши, маємо що запропонувати

P.P.S. Так, у нас є spot instances у продакшені. Так, вони іноді terminate. Ні, це не баг, це feature для cost optimization

We are looking for an experienced Kubernetes Health / Drift / Rollout Engineer

This role owns the operational automation that makes the Kubernetes platform trustworthy in production. 

What This Person Will Build

•  Kubernetes profile drift detection against expected cluster configuration.
•  Node and cluster health monitoring with degraded/failed states
• Staged rollout automation for OS image and Kubernetes upgrades
• Canary, percentage-based rollout, halt, rollback, and recovery logic
•  Node replacement flows and capacity updates after failures
•  Audit events and operational diagnostics for all lifecycle actions

Must-Have Background

• Strong Go and Kubernetes client-go experience
•  Experience building Kubernetes controllers, operators, reconcilers, health monitors, rollout systems, or upgrade automation
•  Deep understanding of node lifecycle, cordon/drain, PodDisruptionBudgets, device plugins, cluster upgrades, and failure recovery
•  Production operations mindset around rollback, blast radius, staged deployment, and observability
•  Experience debugging real Kubernetes incidents

Nice to Have
 

• Experience with Argo Rollouts, Flux, Cluster API, Rancher, OpenShift, Kured, node remediation, edge clusters, or multi-site cluster operations.

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:

We power a global social investing platform that enables users to discover, invest, and collaborate through shared portfolios and community-driven insights. Operating in multiple languages across dozens of countries, the platform serves tens of millions of registered users and handles high volumes of transactional and analytical data daily. Founded in the mid-2000s with a vision to democratize investing through transparency and education, the product has evolved into a publicly traded, large-scale service with over a thousand employees and offices worldwide. Key challenges include maintaining high availability and performance at scale, securing sensitive data across cloud environments, and continuously automating delivery pipelines to support rapid feature releases.

About the Role:

You will join a central DevOps organization tasked with defining best practices, creating guidelines, and embedding a DevOps culture across global R&D teams. As Principal DevOps, you own the end-to-end design, implementation, and operation of large-scale, complex environments that ensure seamless scalability, resilience, and optimal performance. You will spearhead cross-organizational projects—such as multi-cluster Kubernetes upgrades, CI/CD redesigns, and new infrastructure rollouts—driving each initiative from research and solution design through implementation and validation. This role offers deep technical ownership, the autonomy to introduce cutting-edge tools, and the opportunity to mentor and guide a diverse group of engineers toward a unified, high-performing delivery model.

Key Responsibilities:

• Lead and execute cross-functional DevOps projects from concept through production rollout.
• Define, document, and enforce DevOps best practices, standards, and guidelines.
• Research and evaluate new tools, technologies, and methodologies to optimize delivery and operations.
• Design and maintain scalable, resilient infrastructure solutions across cloud and on-prem environments.
• Architect, build, and refine CI/CD pipelines with tools such as GitHub Actions or Jenkins.
• Collaborate with R&D teams to improve service reliability, scalability, and performance.
• Own Kubernetes multi-cluster lifecycle management, including upgrades, security, and governance.
• Manage end-to-end projects: gather requirements, propose designs, plan rollouts, and oversee implementation.
• Troubleshoot and resolve complex production issues related to performance, availability, and security.
• Mentor and guide team members, lead technical discussions, and foster a collaborative culture.

Required Competence and Skills:

• 6+ years of hands-on experience in DevOps or Site Reliability Engineering roles.
• Proven expertise in the full application release cycle and CI/CD best practices.
• Experience managing and developing CI/CD tools (e.g., GitHub Actions, Jenkins).
• Experience designing CI/CD solution architectures aligned to development and business needs.
• Deep understanding of infrastructure and operations: storage, networking, compute, and cloud security (Azure preferred).
• Hands-on experience with Infrastructure as Code tools such as Terraform.
• Proficiency in Linux shell scripting and at least one programming language (Python preferred) for automation.
• Strong Kubernetes and container orchestration skills, including cluster provisioning and upgrades.
• Demonstrated ability to operate in production environments, handling performance, scalability, and security challenges.
• Excellent debugging skills for identifying and resolving complex technical issues.
• Self-starter with strong time management and the ability to work independently in a dynamic environment.
• Leadership experience: mentoring peers, leading discussions, and driving decisions in technical forums.

Nice to Have:

• Familiarity with Terragrunt for Infrastructure as Code workflows.
• Experience with service mesh architectures (e.g., Istio, Linkerd).
• Exposure to internal developer platforms (IDP) and self-service tooling.

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.

- We offer a highly competitive package with yearly performance and compensation reviews.

About the client:

Our Client is a fast-paced digital healthcare company that creates a growing portfolio of online health communities for people with chronic conditions. The company’s mission is to improve patients’ quality of life by connecting them with each other, with caregivers, and healthcare industry partners, building beneficial social interactions and meaningful health conversations. 

About the project:

The core of the project is working with the data; the target is to redesign and enhance data-driven solutions. The team is responsible for expanding and optimizing the data flow and data pipeline architecture, modeling and analyzing data, interpreting trends or patterns in complex data sets, and translating them into product and marketing insights. If you are excited by the prospect of optimizing or even re-designing our data architecture to support our next generation of products and data initiatives, we would be thrilled to have you apply!

Requirements

● Good Python skills

● Good working SQL knowledge and experience working with relational databases, query authoring (SQL), as well as working familiarity with a variety of databases

● A successful history of manipulating, processing, and extracting value from large disconnected datasets

● Experience building and optimizing data pipelines, architectures, and data sets

● Experience performing root cause analysis on internal and external data and processes to answer specific business questions and identify opportunities for improvement

● Strong analytic skills related to working with unstructured datasets

Technologies:

• Python
• AWS: SES, RDS (MySQL), EC2, Elasticsearch Service, Route 53, VPC, etc
• Snowflake
• Docker
• dbt
• Airflow

Job Responsibilities

● Manage and optimize core data infrastructure

● Develop a custom data infrastructure not available off-the-shelf

● Build monitoring infrastructure to give visibility into the pipeline’s status

● Monitor all jobs for impact on cluster performance

● Run maintenance routines regularly

● Tune table schemas to minimize costs and maximize performance

● Building and maintaining custom ingestion pipelines

● Build non-SQL transformation pipelines

● Build processes supporting data transformation, data structures, metadata, dependency, and workload management

We are the creators of a new fintech era!
Our mission is to change this world by making blockchain accessible to everyone in everyday life. WhiteBIT is a global team of over 1,200 professionals united by one mission — to shape the new world order in the Web3 era. Each of our employees is fully engaged in this transformative journey.
We work on our blockchain platform, providing maximum transparency and security for more than 8 million users worldwide. Our breakthrough solutions, incredible speed of adaptation to market challenges, and technological superiority are the strengths that take us beyond ordinary companies. Our official partners include the National Football Team of Ukraine, FC Barcelona, Lifecell, FACEIT and VISA.

The future of Web3 starts with you: join us as a Data Team Lead!

Requirements

— 5+ years of experience as Data Analyst / Quant Analyst / Data Engineer / Risk Analyst, including 2+ years in a Lead/Senior role with direct management of a team of 3+
— Strong production-level Python (pandas, numpy, pyarrow, SQLAlchemy, asyncio)
— Expert SQL: window functions, query optimisation, hands-on with columnar databases (ClickHouse, Snowflake, BigQuery)
— Experience building and operating ETL/ELT pipelines (Airflow, dbt, Prefect) in both batch and real-time (Kafka, Flink, Redpanda)
— Hands-on with BI tools: Tableau, Grafana, Superset — building dashboards for trading and risk metrics
— Solid understanding of trading fundamentals: PnL attribution, margin requirements, VaR, risk models, funding rates, basis
— Experience with large volumes of market data (millions of rows, low-latency, tick data)
— Team-building experience: hiring, onboarding, mentoring, performance reviews, goal setting
— Prior experience in crypto / fintech / proprietary trading is mandatory
— English B2+ for communication with international teams and stakeholders

Responsibilities

— Lead the Data Analysts / Data Engineers team (3–5 people): hiring, onboarding, mentoring, growth, performance reviews
— Build and maintain analytics for PnL, risk, positions and execution metrics for Trading and Liquidity Desks
— Architect and evolve the data platform: from ingestion (exchange APIs, market data streams, on-chain) to visualization
— Develop and optimise ETL/ELT pipelines (batch and real-time)
— Build and evolve BI dashboards (Tableau, Grafana) tailored to traders, risk managers and operations
— Maintain alerting and monitoring for deviations in key metrics (PnL, exposure, latency, data freshness)
— Work with internal databases, exchange APIs, market data streams and on-chain sources
— Partner closely with risk, trading, engineering and operations teams — translating business requests into analytical tasks
— Establish team processes: data quality, code review, documentation, on-call
— Roadmap planning, prioritisation, and regular reporting to stakeholders and Liquidity Department leadership

Work conditions

Immerse yourself in Crypto & Web3:
— Master cutting-edge technologies and become an expert in the most innovative industry.
Work with the Fintech of the Future:
— Develop your skills in digital finance and shape the global market.
Take Your Professionalism to the Next Level:
— Gain unique experience and be part of global transformations.
Drive Innovations:
— Influence the industry and contribute to groundbreaking solutions.
Join a Strong Team:
— Collaborate with top experts worldwide and grow alongside the best.
Work-Life Balance & Well-being:
— Modern equipment.
— Comfortable working conditions, and an inspiring environment to help you thrive.
— 22 business days of paid leave.
— Additional days off for national holidays.
— Health insurance.

We are a dynamic fintech company of 17 people, acting as a bridge between high-risk businesses and payment providers like Stripe. Our mission is to streamline financial processes, enhance data automation, and leverage AI to accelerate decision-making.

Role Overview:
We are looking for a versatile Financial Data & AI Automation Engineer who will combine financial insight, business analysis, and modern technology skills. You will be responsible for building automated dashboards, integrating systems, managing data pipelines, and implementing AI-driven solutions that accelerate our financial operations.

Key Responsibilities:

• Build, maintain, and optimise financial dashboards and reports (Excel, Google Sheets, Data Studio, or similar).
• Automate repetitive processes using scripts, AI agents, and no-code/low-code platforms (Zapier, Make/Integromat, Google Apps Script).
• Gather business requirements, translate them into technical solutions, and ensure proper documentation.
• Collaborate with team members to design integrated systems (CRM/ERP) and improve workflows.
• Ensure financial data accuracy, support P&L preparation, and assist in decision-making.

• Stay up-to-date with emerging technologies and AI tools relevant to finance and operations.

   

Required Skills & Qualifications:

• Strong programming skills (Python, JavaScript, or similar) for automation and AI agent development.
• Hands-on experience with AI-driven tools and agents.
• Solid understanding of financial processes, P&L basics, and reporting.
• Experience in building dashboards and working with structured data.
• Familiarity with no-code/low-code tools and workflow automation.
• Strong analytical skills and attention to detail.
• Excellent communication and documentation abilities.

• Self-motivated and highly disciplined, able to complete tasks independently.

   

Preferred Skills:

• Experience integrating multiple systems into a unified platform (CRM/ERP).
• Background in business analysis or process optimisation.

• Familiarity with cloud platforms and AI APIs.

   

Why Join Us:

• Opportunity to shape the financial and operational backbone of a fast-growing fintech.
• Work with cutting-edge AI and automation technologies.
• Flexible work environment with a collaborative, small-team culture.
• Chance to impact high-risk financial operations and build scalable solutions.

Cyber Harbor is a fast-growing Ukraine-based company founded by engineers and researchers who helped defend critical cyber 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 кіберінфраструктури 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.

We are seeking a highly skilled Senior Data Engineer to design, build, and maintain scalable data infrastructure and pipelines. In this role, you will be responsible for enabling reliable data processing, ensuring high data quality, and supporting analytical and business intelligence needs across the organization. You will work with large-scale distributed systems, modern data platforms, and both batch and real-time data processing frameworks.
 

Key Responsibilities:

• Design, develop, and maintain robust ETL/ELT data pipelinesBuild and optimize scalable data processing systems (batch and streaming)
• Architect and manage data lakes, data warehouses, and data marts
• Develop data transformations using SQL, Python, and Apache Spark (PySpark)
• Integrate data from various sources (databases, APIs, streaming systems)
• Ensure data quality, integrity, and consistency through validation and monitoring
• Optimize performance of data pipelines (partitioning, indexing, query tuning)
• Implement and maintain workflow orchestration (e.g., Apache Airflow)
• Collaborate with cross-functional teams (Data Analysts, Data Scientists, Backend Engineers)
• Support and contribute to CI/CD pipelines for data workflows
• Document data architecture, processes, and standards

Required Qualifications
 

Technical Skills:

• 4+ years of professional experience as a Data Engineer or in a similar role
• Strong proficiency in SQL (e.g., PostgreSQL, Snowflake, BigQuery, Redshift)
• Hands-on experience with Apache Spark / PySpark
• Solid understanding of data modeling (normalized and dimensional models)
• Experience designing and implementing ETL/ELT pipelines
• Experience with cloud platforms (AWS, GCP, or Azure)

Experience with:

• Kubernetes
• Containerization tools (Docker)
• Version control systems (Git)
   

Nice to Have:

• Experience with stream processing (e.g., Apache Kafka, Kinesis, Flink)
• Knowledge of modern data stack tools (e.g., dbt, Delta Lake, Iceberg)
• Experience with data governance and lineage tools
• Exposure to infrastructure as code (e.g., Terraform)
   

What we offer:

• Paid vacation and sick leaves
• Competitive salary
• Flexible work schedule
• Career growth
• Corporate celebrating and presents
• Corporate English courses
• Office/hybrid work in Ternopil or opportunity for remote work
• Coffee, tea, fruits, and cookies
  in the office