Jobs Data Engineer

Шукаємо Senior Data Engineer з досвідом BigQuery, Python, DBT та Data Modeling в дуже велику і стабільну продуктову компанію. Компанія розробляє софт для найбільших страхових компаній світу.

Проект – побудова нової Data Platform на базі BigQuery з використанням DBT, Python, GCP. Сінйорна команда, адекватний і професійний менеджмент.

Шукаємо виключно українських девелоперів закордоном. Нажаль, в Україні цього разу не розглядаємо, через обмеження по доступу до критичних даних. Пропонуємо дуже гнучкі умови: віддалена робота, цікаві задачі і хороше/спокійне керівництво.

Опис вакансії:

What You’ll Do: 

• Design & run pipelines – create, deploy, and monitor robust data flows on GCP. 
• Model data – design star/snowflake schemas for analytics and reporting. 
• Write BigQuery SQL – build procedures, views, and functions. ● Build ML pipelines – automate training, validation, deployment, and model monitoring. 
• Optimize ETL – speed up workflows and cut costs. 
• Use the GCP stack – BigQuery, DBT + Dataflow, Dataproc, Airflow/Composer, Celigo.
• Guard quality & uptime – add tests, validation, and alerting; fix issues fast. 
• Document everything – pipelines, models, and processes. 

• Keep learning – track new tools and best practices. 

   

What You’ll Need: 

• 6+ yrs building data/ETL solutions; 2+ yrs heavy GCP work. 
• Proven BigQuery warehouse design and scaling. 
• Deep SQL, Python, DBT, Git; Talend, Fivetran, or similar ETL tools. 
• Strong data‑modeling skills (star, snowflake, normalization).
• Solid grasp of Data Lake vs. Data Warehouse concepts. 
• Problem‑solver who works well solo or with a team. 
• Clear communicator with non‑technical partners. 
• Bachelor’s in CS, MIS, CIS, or equivalent experience. 

The company is building the control layer for an energy-constrained world — deploying AI, machine learning, and reinforcement learning to optimize HVAC systems, industrial equipment, and large-scale energy loads across commercial buildings, factories, hospitals, and data centers. The focus is on real, measurable impact: autonomous control systems that drive 20–30%+ energy savings in production environments.

We're looking for a BMS Control Engineer / Forward Deployment Engineer (TPM) who will join the team. This is a hands-on role for someone who doesn't just design building automation systems, but has deployed, commissioned, and optimized them in real-world infrastructure.

This role is for someone who takes full ownership of field deployments — from site discovery to production rollout. You'll work at the intersection of BMS/BAS systems, HVAC controls, and AI-driven optimization, deploying autonomous control systems across commercial buildings, factories, hospitals, and data centers.

Your responsibilities will include:

• Own deployments end-to-end: site discovery, integration, commissioning, validation, and rollout;
• Install, configure, and commission BAS/BMS and PLC-integrated systems;
• Deploy gateways, sensors, submeters, and communications infrastructure;
• Perform startup, point-to-point testing, and controls validation;
• Interface with AHUs, RTUs, chillers, boilers, pumps, cooling towers, and VFDs;
• Integrate through BACnet (IP & MS/TP), Modbus, LON, and IP networks;
• Work with Niagara, Siemens, Honeywell, Johnson Controls Metasys, Delta, and other BAS platforms;
• Configure addressing, routing, communications, and device connectivity;
• Diagnose controls hardware, wiring, networking, protocol, and sensor issues;
• Support deployment of AI-driven and RL-driven control strategies;
• Own deployment schedules, communications, milestones, and execution;
• Coordinate customers, contractors, vendors, and internal engineering teams;
• Maintain deployment plans, commissioning reports, diagrams, and as-built documentation.
   

What we expect from you:

• Degree in Electrical Engineering, Mechanical Engineering, HVAC, or related discipline — or equivalent BAS/PLC/SCADA/DCIM experience;
• 2+ years of hands-on BACnet experience (IP & MS/TP);
• 2+ years of Modbus experience;
• 2+ years of HVAC Controls / DDC / BMS experience;
• Strong understanding of BMS/DDC systems, PLCs, PID loops, hydronics, and refrigeration;
• Experience with BAS platforms: Niagara (Tridium), Siemens, Honeywell, Johnson Controls Metasys, Delta;
• Hands-on commissioning and troubleshooting experience in the field;
• Ability to work independently and take ownership in customer-facing environments.
   

Nice to have:

• Niagara (Tridium), EPA 608, NATE, or OSHA certifications;
• Experience in industrial facilities, healthcare, mission-critical environments, or data centers;
• Exposure to IoT, edge computing, SCADA, or DCIM platforms;
• Experience with LON protocol and IP networking in BAS contexts.
   

We offer:

• Full-time engagement on a high-impact infrastructure project;
• Remote-friendly with on-site deployment work at client facilities;
• Direct work with cutting-edge AI and reinforcement learning applied to real-world systems;
• Measurable impact — 20–30%+ energy savings across live deployments;
• Opportunity to help define the future of autonomous building and industrial control systems.

We are looking for a Senior Machine Learning Engineer to work on LLM-based systems with a strong emphasis on integration, end-to-end workflows, and production readiness. This role combines performance optimization (prefill/decode, throughput, latency) with hands-on work integrating components across the AI platform.

A significant part of the role involves building end-to-end integration flows and tests, particularly around token generation pipelines and system orchestration, as well as contributing to intelligent system behavior such as hardware selection and execution strategies. The role also includes developing system-level logic in Python for multi-tenant management, caching strategies, and service lifecycle management across the platform.

Responsibilities:

• Build and maintain end-to-end integration flows across the AI inference pipeline (serving, orchestration, APIs, and infrastructure);
• Design, implement, and optimize LLM inference workflows, including prefill and decode stages;
• Improve system performance with focus on throughput, latency, and interactivity;
• Write production-grade components in Python and integrate them into the broader system;
• Contribute to system-level logic such as smart hardware selection and execution strategies;

• Integrate models (open source and custom), services, and APIs into cohesive, reliable end-to-end application pipelines.

  Requirements:

• 5+ years of experience in software engineering or machine learning engineering;
• Strong proficiency in Python;
• Strong experience with LLM inference systems and performance optimization;
• Hands-on experience with system integration and end-to-end workflows;
• Experience with inference frameworks such as vLLM, TensorRT, SGLang etc;

• Experience working with GPU/accelerator-based systems.

  Would be a plus:

• Hands-on experience with Dynamo and LLM-D for LLM inference and serving;
• Familiarity with Kubernetes and cloud environments.

Are you passionate about building scalable, reliable data systems that power real-world solutions? We are looking for a Senior Data Engineer to join our team and work remotely from Europe, Ukraine, or LATAM.

At Sigma Software, we partner with innovative companies to deliver cutting-edge technology solutions. This role offers the opportunity to design and operate a canonical data platform that integrates diverse external data sources, ensuring high quality and flexibility.

Why join us? You’ll work with modern technologies, collaborate with talented professionals across multiple regions, and have the freedom to experiment and innovate while contributing to impactful projects in the AdTech domain.

Customer

Our client is a fast-growing AdTech company focused on solving real-world challenges in digital advertising and data-driven marketing. They specialize in building highly resilient and scalable systems that encourage experimentation and innovation. Their data platform is designed to be both powerful and flexible, enabling engineers to introduce new ideas and leverage the latest technologies to optimize advertising performance and audience insights.

Project

The project involves developing and maintaining a canonical data platform that integrates multiple external data sources. It supports both full data loads and incremental updates, ensures high data quality, and leverages AI-assisted tools for monitoring and issue detection.

Key Technologies: Java, Scala, SQL, GCP Dataflow, REST APIs, AI-assisted tools, event-driven architectures

Requirements

• At least 5 years of experience as a Data Engineer or Backend/Data Engineer
• Strong production experience with Scala
• Proven experience integrating external systems via REST APIs (pagination, rate limiting, token-based authentication)
• Strong data modelling skills with structured, relational data
• Solid SQL knowledge
• Experience with GCP Dataflow
• Experience operating data pipelines in production environments
• Strong communication skills and ability to collaborate across teams

• At least an Upper Intermediate level of English

   

WILL BE A PLUS:

• Experience with event-driven architectures or messaging systems
• Designing canonical schemas across multiple data sources

• Experience with LLM (Large Language Models)

   

Personal Profile

• Proactive and detail-oriented
• Thrives in collaborative environments
• Enjoys solving complex integration challenges
• Comfortable experimenting with new technologies
• Committed to improving data systems

Responsibilities

• Design, build, and maintain reliable data pipelines to ingest and process data from external systems
• Implement integrations using Java or Scala, ensuring scalability and resilience
• Handle both full data loads and incremental updates efficiently
• Collaborate with engineering and product teams to align on integration and data needs
• Develop and maintain a unified internal data model
• Ensure data quality, detect and resolve incorrect or incomplete data
• Utilize AI-assisted tools to improve data quality and operational efficiency
• Monitor and optimize data pipelines for production readiness

Are you passionate about building cutting-edge, AI-ready data platforms from the ground up? We are looking for a Senior Data Engineer to join our Data Engineering Team and lead high-impact, greenfield initiatives.

You will work on building modern cloud-native data platforms, migrating on-premises legacy systems to the cloud, and laying the architectural foundation for AI-ready data infrastructure.

In this role, you will collaborate closely with Machine Learning, Data Science, and Product teams, serving as a key technical contributor and thought leader. You will also drive R&D efforts around agentic AI architectures, event-driven systems, and LLM-ready data pipelines — turning architectural concepts into production-grade solutions.

Responsibilities:

• Design and build scalable, cloud-native data platforms from greenfield to production
• Implement near-real-time ingestion pipelines using event-driven patterns
• Define and enforce platform standards, including Data Lake / Lakehouse principles, medallion architecture, and data contracts
• Refactor and optimise existing Spark and PySpark scripts for performance and maintainability
• Introduce best practices for code quality, testing, and CI/CD across data pipelines
• Drive adoption of AI tooling and agentic workflows within the data engineering team
• Ensure data quality, observability, and reliability across all pipelines and platforms

• Develop self-service tooling and microservices to simplify platform usage for other teams

   

Requirements:

• 5+ years of professional experience in Data Engineering
• Strong Python and SQL development skills for pipeline development and optimisation
• Proficiency in Apache Spark / PySpark, including query optimisation and performance tuning
• Hands-on experience with Databricks (preferred) or Snowflake
• Experience with at least one major cloud provider: Azure (preferred), AWS, or GCP
• Experience with stream processing technologies (Kafka, Spark Structured Streaming)
• Solid understanding of ETL/ELT patterns, data modelling (dimensional, Data Vault), and data warehousing
• Experience with orchestration tools (Apache Airflow, Azure Data Factory, or equivalent)
• Knowledge of Infrastructure as Code (Terraform or equivalent)
• Understanding of production-grade system requirements: reliability, scalability, observability, and performance

• Upper-Intermediate English level

   

Will be a plus

• Familiarity with RAG pipeline design and LLM integration patterns
• Knowledge of data governance frameworks and tools (Unity Catalog, Apache Atlas, or similar)
• Experience with dbt for data transformation and modelling

• Familiarity with MLflow, Feature Stores, or ML platform integration

   

Personal profile

• Self-driven and proactive in identifying improvements
• Comfortable working in a fast-paced, innovative environment
• Strong problem-solving mindset with attention to detail
• Open to experimenting with emerging technologies and approaches

_____________________________________________________________

Ти захоплюєшся створенням передових, AI-ready дата-платформ з нуля? Ми шукаємо Senior Data Engineer, щоб ти приєднався(-лася) до нашої команди Data Engineering та очолив(-ла) масштабні, інноваційні ініціативи з нуля.

Ти працюватимеш над побудовою сучасних хмарних дата-платформ, міграцією локальних (on-premises) легасі-систем у хмару та створенням архітектурного фундаменту для AI-ready дата-інфраструктури.

У цій ролі ти тісно співпрацюватимеш з командами Machine Learning, Data Science та Product, виступаючи ключовим технічним експертом та лідером думок. Також ти вестимеш R&D-роботи над agentic AI-архітектурами, подієво-орієнтованими системами та LLM-ready дата-пайплайнами — перетворюючи архітектурні концепції на готові до продакшену рішення.

Обовʼязки:

• Проєктувати та створювати масштабовані, хмарні дата-платформи від концепції до продакшену
• Реалізовувати пайплайни для майже реального часу (near-real-time ingestion) з використанням подієво-орієнтованих патернів
• Визначати та впроваджувати стандарти платформи, включно з принципами Data Lake / Lakehouse, медальйонною архітектурою та дата-контрактами
• Рефакторити та оптимізувати наявні скрипти на Spark та PySpark для підвищення продуктивності та зручності підтримки
• Запроваджувати найкращі практики якості коду, тестування та CI/CD для дата-пайплайнів
• Сприяти впровадженню AI-інструментів та agentic-підходів у команді дата-інженерів
• Забезпечувати якість, спостережуваність (observability) та надійність усіх пайплайнів і платформ

• Розробляти self-service інструменти та мікросервіси, що спрощують використання платформи іншими командами

   

Вимоги:

• 5+ років комерційного досвіду в Data Engineering
• Сильні навички розробки на Python та SQL для створення та оптимізації пайплайнів
• Впевнене володіння Apache Spark / PySpark, включно з оптимізацією запитів та налаштуванням продуктивності
• Практичний досвід роботи з Databricks (бажано) або Snowflake
• Досвід роботи з принаймні одним великим хмарним провайдером: Azure (бажано), AWS або GCP
• Досвід роботи з технологіями потокової обробки даних (Kafka, Spark Structured Streaming)
• Глибоке розуміння ETL/ELT-патернів, моделювання даних (dimensional, Data Vault) та побудови дата-складів
• Досвід роботи з інструментами оркестрації (Apache Airflow, Azure Data Factory або аналогами)
• Знання Infrastructure as Code (Terraform або аналогів)
• Розуміння вимог до продакшен-рішень: надійність, масштабованість, спостережуваність, продуктивність

• Рівень англійської — Upper-Intermediate

   

Буде плюсом:

• Знайомство з проєктуванням RAG-пайплайнів та патернами інтеграції LLM
• Знання фреймворків і інструментів для data governance (Unity Catalog, Apache Atlas або подібних)
• Досвід роботи з dbt для трансформації та моделювання даних

• Знайомство з MLflow, Feature Stores або інтеграцією з ML-платформами

   

Особистий профіль:

• Самомотивованість та проактивність у пошуку покращень
• Комфортна робота у швидкому та інноваційному середовищі
• Сильне аналітичне мислення та увага до деталей
• Відкритість до експериментів з новими технологіями та підходами

We are looking for a Senior Data Engineer. This is not a standard ETL role. You will work on a high-load system processing 10,000+ executions per minute, building scalable pipelines where AI and LLM logic are embedded directly into production data flows.

The role combines data engineering, backend thinking, infrastructure ownership, and real production AI integration.

What you will do:

• Design and maintain scalable data pipelines in Python on Google Cloud Platform
• Build and optimize AI-driven scoring flows using LLMs for real-time identity enrichment
• Work with BigQuery, Apache Spark, and Apache Iceberg for heavy data processing
• Maintain high-load orchestration with custom Python nodes and complex workflows
• Own deployment and release processes (CI/CD)
• Optimize PostgreSQL performance under heavy load
• Investigate incidents and resolve root causes permanently

• Use AI engineering tools such as Claude in daily development

   

Requirements:

• 4+ years of experience in Data Engineering / Backend Engineering
• Strong Python skills
• Commercial experience with production LLM integration (OpenAI / Anthropic / Gemini)
• Strong knowledge of GCP (Cloud Functions, IAM, Networking)
• Experience with BigQuery, Spark, Iceberg
• Good understanding of Kubernetes
• Experience with workflow orchestration tools (n8n is a strong plus)
• Strong practical knowledge of PostgreSQL

• English level B2+

   

What is important for us:

• Ownership mindset
• Fast learning ability
• Strong problem-solving approach
• Active AI usage in engineering work
• Focus on practical results over unnecessary complexity

We are looking for a Data / Backend Engineer to architect and scale the core data infrastructure behind our healthcare marketing platform. In this role, you will design high-throughput data systems that process millions of behavioral events, power real-time attribution and user scoring, and enable precise targeting of healthcare professionals across 20+ channels.

You will work at the intersection of data engineering, backend systems, and marketing infrastructure, building scalable pipelines, tracking systems, and APIs that support analytics, segmentation, and campaign activation. The role also involves experimenting with AI-powered automation and agent-based workflows to improve internal operations and product capabilities.

This is a high-ownership position where you will shape architecture decisions, build critical platform components from the ground up, and help evolve our data platform as the company scales.

Responsibilities

- Architect and own data-heavy backend systems powering real-time attribution, user modeling, and scoring

- Build and evolve client-side tracking pixels (like FB pixel / Amplitude snippet / Heap autocapture) from scratch

- Set up and manage scalable ETL workflows: cleaning, merging, enriching, splitting, transforming across millions of behavioral events
Lead the build of CDP / CDXP-style data layers to support segmentation, scoring, and activation across channels

- Connect and compose systems using modern low-code / no-code tools (n8n) to accelerate ops

- Implement and maintain high-availability APIs for analytics, scoring, and campaign delivery

- Drive experimentation around AI-powered agents and automation tools that can boost internal workflows

Requirements

- System Design & Data Architecture:
Designs scalable, event-driven data platforms with strong decoupling, fault tolerance, and horizontal scalability. Builds real-time and batch pipelines using lakehouse architectures and streaming systems (Kafka / PubSub).

- Distributed Data Processing (Spark / BigQuery / Iceberg):
Expert in large-scale data processing, query optimization, and cost-efficient analytics. Deep understanding of Spark execution, partitioning, and modern table formats (Iceberg / Delta).

- Cloud & Infrastructure (GCP / Kubernetes):
Builds resilient cloud-native data platforms on GCP and Kubernetes using IaC, autoscaling, and secure access (IAM, Workload Identity).

- Python Engineering:
Develops high-performance Python services for data and ML workloads with focus on concurrency, clean architecture, and production-grade quality.

- Databases & Performance (PostgreSQL / OLTP):
Optimizes high-throughput OLTP systems through indexing, partitioning, and query analysis (EXPLAIN ANALYZE, MVCC).

- Reliability & Observability (SRE):
Implements resilient data systems with idempotency, retries, observability, SLOs, and incident management.

- AI / LLM Integration:
Integrates LLMs into production pipelines with structured outputs, caching, batching, prompt versioning, and evaluation.

- Workflow Orchestration (Airflow / Dagster):
Designs scalable DAG-based workflows with dependency management, retries, and reproducible backfills.

- CI/CD & DevOps for Data:
Implements safe deployments for data systems including schema migrations, canary releases, and data contracts.

- Ownership & Engineering Maturity:
Owns end-to-end production systems and architecture decisions while balancing delivery speed, quality, and technical debt.

Nice-to-have: 

- Experience in MarTech / AdTech platforms (e.g., DSPs, attribution systems, DMP/CDP tools)

- Deep knowledge of data matching/fingerprinting techniques (identity graphs, IP + UA resolution, hashed PII workflows)

- Strong prompt engineering skills — not just ChatGPT 101, but chaining, system prompting, tooling integration

What We Offer
- Fully remote with flexible hours (aligned with EU timezones for syncs).
- Influence on quality strategy across the entire engineering organization.
- A cross-team role with visibility into every part of the product.
- AI-first tooling.
- Claude Code licenses and cutting-edge AI development workflows. 
- A team with no bureaucracy, decisions are made fast.

We are looking for a Senior Data Engineer to join the Identity team at Equals5. 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.
   

What We Offer

• Fully remote with flexible hours (aligned with EU timezones for syncs).
• AI-Native Environment: We provide licenses for Claude Code and encourage using the bleeding edge of AI tech for both daily coding and product features.
• High-Impact Role: You will directly influence how we identify and score users, impacting the core business logic.
• Cross-functional visibility: Work closely with Product and Tech Leads to shape the future of Identity.
• No Bureaucracy: Fast decisions, no legacy processes, focus on results.

Dataforest is looking for a Data Engineer to join an interesting software development project in the field of Cybersecurity. Our client’s platform offers Identity Insights drives real-time, multi-contextual digital forensics to protect new account opening workflows and expose fake accounts already in a customer database.

Requirements:
• 3+ years of hands-on experience in data engineering;
• 3+ years of commercial experience with Python;
• Advanced experience with SQL DBs (optimisations, monitoring, etc.);
• Advanced experience with PySpark;
• Solid understanding of ETL principles (architecture/ monitoring/ alerting/search and resolve bottlenecks);
• Familiar with AWS infrastructure (boto3, S3 buckets, etc);
• Experience working with large volumes of data;
• Understanding the principles of medallion architecture.

Responsibilities:
• Maintain data processing architecture using Python and PySpark that interacts with ScyllaDB & PostgreSQL.
• Work with Databricks infrastructure to ensure reliability, scalability, and cost efficiency.
• Proactively identify bottlenecks and suggest technical improvements.

Nice to have:

• Cassandra/Scylla

• PostgreSQL

• Pandas

• Experience with Kafka and Redis

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.

We are seeking an experienced Senior Data Engineer to help build and scale modern data platforms that power analytics, reporting, and data-driven decision-making. In this role, you will work with cloud-based data ecosystems, leveraging Databricks and Spark technologies to process large volumes of data and deliver high-performance solutions across the organization.

You'll collaborate closely with engineering teams, analysts, and business stakeholders to design robust data architectures, improve data reliability, and support mission-critical initiatives.

Key Responsibilities

• Design, develop, and maintain scalable data pipelines and processing frameworks.
• Create and optimize ETL/ELT workflows for efficient data ingestion and transformation.
• Work with high-volume datasets in distributed computing environments.
• Develop data models, transformation logic, and integrations across multiple systems.
• Partner with cross-functional teams to understand data requirements and deliver reliable solutions.
• Monitor and improve data quality, platform performance, and operational stability.
• Contribute to architecture decisions and implement data engineering best practices.
• Support cloud-based data infrastructure and continuous improvement initiatives.

Required Qualifications

• 7+ years of professional experience in Data Engineering.
• Proven hands-on expertise with Databricks in production environments.
• Strong experience with Apache Spark and PySpark.
• Advanced SQL skills with a focus on performance optimization.
• Solid background building and maintaining ETL/ELT processes.
• Strong Python development experience.
• Experience working with large-scale data processing and analytics platforms.
• Hands-on experience with at least one major cloud provider (AWS, Azure, or GCP).
• Professional proficiency in both English (C1) and Russian (C1).
• Strong problem-solving skills and ability to work independently in a remote environment.

Contract Details

• Full-time engagement under a B2B agreement.
• Long-term, open-ended collaboration.
• Monthly gross compensation.
• Payments made to the contractor's registered business account (FOP / Sole Proprietorship / equivalent).
• Contractor is responsible for managing and paying their own taxes.
• Standard 8-hour workday.
• 30-day notice period.

Nice to Have

• Experience designing data lake or lakehouse architectures.
• Familiarity with data governance, monitoring, and observability tools.
• Experience supporting analytics, BI, or machine learning workloads.

If you have a strong background in Databricks and large-scale data engineering and are looking for a long-term remote opportunity, we'd love to hear from you.

We are a product company building AI-powered mobile applications used by over 10 million people in 150 countries. We own the entire product lifecycle — from the initial idea to large-scale global implementation. We thrive in a fast-paced environment, making data-driven decisions without unnecessary bureaucracy. If you value autonomy, rapid releases, and seeing the direct impact of your work, you will fit right in.
 

The Role

We are looking for a Senior DevOps Engineer to take full ownership of the infrastructure for our ambitious new project in the Cloud Gaming & Streaming space. Your primary mission is to build a high-performance, fault-tolerant system capable of handling massive loads and streaming content to thousands of concurrent users.
 

Work Format & Relocation

• Location: Dubai, UAE (Office).
• Trial Period: First 2–3 months are fully remote for a smooth onboarding.
• Relocation Support: Full corporate visa sponsorship and relocation support provided after the trial period.

Key Responsibilities

• Ensure high availability and seamless scalability of infrastructure supporting thousands of servers.
• Automate server setup, provisioning, and deployment using Terraform and modern configuration management tools.
• Architect and optimize systems for high-load, distributed streaming environments.
• Drive incident response, monitoring, and troubleshooting to maintain product stability.
   

Requirements

• Experience: 4+ years in a DevOps role with hands-on experience in supporting high-load systems.
• OS Expertise: Deep understanding and practical experience in both Linux and Windows administration.
• Architecture: Experience with microservices, containerization, and distributed systems.
• IaC & Automation: Proficiency in Terraform and strong scripting skills for server auto-setup.
• Language: English (Upper-Intermediate or higher, sufficient for technical collaboration).
   

Nice-to-have

• Understanding of data streaming principles and previous experience in the streaming or gaming field.
• Basic knowledge of C++ development to collaborate effectively with the core infrastructure team.
   

What We Offer

• Relocation Package: Full financial and organizational support for your move to Dubai (visa, tickets, initial housing) after the trial period.
• Modern Office: Work from a vibrant, tech-driven workspace in Dubai with a multinational team.
• Real Impact: Direct influence on the tech stack of a Cloud Gaming platform with a potential million-user audience.
• Ownership: Maximum autonomy in choosing tools and approaches to solve complex challenges.
• Fast-Paced Culture: A product-driven environment where decisions are made quickly, without micromanagement.
• Compensation: Competitive salary pegged to USD (to be discussed individually based on technical interview results).

Full-time · Remote · Start: ASAP (3–4 weeks)

About the role

We're building a social commerce platform for the Middle East — live shopping, real-time auctions, and community-driven discovery in one place. Think TikTok Shop meets eBay Live, built for a market that moves fast.

We need a hands-on engineer to own our entire data and automation engine: from raw behavioral events to personalized recommendations, automated lifecycle messaging, and production AI. This is not a research role. You will ship things that directly drive revenue and retention.

What you'll own

Data platform & warehouse Design and maintain our central OLAP warehouse (ClickHouse or equivalent). Build reliable ingestion pipelines. Be the person who ensures clean, trusted data across the organization.

Behavioral event tracking Instrument mobile and web apps to capture the full user journey — watch time, bid activity, follows, purchases. Own identity resolution across sessions and devices.

Growth data activation Build reverse ETL pipelines from the warehouse into ad platforms and marketing tools: Meta CAPI, Google Ads, Braze, Customer.io, WhatsApp API. Automate audience sync and campaign triggers.

Lifecycle automation & personalization Design behavior-based trigger logic (cart abandonment, livestream reminders, re-engagement flows). Build ranking and recommendation models for products and live shows.

Production AI integration Deploy LLM-powered workflows for seller onboarding, content moderation, and customer support automation. Own cost controls, evaluation pipelines, and reliability of these systems in production.

Requirements

• 7+ years in data engineering, software engineering, or data architecture
• Production-grade Python and SQL — you write code that runs in prod, not notebooks
• Proven experience building OLAP warehouses: ClickHouse, BigQuery, Snowflake, or Redshift
• Experience with event tracking and identity resolution: Segment, RudderStack, PostHog, or similar
• Experience connecting warehouses to marketing/CRM tools via Reverse ETL: Hightouch, Census, or direct integrations
• Shipped LLMs or RAG systems in production — demos and side projects don't count
• Strong communication: you can explain data trade-offs to non-technical stakeholders clearly

Nice to have

• Background in e-commerce, marketplaces, or consumer apps
• Experience with recommendation systems, personalization algorithms, or vector databases
• Familiarity with real-time streaming metadata (LiveKit, WebRTC)

Stack you'll work with

ClickHouse · Python · dbt · Segment / RudderStack · Meta CAPI · Braze · Customer.io · Hightouch · OpenAI / Anthropic APIs · vector databases

Why this role

• You'll be the first dedicated data/AI engineer — high ownership, high impact
• Fast-growing market with real behavioral data from day one
• Direct line to product and business decisions
• Competitive compensation, remote-friendly

We are seeking a Site Reliability Engineer; this is a fully remote job in the European time zone.

What You'll Be Doing

• Configuring and optimizing Nginx, php-fpm, PostgreSQL, ElasticSearch, Redis, RabbitMQ in production (daily routine)
• Monitoring system health with Prometheus, Victoria Metrics, Icinga, Opsgenie, Jira Service Management (daily routine)
• Managing cloud infrastructure: compute, storage, IAM, VPCs, load balancers
• Ensuring high availability and responding to incidents
• Participating in monthly on-call rotation (1 shift/month, 24h, with compensating days off)

Must Have

• Linux (RHEL) is required
• TCP/IP networking, firewalls, routing, load balancing
• Production experience with Nginx, php-fpm, PostgreSQL, ElasticSearch, Redis, RabbitMQ
• Monitoring stack: Prometheus, Victoria Metrics, Icinga, Opsgenie
• Cloud infrastructure management (any major cloud)
• English - Upper-Intermediate spoken (required)

Nice to Have

• Terraform, Ansible, Jenkins, GitLab CI
• Docker, Kubernetes, Helm
• Puppet DSL, PuppetDB
• ELK / OpenSearch stack

Conditions

• FOP contract
• Schedule: local business hours, Mon–Fri + 1 on-call shift/month (24h) with 2 compensating days off
• 24 vacation days/year

About PredictSpring

PredictSpring is a market-leading company shaping the future of omni-channel retail and modern POS technology. We help global retail and lifestyle brands deliver seamless, modern, and data-driven customer experiences across digital and in-store channels.

We are looking for a highly skilled Senior AI/ML Engineer – GenAI to design, develop, and deploy enterprise-grade AI solutions with a strong focus on Generative AI, Large Language Models, Retrieval-Augmented Generation, and Agentic AI systems.

In this role, you will build production AI applications, multi-agent workflows, scalable ML pipelines, and cloud-native AI solutions that create business value across our platform and operations.
 

Responsibilities

As a Senior AI/ML Engineer – GenAI, you will:

• Design, develop, and deploy enterprise Generative AI applications using foundation models such as GPT, Claude, Gemini, Llama, Mistral, and other open-source LLMs.
• Build advanced RAG solutions using vector databases, embeddings, reranking techniques, and hybrid search architectures.
• Develop prompt engineering strategies, evaluation frameworks, guardrails, and hallucination mitigation techniques.
• Fine-tune and optimize LLMs using techniques such as LoRA, QLoRA, PEFT, and reinforcement learning approaches.
• Integrate LLMs with enterprise applications, APIs, databases, and business workflows.
• Design and implement autonomous and semi-autonomous AI agents capable of reasoning, planning, memory management, tool usage, and workflow orchestration.
• Build multi-agent systems using frameworks such as LangGraph, LangChain, AutoGen, CrewAI, Semantic Kernel, MCP, A2A, or similar technologies.
• Build and maintain end-to-end machine learning pipelines, including data ingestion, feature engineering, model training, evaluation, deployment, and monitoring.
• Develop predictive models, recommendation systems, anomaly detection solutions, NLP applications, and deep learning models.
• Design CI/CD pipelines for machine learning and AI applications.
• Deploy and manage AI workloads using Docker, Kubernetes, and cloud-native services.
• Monitor model drift, performance degradation, latency, and data quality.
• Architect cloud-native AI solutions on AWS, Azure, or Google Cloud Platform.
• Partner with product managers, software engineers, data engineers, and business stakeholders to translate business requirements into AI solutions.
• Mentor junior engineers and contribute to architecture reviews, technical strategy, and AI best practices.

Requirements

We are looking for someone with:

• Upper C1 or higher English proficiency, with fluent spoken and written English.
• Ability to confidently participate in client-facing discussions, technical workshops, architecture reviews, stakeholder presentations, and cross-functional collaboration.
• Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Data Science, Machine Learning, Engineering, or a related field.
• 7+ years of software engineering, machine learning, or AI experience.
• Minimum 3+ years of hands-on experience developing and deploying Generative AI applications in production environments.
• Strong Python programming skills with experience building scalable backend systems.
• Extensive experience with machine learning frameworks including PyTorch, TensorFlow, scikit-learn, and Hugging Face.
• Proven experience developing RAG architectures and knowledge retrieval systems.
• Experience building Agentic AI solutions and multi-agent workflows.
• Strong understanding of vector databases, embeddings, semantic search, and retrieval optimization.
• Experience with cloud platforms including AWS, Azure, or GCP.
• Strong understanding of MLOps principles, CI/CD, containerization, and model lifecycle management.

Preferred Qualifications

Nice to have:

• Experience with managed AI services such as AWS SageMaker, AWS Bedrock, Azure OpenAI, Azure ML, or Vertex AI.
• Experience with distributed computing platforms such as Databricks, Spark, or Ray.
• Experience with AI governance, responsible AI practices, model monitoring, and production AI observability.
• Experience with secure AI architectures, role-based permissions, auditability, and compliance controls.
• Experience in retail, e-commerce, omni-channel commerce, or POS technology is a strong plus.

Why PredictSpring?

• Join a market-leading company shaping the future of omni-channel retail and modern POS.
• Work on high-impact challenges at the intersection of commerce, data, AI, and customer experience.
• Collaborate with a talented global team in a flexible remote work environment.
• Enjoy opportunities for growth, learning, and professional development.
• Contribute to products used by some of the world’s most recognized retail and lifestyle brands.
• Be part of an innovative, collaborative, and data-driven culture focused on delivering measurable business value.

About the Project

Client is undergoing a large-scale Identity & Access Management transformation program as part of its alignment with Allianz Group standards.The initiative aims to establish a centralized Identity Governance and Administration (IGA) platform across multiple portfolio companies, replacing fragmented identity management approaches with a unified governance model.The selected candidate will play a key role in defining the business role model, capturing authorization requirements, supporting role design activities, and working closely with business stakeholders throughout the IAM transformation journey.

We are looking for an experienced IAM Business Engineer to act as the bridge between business stakeholders and the IAM program team.The primary focus of this role is to understand how access and authorization are currently managed across portfolio companies, define the future business role model, contribute to Segregation of Duties (SoD) controls, and support the rollout of the centralized IAM solution. This is a highly stakeholder-facing role with a strong emphasis on analysis, workshops, documentation, role modelling, and governance rather than technical implementation.

Responsibilities:

Business Role Modelling

• Design and maintain the enterprise business role model
• Define authorization concepts and role structures
• Create and maintain entitlement catalogues
• Support business role lifecycle management

Requirements Gathering

• Conduct workshops with business stakeholders and application owners
• Capture current access management practices and authorization requirements
• Analyze existing role structures across portfolio companies
• Identify common patterns and opportunities for standardization

IAM Governance & SoD

• Contribute to Segregation of Duties (SoD) matrix development
• Support access governance activities
• Identify conflicting access rights and governance risks
• Assist with access review and certification concepts

Stakeholder Management

• Collaborate with business owners across multiple portfolio companies
• Facilitate discussions regarding role design and access requirements
• Align stakeholders on future-state IAM processes and role concepts
• Support communication and change management activities

Migration & Adoption Support

• Support portfolio companies during migration to the centralized IAM platform
• Help stakeholders understand new role concepts and governance requirements
• Participate in role-mapping and transition activities
• Assist with adoption and rollout activities

Required Experience:

• 5+ years of experience in Identity & Access Management, Access Governance, or Role Management
• Proven experience designing RBAC models and business roles
• Experience gathering requirements from business stakeholders
• Experience conducting workshops and stakeholder interviews
• Understanding of access governance principles and role engineering
• Experience with Segregation of Duties (SoD) concepts
• Strong documentation and analytical skills

Preferred Experience

• Experience with Identity Governance & Administration (IGA) programs
• Experience with One Identity, SailPoint, Entra ID, or similar IAM platforms
• Experience with role mining activities
• Experience in enterprise IAM transformation initiatives
• Experience working in multi-company or multinational environments