Jobs Data Engineer

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: 
The platform processes 50 TB+ of raw data daily, handles 4M+ requests/second, and reaches over 1 billion unique users weekly. As a DataOps Engineer, you will be the reliability guardian of this data ecosystem - catching issues before they hit production, responding to operational incidents, and building the automation and infrastructure that keeps everything running.

About the role:

We’re looking for a DataOps Engineer who will focus on data reliability, monitoring, and quality across production pipelines.
 

This role combines:

• proactive work (building monitoring, improving pipelines, adding tests)
• reactive work (handling alerts, debugging issues, fixing incidents)

You’ll be responsible for keeping data pipelines stable, accurate, and transparent for downstream teams.
 

What you’ll do:

• Build and maintain monitoring & alerting for data pipelines (freshness, accuracy, health)
• Detect anomalies and investigate issues before they affect business
• Implement data quality checks, validation rules, and automated tests
• Troubleshoot incidents, find root causes, and document solutions
• Work with Airflow, Python, and SQL for operational tasks and fixes
• Maintain metadata and documentation (tables, lineage, sources)
• Improve performance and reliability of existing pipelines
• Collaborate with Data Engineers and business stakeholders
   

Requirements:

• 3+ years in Data Engineering / DataOps / similar roles
• Strong Python + SQL
• Hands-on experience with Airflow
• Experience with PySpark
• Experience with data warehouses (MySQL, Presto, Athena or similar)
• Experience with monitoring / observability / alerting tools
• Strong focus on data quality and reliability
• English for daily communication
   

Nice to have:

• DevOps or NOC background
• Experience with data governance / metadata tools
• Familiarity with tools like Great Expectations, dbt tests, Monte Carlo
   

Working setup:

• Hybrid format: Kraków office (~10 days/month)
• Small, experienced team with high ownership
• English-speaking environment
   

What we offer:

• Up to $5000 salary
• 20 paid vacation days + public holidays
• Fully covered accounting & legal support
• Equipment and co-working support if needed
• Regular compensation reviews

Company: Interexy

 Location: Hybrid / Remote Job

 Type: Full-time

 About Us: Interexy (https://interexy.com/) is a global custom software development and IT consulting company founded in 2017 and headquartered in Miami. We deliver innovative solutions for giants like SAP, PwC, and General Electric, with deep expertise in AI, ML, Blockchain, and FinTech. As we expand our AI Agent Development department, we need an AI/ML Engineer who takes full ownership — we don't build demos, we ship high-performance, production systems for enterprise clients.

We expect from you:

• At least 2 years of experience developing ML solutions.
• Deep knowledge of:
  • Linear algebra,
  • Probability theory,
  • Mathematical statistics.
• Strong proficiency in Python:
  • NumPy, Pandas, SciPy, scikit-learn.
• Understanding and practical experience with ML algorithms:
  • Collaborative filtering,
  • Content-based filtering,
  • Embeddings,
  • Gradient boosting, neural networks.
• Strong knowledge of SQL.
• Experience with Python backend (FastAPI).
• Understanding of high-load system design and microservice architecture.
• Experience building recommender systems.
• Experience with big data tools:
  • Spark, Kafka, Airflow, ClickHouse, Elasticsearch.
• Experience with deep learning (PyTorch / TensorFlow).
• Experience with A/B testing and model quality evaluation (precision, recall, NDCG, MAP).
• Experience with Docker, Kubernetes.
• Understanding of MLOps (ML pipelines, model deployment, monitoring).

Responsibilities:

• Designing and developing recommendation algorithms for music content.
• Building ML models and feature engineering.
• Integrating ML models into Python backend and product services.
• Optimizing recommendation quality and system latency.
• Analyzing user behavior and musical preferences.
• Developing and maintaining ML pipelines (training, testing, deployment).
• Running experiments and A/B tests.
• Participating in architectural decisions for the recommendation engine.
• Documenting solutions and collaborating with the backend team.

We are building a next-generation, adaptive route planning engine designed for extreme logistics complexity. Unlike traditional static optimization models, our system evolves by learning from human expertise. We capture the manual adjustments made by dispatchers and transform that “implicit knowledge” into scalable algorithmic assets.

We are looking for a versatile Data Scientist who thrives at the intersection of Optimization (OR) and Machine Learning. You will own the full ML lifecycle—from deep-dive data analysis and sophisticated feature engineering to selecting and implementing the right architectures (from Decision Trees to Transformers/RL) to bridge the gap between automated planning and human intuition.

Details: 
Start: ASAP 
Experience: 4+ years 
Schedule: Full time remote 
Mode: Fist 1-2 months - part time with future allocation to full time mode.

Key Responsibilities
Human-in-the-Loop Learning: Develop models that analyze the delta between algorithmic outputs and manual human corrections to “learn” implicit constraints and preferences.
Complex Constraint Satisfaction: Work on Large-scale Vehicle Routing Problems (VRP) involving multi-layered constraints and complex clustering.
End-to-End ML Ownership: Lead the entire pipeline: sophisticated data normalization, advanced feature engineering, model selection, training, and evaluation.
Strategic Analytics: Implement analytical frameworks (e.g., Balanced Scorecard approaches) to quantify performance and align model behavior with business KPIs.
Algorithmic Research: Experiment with diverse approaches including Gradient Boosted Trees, Attention mechanisms, and potentially Reinforcement Learning to capture the nuances of logistics planning.

Required Qualifications
Experience: 4+ years of experience as a Data Scientist or ML Engineer, with a proven track record of taking models from research to production.
Optimization Expertise: Strong understanding of optimization problems (VRP/TSP), heuristics, and working with complex constraints. Familiarity with tools like Google OR-Tools is a major plus.
Machine Learning Depth: Solid grasp of supervised learning and a willingness to explore Imitation Learning or RL.
Feature Engineering Mastery: You believe that data preparation and creative feature engineering are the keys to a model’s success. Expert-level Python and SQL skills are a must.
Architectural Flexibility: Ability to match the right tool to the problem—whether it’s a simple Decision Tree for early-stage wins or a Transformer-based architecture for complex sequence modeling.
Analytical Mindset: Experience in defining and tracking complex metrics; ability to perform “smart analysis” to find patterns in human behavior.

Bonus Points
Experience in the logistics or supply chain domain.
Background in Geospatial data.
Experience with Cloud Infrastructure (AWS Bedrock, SageMaker, etc.).

We are looking for an experienced Data Engineer to support an AI related project for a corporate client.

The consultant will work together with Python Backend and DevOps specialists to build and support the data foundation for an AI driven solution.
 

Project context

The client is preparing an AI initiative and is looking for external expert support. The final architecture is still being clarified, but the project requires strong data engineering skills and the ability to work in a modern cloud based environment.
 

Responsibilities

• Design, build and maintain data pipelines
• Support data processing and transformation for AI related use cases
• Work closely with backend and DevOps specialists
• Ensure data quality, reliability and maintainability
• Support integration between backend systems, data layers and cloud infrastructure
• Participate in technical discussions and project clarification
   

Requirements

• Strong experience as a Data Engineer
• Experience with Python and data processing workflows
• Good understanding of data pipelines, ETL / ELT and data architecture
• Experience with cloud environments, ideally AWS or Azure
• Experience with AI, ML or analytics projects is a plus
• Good communication skills
• Ability to work independently in a consulting setup
• Fluent English communication

CrunchCode — міжнародна сервісна ІТ-компанія з досвідом близько 7 років у розробці вебсервісів і вебзастосунків. Ми працюємо у форматах staff augmentation (outstaff) та outsourcing і підключаємо спеціалістів до проєктів клієнтів у довгостроковій моделі співпраці.

Ми працюємо переважно з проєктами в доменах логістики (включно з last mile),e-commerce, fintech та банкінгу, а також enterprise-рішеннями.
Для нас важливо, щоб проєкт був “чистим” і зрозумілим з точки зору етики та цінності для користувачів.

Ми принципово не беремо проєкти, пов’язані з:
● gambling / гемблінгом,
● adult-контентом та порнографією,
● шахрайством або будь-якою розробкою, що спрямована на обман чи маніпуляції.

What We Offer:
● Fully remote work
● Long-term, stable project
● High level of autonomy and trust
● Minimal bureaucracy
● Direct impact on business-critical logistics systems
● Long-term engagement, not a short-term contract.

Project Overview

High-scale enterprise data warehouse migration from Vertica to Snowflake. The scope covers migrating large data volumes (terabytes), redesigning and rewriting ETL / data loading pipelines, and ensuring scalable, high-performance data processing. 

Tech Stack: Snowflake · Vertica · ETL · SQL · SnowConvert · Data Warehousing

Requirements (Must-have):

• 5+ years of experience in data warehouse migrations
• Strong hands-on Snowflake experience — required
• Strong relational DB and SQL transformation expertise
• Ability to work independently and mentor others
• Location: Baltics (preferred) or nearshore
  
  Responsibilities:
• Migrate data from Vertica to Snowflake at enterprise scale (terabytes)
• Redesign and rewrite ETL / data loading scripts
• Ensure scalable, high-performance data processing
• Use tools like SnowConvert where relevant
• Mentor other team members
  
  Nice to Have:
• Vertica experience
• Experience with SnowConvert or similar migration tooling
  
  Hiring Process:
  Intro call → Technical discussion → Offer

Project Description
Our customer (originally the Minnesota Mining and Manufacturing Company) is an American multinational conglomerate operating in the fields of industry, worker safety, and consumer goods. Based in the Saint Paul suburb of Maplewood, the company produces over 60,000 products, including adhesives, abrasives, laminates, passive fire protection, personal protective equipment, window films, paint protection film, electrical, electronic connecting, insulating materials, car-care products, electronic circuits, and optical films.

Job Description

• 5+ years in Quality Assurance with a proven track record in Data Warehousing and ETL testing.
• Advanced ability to write complex queries to audit data logic.
• Proficiency in Python to automate data validation tasks and compare large datasets programmatically.
• Deep understanding of data-specific concepts like schema evolution, data truncation, null handling, and referential integrity.
• Solid experience working in fast-paced Scrum environments and understanding the QA lifecycle within short delivery sprints.
• High-level professional proficiency in English (written and verbal) for technical documentation and stakeholder communication.
• Strong problem-solving skills with the ability to identify "the needle in the haystack" within millions of rows of data.

Nice-to-Haves:

• Hands-on experience using Databricks for data exploration, running SQL/Python notebooks, and verifying complex table schemas.
• Experience using Azure DevOps (AzDO) or Jira for test case management and bug tracking.
• Familiarity with Azure services (Function apps, ADLS etc).
• Experience in testing web services/APIs.

Job Responsibilities

• Create comprehensive manual and automated test plans tailored to ETL workflows and Data Warehouse architectures.
• Perform rigorous testing to ensure data flows correctly and accurately from diverse source systems to target tables
• Design and implement automation scripts to validate data integrity, completeness, and transformation logic at scale.
• Identify and track data discrepancies, collaborating closely with Data Engineers to perform root-cause analysis on failures.
• Actively participate in Scrum ceremonies to refine requirements, estimate data-related tasks, and provide quality-based recommendations

Location: Remote (Europe-based Ukrainian candidates only)

Project Sector: EnergyTech (Iceland)

Experience: 3–5 years

English Level: Upper-Intermediate / Advanced
 

ABOUT OUR CUSTOMER

It is a European company building exciting new products from scratch for startups and helping mature companies in their journey towards data-driven innovation and AI-based solutions. Their expertise spans EnergyTech, FinTech, ClimateTech, and more.

Founded in Ukraine and developed based on Scandinavian culture, HBM is hiring both in Ukraine and the EU. We combine the agility of a startup with a human-oriented leadership team and a strong focus on work-life balance.
 

PROJECT OVERVIEW

Our customer is a leading Icelandic energy company providing electricity, geothermal water, and carbon storage. We are looking for a Middle Data Engineer with a focus on support and optimization.

Unlike a typical "build-from-scratch" role, this position is centered around maintaining and stabilizing a complex DWH ecosystem. You will be the "guardian" of data flow, ensuring that daily operational pipelines run reliably and investigating failures in the legacy and modern stack.
 

TECH STACK

• Platforms: SQL Server, Azure
• BI Stack: Microsoft BI (SSRS, SSIS, SSAS — Olap and Tabular), Power BI, Tableau
• Tools: TimeXtender, exMon (monitoring)
• Languages: SQL (primary), Python, PowerShell
   

CHALLENGES & RESPONSIBILITIES

• Pipeline Troubleshooting: Investigating failed ETL tasks, timeouts, and execution errors.
• Root Cause Analysis: Identifying why data extractions from in-house systems (like SCADA) fail and fixing them.
• Monitoring: Working with exMon to resolve warnings and ensure data consistency in business-critical tables.
• DWH Maintenance: Correcting configuration issues in pipeline parameters, schedule triggers, or source/target connections.
• Collaboration: Working closely with the Icelandic on-site team and the Data Engineering Lead in an Agile environment.
• Documentation: Updating Jira tickets with clear English descriptions of problems and resolutions.
   

REQUIREMENTS

• Experience: 3–5 years of commercial experience with DWH solutions and data pipelines.
• SQL Mastery: Strong debugging skills, specifically with MS SQL Server.
• ETL Expertise: Solid experience with ETL/ELT workflows (SSIS, ADF, or similar).
• Analytical Mindset: Ability to parse log outputs, identify root causes, and correct code-level issues.
• DWH Concepts: Deep understanding of fact tables, dimensions, and staging layers.
• Soft Skills: Proactive "action-oriented" approach and the ability to communicate effectively with stakeholders.
• Language: Upper-Intermediate or Advanced English.
• Location: You are a Ukrainian currently residing in Europe.
   

NICE TO HAVE

• Experience with Python or PowerShell for data processing and automation.
• Background in the Energy sector or working with IoT/SCADA data.

RECRUITMENT PROCESS

1. HR Interview (30 min)
2. Managerial Interview (30 min)
3. Technical Interview (1.5 hours)
4. Customer Interview (30–45 min)
    

WE OFFER

• Long-term engagement with a stable Icelandic partner.
• A flat organization where your voice is heard.
• Flexible remote work from anywhere in Europe.
• Competitive compensation and a focus on well-being.
• Professional growth within a team that values Scandinavian work culture.

Senior Data Engineer (Python)

Builds one of the world’s largest property intelligence datasets by processing satellite and street-level imagery across the entire United States.

We are looking for a Senior Python Data Engineer to design and operate large-scale data pipelines that generate property attributes from imagery using internal AI models.

This role focuses on building distributed processing systems running on Kubernetes clusters and on-prem GPU infrastructure, capable of processing massive geospatial datasets at national scale.

You will work closely with AI engineers and SaaS platform teams to build robust pipelines that transform imagery into structured property intelligence used by the insurance and financial industries.

 

Responsibilities

• Design and build large-scale Python processing pipelines for satellite and street-level imagery

• Develop distributed workloads running on Kubernetes clusters

• Build and maintain orchestration workflows using Airflow

• Design and manage data storage and processing workflows using PostgreSQL

• Process geospatial datasets using GeoPandas, GDAL, Shapely, or similar tools

• Integrate large-scale AI inference pipelines running on GPU infrastructure

• Optimize processing performance for massive imagery datasets

• Improve observability, monitoring, and reliability of production pipelines

• Collaborate with AI engineers to support large-scale computer vision inference workflows

• Integrate pipelines with AWS-based services

 

Requirements

• 7+ years of Python engineering experience

• Strong experience designing distributed data pipelines or large-scale data processing systems

• Experience running workloads on Kubernetes

• Hands-on experience with Airflow or similar orchestration frameworks

• Experience processing large datasets (imagery, geospatial, or other high-volume data)

• Strong understanding of ETL architectures and distributed data systems

 

Nice to Have

• Experience with geospatial processing (GeoPandas, GDAL, Rasterio, Shapely)

• Experience working with satellite imagery, aerial imagery, or remote sensing datasets

• Experience with GPU-based inference pipelines

• Experience with distributed processing frameworks such as Spark, Ray, or Dask

• Experience working with on-prem compute clusters

• Experience with C#

 

Why Join

You will be working on a platform that processes imagery data at national scale to generate property intelligence for the insurance and financial industries. The system analyzes hundreds of millions of properties using AI and geospatial processing, creating one of the most comprehensive property datasets in the world.

AWS Cloud Engineer

Softprom Solutions
Azerbaijan | Remote / Hybrid
Full-time | Contractor (Individual Entrepreneur)
Contract with Austria

About Softprom

Softprom Solutions is an international IT distributor and solutions provider working with leading global vendors in Cloud, Cybersecurity, Infrastructure, and Enterprise IT.

We are expanding our Cloud Practice and are looking for an AWS Cloud Engineer in Azerbaijan who wants to grow professionally, work on real customer projects, and collaborate with international teams under an Austrian contract.

About the role

This role is ideal for an AWS-certified engineer with solid fundamentals who wants to deepen hands-on experience in cloud architecture, deployments, automation, and customer-facing work.

You will work closely with senior architects, sales teams, and customers, participating in both technical delivery and pre-sales activities.

Responsibilities

• Support the design and documentation of AWS cloud architectures following the AWS Well-Architected Framework
   
• Participate in deployment and configuration of core AWS services, including
  VPC, EC2, S3, RDS, IAM, Lambda, Load Balancers
   
• Assist with AWS networking configuration:
  Subnets, Route Tables, Security Groups, NACLs
   
• Contribute to automation and Infrastructure as Code (IaC) initiatives using
  Terraform and/or AWS CloudFormation
   
• Create and maintain technical documentation for architectures and configurations
   
• Participate in customer meetings, presentations, and demos, explaining AWS solutions and capabilities
  
   

Requirements (Must have)

• Active AWS Certified Solutions Architect – Associate (SAA-C03)
   
• Solid theoretical understanding of AWS core services:
  Compute, Storage, Databases, Networking, Security
   
• Basic networking knowledge:
  TCP/IP (L3, L4), IP addressing, subnetting, DNS
   
• Understanding of cloud principles:
  High Availability, Fault Tolerance, Scalability, Security
   
• Basic Linux skills (command line)
   
• Ability to read and understand technical documentation in English
  
   

Nice to have

• Hands-on experience with Terraform or CloudFormation
   
• Basic scripting skills (Python, Bash)
   
• Familiarity with Docker, Kubernetes, ECS
   
• Personal, educational, or non-commercial projects deployed on AWS
  
   

Soft skills

• Strong motivation to learn and grow in cloud engineering
   
• Structured and analytical thinking
   
• Clear and confident communication
   
• Ukrainian or Russian — fluent
   
• English — reading technical documentation (spoken English is a plus)
  
   

We offer
 

• Individual Entrepreneur (FOP) / contractor model
   
• Official contract with Austria
   
• Full-time workload
   
• Real commercial AWS projects (not internal labs)
   
• Participation in architecture design and pre-sales activities
   
• Professional growth within Cloud & Solutions Architecture
   
• International customers and vendors
   
• Supportive, senior cloud team and mentorship

Google Cloud Solutions Architect / Pre-Sales Engineer

Company: Softprom Solutions
Location: Remote (Ukraine)
Employment: Full-time, FOP (contractor)

About the role

Softprom Solutions is looking for a Google Cloud Solutions Architect / Pre-Sales Engineer to join our Cloud team.

This role is ideal for a specialist with hands-on experience in Google Cloud Platform and an active Google Cloud certification, who wants to work on real commercial projects, participate in pre-sales activities, and grow in cloud architecture.

Responsibilities

• Design and document Google Cloud architectures according to the Google Cloud Architecture Framework
• Participate in pre-sales activities:
  • technical discovery with customers
  • solution design
  • participation in demos and presentations
• Deployment and configuration of core GCP services, including:
  • Compute Engine, Cloud Storage, Cloud SQL
  • VPC, IAM, Load Balancing
  • Cloud Functions / Cloud Run
• Design and configure GCP networking:
  • VPC networks, subnets
  • Firewall rules
  • Routes
• Implement and support Infrastructure as Code (IaC) using Terraform
• Create technical and solution documentation
• Act as a technical point of contact for sales and customers

Requirements (Must have)

• Active Google Cloud certification
  (Associate Cloud Engineer or Professional Cloud Architect)
• Experience as Cloud Engineer / Solutions Architect / Pre-Sales Engineer
• Practical understanding of Google Cloud core services:
  • Compute, Storage, Databases, Networking, Security
• Solid networking knowledge:
  • TCP/IP (L3, L4)
  • IP addressing, subnetting
  • DNS
• Understanding of cloud principles:
  • High Availability
  • Fault Tolerance
  • Scalability
  • Security
• Linux skills (command line)

Nice to have

• Experience in pre-sales or customer-facing roles
• Experience with Terraform
• Basic scripting skills (Python, Bash)
• Experience with Docker, Kubernetes (GKE), Cloud Run
• Experience with AWS or multi-cloud environments

Soft skills

• Ability to communicate technical solutions to non-technical audiences
• Structured and analytical thinking
• Proactivity and ownership
• Ukrainian — fluent
• English — reading and basic spoken (technical / pre-sales)

We offer

• Compensation: $2000 USD + project-based bonuses
• FOP cooperation
• Full-time workload
• Real commercial Google Cloud projects
• Participation in pre-sales and architecture design
• Professional growth in Cloud & Solutions Architecture
• International projects and vendors
• Strong cloud team and mentorship

At Geniusee, we help businesses thrive through technology partnerships and strengthen the engineering community by sharing knowledge and creating opportunities 🙌

We live by our values: Continuous Growth, Team Synergy, Taking Responsibility, Conscious Openness, and Result-Driven Mindset. Here, you’ll find a safe, inclusive, and supportive environment where your voice is heard, and feedback is welcome 🤗

Whether you want to work from home or from our offices in Kyiv / Lviv / Warsaw with stable electricity and Wi-Fi, we’ve got you covered.
Join us and make an impact 💜

About the project:
FinTech

 

REQUIREMENTS:
● 3+ years of experience in Data Engineering
● Strong data engineering background with the ability to design and own solutions end-to-end
● Proficiency in Python, Airflow, dbt, and Redshift for data processing, pipeline development, and transformation
● Experience building and maintaining ETL / ELT pipelines and data integrations, including fetching and normalizing data from non-robust 3rd party sources
● Hands-on experience with LLM/agent-based automation applied to business processes (e.g., building agents or LLM-powered workflows for data transformation, testing, or extraction)
● Practical familiarity with modern AI tooling — LLM APIs (OpenAI, Anthropic, etc.), RAG patterns, prompt engineering, and agent frameworks (LangChain, LlamaIndex, or similar)
● Cross-functional flexibility: comfortable stepping beyond pure DE work into adjacent areas — light DevOps (Docker, CI/CD, cloud deployment), backend integration, and basic frontend when a POC requires it
● Excellent communication skills — able to explain technical decisions to non-technical stakeholders
● Self-directed and proactive: able to spot workflow inefficiencies and drive improvements with minimal supervision
● Product thinking: collaborate with business teams, propose solution approaches, build quick POCs, iterate on feedback, and support production deployment

RESPONSIBILITIES:
● Analyze business workflows and identify opportunities for data automation and AI-driven process automation
● Design, build, and maintain scalable data pipelines and integrations, including ingestion from unreliable or unstructured 3rd party sources
● Build LLM- and agent-based solutions for data transformation, validation/testing, and extraction tasks
● Containerize data and AI workloads using Docker and deploy to cloud infrastructure (AWS)
● Develop prototypes and POCs to validate ideas quickly — both data pipelines and AI-powered workflows
● Collaborate with business and technical teams to refine requirements and iterate on solutions
● Support the deployment and integration of data and AI solutions into production systems
● Continuously improve data processes through automation and AI-driven approaches
● Contribute to data modeling, quality, and observability practices

Preferred Experience:
● Experience combining traditional ETL/data pipelines with LLM/agent components in production or near-production settings
● Experience working in cross-functional product teams
● Familiarity with cloud-based data platforms (AWS preferred)
● Experience with vector stores, embeddings, or retrieval-augmented generation (RAG)

What will you get:

Career growth & projects
● Competitive salary based on your skills and experience, and a benefits package.
● Regular performance appraisals to support your career development.
● Professional development support: online courses, certifications, and study compensation (including English courses).
● A modern tech stack across challenging, long-term projects.

Health & well-being
● Paid vacation (18 working days) and sick leave (15 days).
● VIP medical insurance or sports coverage.

Work environment & flexibility
● Remote work from anywhere in the world or in one of our offices in Kyiv, Lviv, or Warsaw.
● Coworking compensation.
● Necessary equipment to perform your work.

Culture & community
● A collaborative and open culture where contributions are recognized.
● Regular corporate online & offline activities.
● Geniusee Charity Fund, making a difference beyond tech.

Strim Duo is a creative digital studio based in Limassol, Cyprus. We specialize in social game development, product engineering, UX/UI design, custom software solutions, mobile apps, and post-launch product support.
Our mission is to build products that work seamlessly across devices, delivering engaging experiences for millions of users worldwide.

We are looking for a strong specialist who goes beyond data processing — someone who understands the business behind the data and can influence decisions through analytics. This role requires autonomy, fast learning, and full ownership of data quality and analytical outputs.

Requirements

• Advanced Python and SQL (query optimization, complex data transformations, large-scale data handling)
• Hands-on experience with ClickHouse or other columnar databases
• Strong background in building ETL/ELT pipelines (ingestion, transformation, orchestration). Experience with Airflow is a plus.
• Solid understanding of Data Warehouse architecture
• Strong Data QA skills (identifying and resolving data issues)
• Experience with Power BI (building and maintaining reports)
• Ability to quickly understand business logic and translate it into data models
• High attention to detail
• English — B2 or higher (working proficiency)

Nice to Have

• Experience with data governance implementation
• Experience in high-load systems
• Experience working with product and business teams

Responsibilities

• Own data quality: identify, analyze, and fix data issues
• Translate business processes into reliable data structures
• Build and optimize ETL pipelines
• Deliver clean and structured data for analytics and BI
• Handle AdHoc analytical requests under tight deadlines
• Maintain and improve Power BI reporting
• Automate repetitive tasks
• Provide analytical support
• Train users on BI tools

What we offer

• Corporate psychologist;
• Gifts for significant occasions;
• Legal support;
• Flexible working hours;
• Direct access to C-level and opportunity to suggest new business ideas and drive changes.

If you are ready to work in a dynamic team, passionate about the product, technology, and the world of entertainment, we’re waiting for your CV and portfolio to schedule an online/offline meeting and get to know each other better!

Your CV will be carefully reviewed by our TA department, and if it meets the requirements of the position, we will contact you within 3 business days to discuss the possibility of scheduling an interview.

N-iX is looking a proactive Data Engineer to join our vibrant team.

As a Data Engineer, you will play a critical role in designing, developing, and maintaining sophisticated data pipelines, Ontology Objects, and Foundry Functions within Palantir Foundry. The ideal candidate will possess a robust background in cloud technologies, data architecture, and a passion for solving complex data challenges.

Key Responsibilities:

• Collaborate with cross-functional teams to understand data requirements, and design, implement and maintain scalable data pipelines in Palantir Foundry, ensuring end-to-end data integrity and optimizing workflows.
• Gather and translate data requirements into robust and efficient solutions, leveraging your expertise in cloud-based data engineering. Create data models, schemas, and flow diagrams to guide development.
• Develop, implement, optimize and maintain efficient and reliable data pipelines and ETL/ELT processes to collect, process, and integrate data to ensure timely and accurate data delivery to various business applications, while implementing data governance and security best practices to safeguard sensitive information.
• Monitor data pipeline performance, identify bottlenecks, and implement improvements to optimize data processing speed and reduce latency. 
• Troubleshoot and resolve issues related to data pipelines, ensuring continuous data availability and reliability to support data-driven decision-making processes.
• Stay current with emerging technologies and industry trends, incorporating innovative solutions into data engineering practices, and effectively document and communicate technical solutions and processes.

Tools and skills you will use in this role:

• Palantir Foundry
• Python
• PySpark
• SQL
• TypeScript

Requirements:

• 5+ years of experience in data engineering, preferably within the pharmaceutical or life sciences industry;
• Strong proficiency in Python and PySpark;
• Proficiency with big data technologies (e.g., Apache Hadoop, Spark, Kafka, BigQuery, etc.);
• Hands-on experience with cloud services (e.g., AWS Glue, Azure Data Factory, Google Cloud Dataflow);
• Expertise in data modeling, data warehousing, and ETL/ELT concepts;
• Hands-on experience with database systems (e.g., PostgreSQL, MySQL, NoSQL, etc.);
• Proficiency in containerization technologies (e.g., Docker, Kubernetes);
• Effective problem-solving and analytical skills, coupled with excellent communication and collaboration abilities;
• Strong communication and teamwork abilities;
• Understanding of data security and privacy best practices;
• Strong mathematical, statistical, and algorithmic skills.

Nice to have:

• Certification in Cloud platforms, or related areas;
• Experience with search engine Apache Lucene, Webservice Rest API;
• Familiarity with Veeva CRM, Reltio, SAP, and/or Palantir Foundry;
• Knowledge of pharmaceutical industry regulations, such as data privacy laws, is advantageous;
• Previous experience working with JavaScript and TypeScript.

We offer*:

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

*not applicable for freelancers

Our customer is one of the world's largest food and beverage companies, operating in 189 countries with over 2000 brands. The company's diverse portfolio includes products such as bottled water, dairy products, breakfast cereals, coffee, confectionery, frozen food, pet foods, snacks, and baby food.

We are looking for a Middle Data Engineer to design, build, and maintain scalable data systems that support analytics, reporting, and machine learning use cases. This role requires strong ownership, solid SQL skills, and experience working with large datasets in production environments.

Responsibilities

• Build and maintain data pipelines (batch and near real-time).
• Develop and optimize data models for analytics and BI tools.
• Write efficient SQL queries for large-scale datasets.
• Support development and maintenance of ETL/ELT processes.
• Ensure data quality, integrity, and consistency across systems.
• Collaborate with data analysts, data scientists, and product teams to understand data requirements.
• Monitor and troubleshoot data pipelines and workflows.
• Contribute to improving the performance of the existing data infrastructure.
• Work with cloud-based data platforms and modern data stack tools.

Requirements

• 2–4 years of experience in Data Engineering or a related role.
• Main technical skills are: Snowflake, dbt, ADF.
• Solid SQL skills (joins, aggregations, window functions).
• Understanding of data governance and data quality concepts.
• Proficiency in Python.
• Experience with ETL/ELT tools.
• Hands-on experience with the Azure cloud platform.
• Azure Ops experience: provisioning and configuring.
• Experience working with data warehouses (e.g., Snowflake, BigQuery, Redshift).
• Understanding of data modeling concepts (e.g., star schema).

Nice to have

• Basic knowledge of Docker or containerization.
• Experience with data processing frameworks (e.g., Spark).

Soft skills

• Strong analytical thinking and problem-solving skills.
• Ability to work independently with some guidance.
• Good communication skills with technical and non-technical stakeholders.
• Willingness to learn and grow in a collaborative environment.

We offer*:

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

*not applicable for freelancers

We are looking for a Senior Data Engineer who can design, implement, and evolve scalable data systems in AWS.

Core Responsibilities
 

• Design and implement batch and streaming data pipelines using Apache Spark.
• Build and evolve a scalable AWS-based data lake architecture.
• Develop and maintain real-time data processing systems (event-driven pipelines).
• Own performance tuning and cost optimization of Spark workloads.
• Define best practices for data modeling, partitioning, and schema evolution.
• Implement monitoring, observability, and data quality controls.
• Contribute to infrastructure automation and CI/CD for data workflows.
• Participate in architectural decisions and mentor other engineers.

RRequirements

• 5+ years of commercial experience as a Data Science / AI Engineer
• Strong Python skills and solid software engineering fundamentals
• Proven experience building high-load, production-grade systems
• 2+ years of experience working with LLM and NLP-related tasks
• Hands-on experience with RAG pipelines and vector databases
• Strong understanding of modern deep learning architectures
• Experience with at least one deep learning framework (TensorFlow or PyTorch)
• Experience with SQL and NoSQL databases
• Good knowledge of Kubernetes
• Experience working with modern AI development tools (e.g., Claude Code, Cursor)
• Upper-Intermediate or higher level of English (spoken and written)
• Familiarity with Model Context Protocol (MCP)
• Experience with production LLM frameworks (e.g., vLLM)
• Experience training or fine-tuning LLMs
• Experience with cloud platforms (AWS, Google Cloud, Azure)
• Participation in Kaggle or similar competitions