Jobs Data Engineer

Location: Remote
Employment Type: Full-time / Long-term
Domain: Logistics
About the Project
We are looking for a Senior AWS Data Engineer to design and build a centralized data platform from scratch for a logistics product running on AWS.
The platform uses a microservices architecture with Amazon RDS MySQL (~136 GB production database). Currently, BI dashboards are spread across multiple subsystems. The goal is to centralize data and enable management to make informed decisions based on crew compliance, certifications, and operational performance.

Responsibilities
Design and build a scalable AWS data platform and data lake from scratch.
Develop ETL/ELT pipelines from MySQL (Amazon RDS).
Design data models optimized for analytics and reporting.
Integrate BI tools such as AWS QuickSight, Metabase, or Apache Superset.
Ensure data quality, security, and strict customer data segregation.
Collaborate with engineering and business teams to deliver reliable reporting solutions.

Requirements
5+ years of experience as a Data Engineer.
Strong hands-on experience with AWS.
Experience building data lakes using Amazon S3.
Experience with AWS Glue and Amazon Athena.
Strong SQL and MySQL skills.
Experience designing ETL/ELT pipelines.
Knowledge of data warehousing and data modeling principles.
Experience working with cloud-based microservices architectures.
Upper-Intermediate English (B2+) or higher.

Nice to Have
Experience with AWS QuickSight, Metabase, or Apache Superset.
Python for data engineering.
Experience in Logistics or Supply Chain projects.

N-iX is a global software development service company that helps businesses across the globe create next-generation software products. Founded in 2002, we unite 2,400+ tech-savvy professionals across 40+ countries, working on impactful projects for industry leaders and Fortune 500 companies. Our expertise spans cloud, data, AI/ML, embedded software, IoT, and more, driving digital transformation across finance, manufacturing, telecom, healthcare, and other industries. Join N-iX and become part of a team where your ideas make a real impact.

We're looking for a hands-on Senior Data Engineer who can independently design and deliver end-to-end data solutions. You'll work directly with business stakeholders to understand requirements and transform them into scalable data platforms, analytics solutions, and AI-enabled applications. The ideal candidate is comfortable owning initiatives from discovery through implementation while collaborating closely with the engineering team.

This role requires deep expertise in Snowflake and modern cloud data platforms, along with strong SQL, Python, and data modeling skills.

Working hours: Europe and Ukraine (with the ability to work till around 2:00-3:00 PM CST/ 09:00-10:00 PM CET/ 10:00-11:00 PM EET).

Key Responsibilities:

• Design, build, and maintain scalable end-to-end data pipelines from ingestion through transformation and reporting.
• Develop robust data warehouse solutions using modern data modeling techniques (Kimball, Data Vault, or normalized models).
• Build and optimize Snowflake-native solutions using Dynamic Tables, Streams, Tasks, Stored Procedures, and Snowpark.
• Design high-performance SQL queries and optimize warehouse performance, clustering, and search optimization.
• Develop Python-based data processing and API ingestion workflows.
• Build and maintain data movement and orchestration pipelines using Azure Data Factory and Azure cloud services.
• Design and optimize Power BI semantic models, reports, and dashboards for business stakeholders.
• Collaborate directly with business users to gather requirements, define technical solutions, and deliver business value.
• Implement CI/CD practices, governance, RBAC, and data security within Snowflake environments.
• Contribute to AI-enabled data solutions using modern AI platforms and machine learning workflows.
• Mentor other engineers through code reviews, technical guidance, and engineering best practices.

Requirements:

• 5+ years of hands-on experience as a Data Engineer building and delivering end-to-end data solutions.
• 3+ years of hands-on experience with Snowflake, including building production-grade data pipelines using Dynamic Tables, Streams, Tasks, Stored Procedures, and Snowpark.
• Expert-level SQL skills with extensive experience optimizing complex queries and designing high-performance data warehouses.
• Strong experience designing and implementing enterprise data models using dimensional modeling (Kimball), Data Vault, or normalized approaches.
• Advanced Python programming skills for data processing, API integrations, workflow automation, and ETL/ELT development.
• Experience building and maintaining cloud-based data platforms on Microsoft Azure, including Azure Data Factory, Azure Functions, and Azure Data Lake Storage (ADLS Gen2).
• Strong experience developing business intelligence solutions using Power BI, including data modeling, DAX, and report performance optimization.
• Experience implementing CI/CD pipelines, version control, RBAC, and data governance practices for modern data platforms.
• Experience building AI-enabled data solutions using technologies such as Snowflake Cortex, Azure AI Foundry, Azure Copilot Studio and Python-based machine learning frameworks.
• Experience working directly with business stakeholders to understand requirements, translate them into technical solutions, and independently deliver projects from concept through implementation.
• Excellent communication skills and the ability to collaborate effectively across cross-functional teams.
• English Upper Intermediate+

Nice to Have

• Snowflake certification.
• Microsoft Azure certification.

🚀 We’re on the hunt for a talented AI/ML Engineer to design, implement, and optimize cutting-edge AI/ML solutions. If you thrive on solving complex problems and creating production-ready models, we’d love to hear from you!

🎯 What You’ll Do:

• Develop and fine-tune AI/ML models for performance and scalability.
• Enhance production models, debug issues, and ensure reliability.
• Work with cross-functional teams to shape future AI/ML innovations.
• Explore emerging AI/ML technologies and recommend tools/frameworks.
• Build robust pipelines using Python, SQL, Docker, and more.

🧩 What We’re Looking For:

• Strong experience in AI/ML, data science, or data engineering.
• Expertise in Python, TensorFlow, Keras, Scikit-learn, and Generative AI.
• Familiarity with Docker, Streamlit, and data tools like Pandas and SQL.
• Strong communication skills and the ability to work independently.
• English: Upper-intermediate or higher.

🎯 We offer:

• Paid vacation and sick leave
• We provide the equipment you need to work comfortably (if required)
• We cover 50% of courses if you want to grow professionally
• Regular salary reviews based on your performance
• Competitive salary, depending on your experience
• Always on-time payments — no delays

• A normal, supportive team without unnecessary bureaucracy

   

Ready to shape the future of AI/ML with us? 🚀 Apply now and be part of something extraordinary!

We're Gypsy Collective. The digital world is evolving faster than ever. New opportunities, new challenges, new ambitious goals. That’s why strong businesses need strong people. 

Gypsy Collective is an exclusive talent partner for selected brands. We help our partners attract exceptional talent by building long-term relationships and becoming deeply integrated into their business, culture, and growth ambitions.

We are looking for a Middle DWH Engineer to design, build, and maintain scalable data warehouse solutions that support analytics and business decision-making. You will work across the full data lifecycle - from data ingestion and transformation to orchestration and optimization - while collaborating with analysts, engineers, and business stakeholders.

📅  Your adventures include:

• design, develop, and maintain DWH and Data Lake solutions aligned with business requirements;
• build, optimize, and support ETL/ELT pipelines using Python, SQL, Airflow, and related technologies;
• integrate and maintain data flows from APIs, databases, SaaS platforms, and third-party systems;
• work with PostgreSQL, Trino, and cloud-based analytical platforms to support reporting and analytics needs;
• implement and support incremental loading, CDC processes, backfills, and reprocessing workflows;
• monitor, troubleshoot, and improve data pipelines to ensure reliability, stability, and timely delivery of data;
• implement data quality checks, validation rules, and automated monitoring processes;
• optimize SQL queries, data models, and pipeline performance;
• collaborate with analysts, BI developers, engineers, and business stakeholders to deliver scalable data solutions;
• participate in code reviews and contribute to engineering standards and best practices.

🧭 What makes you a great match:

• strong SQL skills, including complex queries, CTEs, window functions, analytical queries, and query optimization (3+ years);
• strong experience integrating external data sources, including REST APIs, databases, SaaS platforms, and third-party systems; ability to design, develop, troubleshoot, and maintain reliable data ingestion processes in production environments (3+ years);
• experience with Apache Airflow or similar workflow orchestration tools (3+ years);
• experience with Python for data processing, integrations, and automation (2+ years);
• good understanding of DWH concepts, including ETL/ELT, dimensional modeling, Data Vault, and Star/Snowflake schemas (3+ years);
• experience building and supporting production data pipelines with a focus on reliability, stability, monitoring, and error handling;
• understanding of data quality principles, including validation, testing, reconciliation, and monitoring;
• hands-on experience with PostgreSQL and Trino in production environments;
• experience with modern analytical databases or cloud data warehouses (such as BigQuery, Snowflake, Redshift, ClickHouse, Vertica, Athena, or similar platforms.);
• experience with Git and collaborative development workflows (pull requests, code reviews, rebasing, merge conflict resolution).

⭐ Nice to Have

• experience with Change Data Capture (CDC) tools and incremental loading strategies;
• experience with cloud platforms such as AWS, GCP, or Azure;
• familiarity with Docker and containerized environments;
• experience with streaming or near real-time data pipelines (Kafka);
• familiarity with dbt or similar data transformation frameworks;
• experience with data cataloging, lineage, or governance tools.
   

Benefits

• 💸 Flexible payment options: choose the method that works best for you.
• 🧾 Tax assistance included: we handle part of your taxes and provide guidance on the local setup.
• 🎁 Financial perks: Bonuses for holidays, B-day, work milestones and more - just to show we care.
• 📈 Learn & grow: We cover courses and certifications — and offer real opportunities to grow your career with us.
• 🥐 Benefit Сafeteria: Choose what suits you — sports, language courses, therapy sessions, and more.
• 🎉 Stay connected: From team-building events to industry conferences — we bring people together online, offline, and on stage.
• 💻 Modern Equipment: We provide new laptops along with essential peripherals like monitors and headphones for a comfortable workflow.
• 🕘 Your schedule, your rules: Start your day at 9, 10, or even 11 — we care about results, not clock-ins.

N-iX is a global software development service company that helps businesses across the globe create next-generation software products. Founded in 2002, we unite 2,400+ tech-savvy professionals across 40+ countries, working on impactful projects for industry leaders and Fortune 500 companies. Our expertise spans cloud, data, AI/ML, embedded software, IoT, and more, driving digital transformation across finance, manufacturing, telecom, healthcare, and other industries. Join N-iX and become part of a team where your ideas make a real impact.

About the Project:

N-iX is assembling a dedicated delivery team for an intensive, high-visibility engagement with a US-based payments-technology business that is being carved out of its parent company into a standalone entity. The platform processes card payments end to end for thousands of institutional customers through five production .NET applications — including a central payment gateway, a registration platform with an in-house encrypted card vault, an AWS-native ticketing / point-of-sale product, and a large commerce application with a single-tenant, per-customer database model.

Within a hard 90-day window the team delivers: an independent security assessment (penetration testing with code-assisted and cloud review), remediation of critical and high-severity findings verified by retest, end-of-life framework and dependency upgrades, and discovery / sequencing support for the transfer of the Azure and AWS estate to the new owner. The work is fast-paced, brownfield and security-centric, with direct exposure to the client's CTO-level stakeholders and a realistic Phase 2 (re-architecture and platform integration) for continuation.

Role Overview:

We are looking for a Senior Database Engineer (50% allocation) to own the database layer of the security remediation. The flagship legacy application runs a single-tenant model with roughly 2,000 production SQL Server databases (one per customer), and the registration platform stores encrypted cardholder data in a card vault whose business logic lives in T-SQL stored procedures. Nothing here can be done by hand at estate scale: the role is about programmatic scanning, schema-change automation and repeatable, evidence-producing runbooks that the client's retained team can execute estate-wide.

Key Responsibilities:

• Design and run programmatic security scanning across the single-tenant SQL Server estate (~2,000 databases): configuration, permissions, encryption posture, sensitive-data exposure.
• Build schema-change automation with rollout and rollback tooling — templated migrations executed estate-wide by the retained team from your runbooks; no per-database manual work.
• Review and remediate T-SQL stored procedures and triggers flagged by the security assessment, including the encrypted card vault (deep review is AI-assisted and paired with the security team).
• Support encrypted card-vault data handling and migration scenarios: key-rotation impact, re-encryption, integrity verification.
• Harden the MySQL 8 / AWS Aurora databases of the AWS-native ticketing product.
• Produce retest evidence: before / after states, scripts, execution logs, residual-risk notes.

Requirements & Qualifications

• Experience: 6+ years as a DBA / database engineer on large production estates; proven work where changes are rolled out across hundreds or thousands of databases programmatically.
• Core stack (Must-Have): deep SQL Server 2017/2019 administration and performance; expert T-SQL (stored procedures, triggers); working MySQL 8 / AWS Aurora.
• Automation (Must-Have): schema-change automation across many single-tenant databases — templated migrations, batching, verification, rollback.
• Sensitive data (Must-Have): hands-on experience with encrypted data stores — encrypted card-vault handling / migration, key-rotation and re-encryption scenarios.
• Nice-to-Haves: Cosmos DB; DynamoDB; Azure SQL Managed Instance; PCI DSS exposure.
• English: fluent written and spoken English (B2+) for documentation, evidence packages and client calls.
• Working hours: standard EU hours with 2–3 hours of overlap with US Eastern Time for client ceremonies.

We offer*:

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

*not applicable for freelancers

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

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

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

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

Requirements:

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

Working conditions:

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

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

 Apply now!

US Company is searching for a UI/UX and Database Engineer (AI Platform) to join an AI-driven product company focused on building modern communication solutions powered by cutting-edge technologies. This role combines frontend engineering, user experience improvements, and database development while working alongside experienced Full-Stack Engineers in an international remote team. Full-time, official contract, remote work, and flexible schedule.

Brief project description:
The product is an AI-powered communications platform that enables businesses to deliver intelligent customer interactions through modern messaging and voice technologies.

Responsibilities:

• Develop responsive, accessible, and user-friendly interfaces using modern frontend technologies.
• Improve usability, navigation, layouts, forms, and overall user experience across the platform.
• Build and maintain PostgreSQL queries, views, migrations, and database structures.
• Support backend integration with frontend applications through REST APIs.
• Troubleshoot UI and data-related issues.
• Write automated tests for frontend and database functionality.
• Participate in code reviews and Agile ceremonies.
• Produce clear technical documentation.
• Collaborate closely with senior engineers while continuously improving development practices.
• Participate in production support and occasional on-call activities when required.

Required skills (must have):

• 2+ years of professional experience in Frontend or Full-Stack development.
• Strong knowledge of HTML, CSS, and JavaScript.
• Commercial experience with at least one modern frontend framework (React, Vue, Angular or similar).
• Good understanding of UI/UX principles and responsive design.
• Experience writing SQL queries and working with PostgreSQL databases.
• Familiarity with frontend testing frameworks (Jest, Playwright, Cypress or similar).
• Experience integrating frontend applications with REST APIs.
• Excellent spoken and written English.
• Ability to work with several hours of overlap with US business hours.

Would be considered as a plus:

• Experience with Python or Node.js backend development.
• Experience working with Figma.
• Experience with Jira and Agile development methodologies.
• Experience working on SaaS products.
• Basic knowledge of cloud platforms such as AWS.

Work conditions:

• 100% remote work.
• Full-time (40 hours per week).
• Official contract.
• Flexible schedule with required overlap with US business hours.
• Participation in occasional on-call support rotation.

Interviewing / Hiring process:
Step 1 - preliminary interview (main questions) - 45 mins
Step 2 - internal technical interview - 60 mins
Step 3 - technical interview with Team Leader - 60 mins

US Company is searching for a Senior Backend and DB Engineer to join an innovative product team developing an AI-powered SaaS platform. This is an exciting opportunity to build scalable backend services, cloud infrastructure, and data-driven solutions while working with modern AI technologies in a distributed international team. Full-time, official contract, remote work, and flexible schedule.

Brief project description:
The product is SaaS, which enables businesses to automate and enhance customer communications through AI-powered workflows and modern communication technologies.

Responsibilities:

• Design, develop, and maintain scalable backend services using Python and Node.js.
• Design, optimize, and maintain PostgreSQL databases, schemas, queries, and migrations.
• Build and maintain REST APIs and backend integrations.
• Integrate LLM APIs and AI-powered capabilities into production applications.
• Build, deploy, and maintain applications and cloud infrastructure on AWS.
• Optimize application performance, scalability, and reliability.
• Develop and maintain automated unit and integration tests.
• Participate in architecture discussions, code reviews, sprint planning, and technical decision-making.
• Troubleshoot production issues and continuously improve backend quality and performance.
• Collaborate closely with engineers across the team, contributing wherever needed to support successful product delivery.

Required skills (must have):

• 7+ years of professional software engineering experience, including significant experience in backend development.
• Strong backend development experience with Python and/or Node.js.
• Strong experience with PostgreSQL, including schema design, query optimization, indexing, migrations, and performance tuning.
• Experience designing and developing REST APIs.
• Experience building and deploying applications on AWS.
• Experience working with LLM APIs or AI-powered applications.
• Experience with automated testing frameworks and modern development practices.
• Excellent spoken and written English.
• Ability to work with several hours of overlap with US business hours.

Would be considered as a plus:

• Basic experience with React, Vue.js, or similar frontend frameworks.
• Experience with Twilio or other communications platforms.
• Experience working on enterprise SaaS products.
• Experience working with distributed international teams.
• Experience with Agile/Scrum development methodologies.

Work conditions:

• 100% remote work.
• Full-time (40 hours per week).
• Official contract: salary, sick-leave days, holidays, vacations.
• Flexible schedule with overlap with US business hours.

Interviewing / Hiring process:
Step 1 - preliminary interview (main questions) - 45 mins
Step 2 - internal technical interview - 60 mins
Step 3 - technical interview with Team Leader - 60 mins

We are looking for an experienced Senior Data Engineer to help build and maintain a modern data processing platform for a global product ecosystem. You will work on automating complex data transformations, improving data quality, and building reliable pipelines that deliver trusted data to downstream systems.

The role focuses on designing scalable ETL/data pipeline frameworks, migrating existing Talend solutions, and creating a single source of truth for transformed data versions.
 

Core Competence:
 

• 5+ years of professional experience in Python development, with a strong focus on data engineering, ETL processes, and automation.
• Strong experience designing, building, and maintaining data pipelines for large-scale data processing.
• Hands-on experience with GCP data technologies, including:
  • BigQuery — data warehousing, optimization, and analytical workloads.
  • Dataform — data transformation workflows and data modeling.
  • Cloud Composer — workflow orchestration and pipeline automation.
• Experience developing and optimizing ETL/ELT frameworks and migrating legacy data processing solutions.
• Strong understanding of data transformation processes, data modeling, and maintaining reliable data flows between systems.
• Experience working with data quality challenges, including:
  • Data validation and profiling.
  • Identifying inconsistencies and anomalies.
  • Building data quality reporting mechanisms for external suppliers.
• Experience implementing versioned data storage approaches to maintain a single source of truth across business systems.
• Knowledge of Terraform for infrastructure as code and cloud environment management.
• Ability to design scalable, maintainable, and production-ready data architectures.
   

Preferred Qualifications:
 

• Experience migrating from traditional ETL tools such as Talend to modern cloud-based data platforms.
• Familiarity with supplier/product data ecosystems and handling multiple data formats from various sources.
• Experience working with cloud-native data platforms and distributed processing architectures.
• Strong SQL skills and experience optimizing analytical queries.
• Understanding of data governance, metadata management, and data lifecycle principles.
• Experience working in Agile teams and collaborating with business stakeholders to improve data processes.
   

What We Offer You:

• Modern Data Platform Challenges: Work on automating complex data workflows and building reliable data infrastructure.
• Technical Ownership: Design core data frameworks and influence architecture decisions.
• Cloud-Native Environment: Work with modern GCP technologies and infrastructure-as-code practices.
• Business Impact: Improve data quality and reliability for systems used across the organization.
• Professional Growth: Expand expertise in data engineering, cloud technologies, and scalable pipeline design.
• Flexible Work Environment: Collaborate with an international team using modern engineering practices.

We're looking for an experienced Senior Backend Engineer to help build and operate an AI-powered software development platform for a public-sector client. The platform combines LLM-based code generation, AI model integrations, cloud-native backend services, and automated development workflows in a scalable production environment.
 

If you're passionate about distributed systems, modern JVM technologies, cloud infrastructure, and building secure identity-driven platforms, we'd love to hear from you!
 

Core Competence:
 

• 5+ years of professional backend development experience with strong software engineering fundamentals and experience building scalable distributed systems.
• Strong proficiency in Kotlin and/or Java with hands-on experience developing backend applications on the JVM ecosystem.
• Deep experience with Spring Boot / Spring Framework for designing and implementing production-grade microservices.
• Strong understanding of microservices architecture, including service boundaries, API design, inter-service communication, resilience patterns, and distributed system challenges.
• Solid experience with PostgreSQL, including database modeling, schema design, query optimization, and migration management.
• Experience with JUnit for unit and integration testing, with a strong focus on code quality and reliability.
• Hands-on experience with Docker for containerization, image creation, and optimization.
• Strong knowledge of Kubernetes (K8s) for deploying, scaling, and operating cloud-native applications.
• Experience with Helm for Kubernetes package management and deployment automation.
• Proficiency with Gradle for build automation and dependency management.
• Experience with Git/GitLab workflows, including branching strategies, CI/CD pipelines, and code review processes.
• Practical knowledge of OpenID Connect and experience implementing authentication and authorization flows.
• Experience with Keycloak or Ory products, including IAM configuration, realms, clients, and identity flows.
   

Preferred Qualifications:
 

• Experience working with AI-powered platforms, LLM integrations, or AI-assisted development tools.
• Background in digital identity and verifiable credentials ecosystems.
• Knowledge of modern identity standards, including:
  • OpenID4VP — presentation of verifiable credentials.
  • SD-JWT — selective disclosure of individual attributes.
  • OpenID4VCI / OpenID4VC — issuance and management of digital credentials.
  • mdoc (ISO/IEC 18013-5) — mobile document formats such as mobile driver's licenses.
• Experience building secure systems for government, enterprise, or regulated environments.
• Understanding of cloud-native architecture principles and production operations.

• Experience contributing to early-stage platforms and evolving solutions from initial concepts into reliable production systems.

   

What We Offer You:
 

• Cutting-Edge AI Projects: Work on a platform combining LLM technologies, backend engineering, and cloud-native infrastructure.
• Technical Impact: Influence architecture decisions and contribute to building scalable solutions used in real-world environments.
• Modern Engineering Culture: Work with advanced technologies, automation practices, and strong engineering standards.
• Professional Growth: Opportunity to deepen expertise in AI platforms, distributed systems, and digital identity technologies.
• Global Collaboration: Join an international team working on challenging and impactful projects.
• Flexible Work Environment: Remote-friendly setup with a focus on autonomy and work-life balance.

About client

Client builds and operates GPU cloud infrastructure at the scale modern AI demands. We run dense accelerated-compute clusters on bare metal, powered by NVIDIA and AMD accelerators and K8s, stitched together with high-performance Ethernet and InfiniBand fabrics, and we deliver them to customers as reliable, secure, high-throughput platforms. We are scaling rapidly across new data center sites, and the infrastructure team sits at the center of that growth, building the systems that turn racks of hardware into a product customers depend on.

The role

We are hiring a Principal Infrastructure Engineer to build the foundation of our greenfield v2 cloud platform: the bare-metal provisioning and control-plane substrate that turn new racks of GPU hardware into reliable, secure, customer-ready capacity.This is a build-focused, hands-on role and the most senior individual contributor on the platform build. You will own the recommendation and the call on the infrastructure layer (we’re currently in POC across different vendors) and the build-vs-buy decision that goes with it, with our Cloud Platform Architect pressure-testing it. You will drive integration across the other domains and define how infrastructure is templated, multi-tenanted, and handed to customers. You will define the architecture and the standards the rest of the team builds to, while still being deep in the code yourself. Day-to-day operations are not your focus, getting the platform designed and built right is.

You will work at the center of new cluster and new-site buildouts, partnering closely with our network, SRE, and security engineers. They own the fabric and day-to-day operations; you own getting the platform built right. Because the systems you design become the foundation customer GPU workloads run on, getting the architecture and automation right the first time matters more here than almost anywhere.

What you’ll own

• Platform architecture and technical direction: own the architecture of the cloud platform control plane and orchestration layer for new GPU clusters, making the foundational decisions and setting the technical standards the rest of the platform is built on.

• Bare-metal provisioning automation: build the automated pipeline that takes a node from rack-and-stack handoff to a fully configured, real acceptance gates before a node is marked customer-ready, firmware to the qualified recipe, GPU burn-in, NCCL/RCC runs, and fabric checks, plus a golden-image build-and-qualify pipeline in CI repeatedly across sites and at scale.

• Infrastructure as code and automation: treat the platform as code from day one. Build the Terraform and Ansible that provision, configure, and validate the platform, so the build is reproducible rather than hand-assembled.

• Control-plane substrate: build the control plane that turns provisioned bare metal into cluster-ready capacity, and own the clean handoff to the Kubernetes layer. You own tenant isolation at the network and hardware layer; the Kubernetes and namespace isolation model belongs to the Principal Kubernetes Platform Engineer.

• DPU and SmartNIC integration: design how we leverage BlueField DPUs in the platform, offload, provisioning, isolation, and the SuperNIC/DPU-mode configurations that let us get the most out of the hardware.

• Platform reliability by design. Build observability, guardrails, and progressive-rollout mechanisms into the platform from the start. As you build it and design to our SOC 2, ISO 27001, and HIPAA obligation.

• Security Built-in: instrument the platform as you build it and design to our SOC 2, ISO 27001, and HIPAA obligations. Vault-based secrets model from the start. BIOS and system prep for trusted domain execution, secure boot, and backend-fabric hardening.

• Confidential-compute-ready platform (growth area): Design the tenancy and scheduling so it fits our confidential-compute roadmap: whole-GPU per tenant, and TDX with GPU passthrough. Deep CC background is a plus, not a requirement.

• New site buildouts: take a critical role in standing up the platform at new data center sites, turning green-field facilities into production capacity.

• Technical leadership: set patterns, review designs, and raise the engineering bar across the infrastructure team multiplying the impact of other engineers and mentoring senior ICs, without becoming a people manager.

What we’re looking for

Required

• 10+ years building production infrastructure at scale, including deep green-field and platform-build experience, for cloud, hosting, or high-performance compute environments.

• A track record of setting technical direction on complex platforms, architecture others adopt, standards others follow, and influence that extends well beyond your own keyboard.

• Strong Linux systems fundamentals, you can reason about the kernel, networking stack, storage, and performance, not just the command line.

• Fluency in infrastructure as code and automation: Terraform, Ansible, and a real programming language used to build durable platform tooling, not just one-off scripts.

• Production Kubernetes experience: building, deploying, and operating clusters and the platform services that run on them.

• A demonstrated bias toward building things right the first time: sound architecture, reproducible automation, and durable design over short-term shortcuts.

• Strong written communication, you document designs and decisions clearly and leave systems more understandable than you found them.

Strongly preferred

• DPU / SmartNIC experience, especially leveraging offload, DPU/SuperNIC modes, and platform designs that exploit them. This is a meaningful differentiator for us.

• Experience with GPU and accelerated-compute infrastructure across NVIDIA and AMD, including ROCm and firmware lifecycle, or HPC/AI infrastructure.

• Bare-metal provisioning at scale (Redfish/BMC automation, NetBox or a similar source of truth).

• Experience standing up cloud-platform control-plane stacks in a green-field setting.

• Networking depth, BGP, VLANs, fabric concepts, and the ability to debug connectivity and throughput issues. You won’t own the network, but the more fluently you can partner with our network engineers, the better.

• Familiarity with high-performance fabrics: RoCE Ethernet / InfiniBand.

• HashiCorp Vault, and building within a SOC 2 / ISO 27001 / HIPAA compliance posture.

How we work

• Small, senior, high-trust teams. We hire people who can own and solve problems end to end and we give them the room to do it.

• Code over clicks. The platform is defined, reviewed, and versioned. Manual changes are the exception and they get automated away.

• Build it right. We invest in sound architecture and durable design so the platform scales cleanly instead of accumulating debt.

• Customers are real. The platform exists to serve customer workloads, and we build to the reliability and white-glove standard that implies.

• We document. Designs, decisions, and architecture are written down so the team compounds knowledge instead of re-learning it.

AI as a force multiplier

We expect our engineers to use AI to move faster and operate at higher leverage, and we build our environment to make that the default rather than an afterthought. We maintain CLAUDE.md and AGENTS.md context files across our repositories, run MCP servers against our operational systems (Jira, NetBox, Checkmk), and use agentic coding tools such as Claude Code directly in our infrastructure and platform workflows.

You don’t need to be an AI expert, but you should be eager to fold these tools into how you design, build, and automate — and to help us push the frontier of what an AI-leveraged infrastructure team can do.

What success looks like

First 30 days

• Ramped on our environment: the platform stack, provisioning approach, and target architecture. able to navigate the codebase and design docs independently.

• Shipped your first meaningful contribution to the platform build with the team’s review.

• Aligned with network, SRE, and security on where your work meets theirs.

First 90 days

• Owning a defined component of the platform build end to end, from design through delivery.

• Delivered a meaningful piece of provisioning or platform automation that made the build faster, more reproducible, or more reliable.

• Shaped at least one foundational architecture decision that the platform is built on.

First 12 months

• The recognized technical authority for the cloud platform build, setting direction and trusted across network, SRE, security, and platform engineering.

• Designed and delivered a significant piece of the cloud platform or its automation that raised the team’s leverage and the platform’s reliability.

• Took a lead role in bringing at least one new data center site online.

About the Role

We are looking for an experienced Senior Data Engineer to design, build, and maintain scalable data platforms and pipelines. You will work closely with data analysts, data scientists, software engineers, and business stakeholders to deliver reliable, high-quality data solutions that power analytics and business decision-making.

This role is ideal for someone passionate about building modern data architectures, optimizing data workflows, and ensuring operational excellence.

Responsibilities

• Design, develop, and maintain scalable batch and streaming data pipelines.
• Build robust ETL/ELT workflows for ingesting, transforming, and serving data.
• Optimize data storage, processing, and query performance.
• Develop and maintain data models that support reporting, analytics, and machine learning.
• Ensure data quality, reliability, security, and governance across the platform.
• Monitor production pipelines and troubleshoot operational issues while maintaining SLAs.
• Collaborate with cross-functional teams to translate business requirements into technical solutions.
• Improve automation, deployment processes, and infrastructure for data engineering workloads.
• Contribute to architectural decisions and engineering best practices.
• Document technical solutions and mentor junior engineers when needed.

Required Skills

• 5+ years of experience in Data Engineering or a similar role.
• Strong proficiency in Python and SQL.
• Experience building scalable ETL/ELT pipelines.
• Hands-on experience with modern cloud platforms (AWS, Azure, or Google Cloud).
• Experience working with data warehouses such as Snowflake, BigQuery, Redshift, or Synapse.
• Strong understanding of data modeling principles.
• Experience with orchestration tools such as Airflow or similar.
• Knowledge of distributed data processing technologies (Spark preferred).
• Experience with Git and software engineering best practices.
• Strong analytical and problem-solving skills.
• Experience supporting production systems, troubleshooting incidents, and maintaining operational reliability and SLAs.
• Excellent communication skills with both technical and non-technical stakeholders.

Nice to Have

• Experience with dbt for data transformation and modeling.
• Knowledge of data observability and monitoring tools.
• Experience with streaming technologies such as Kafka, Apache Flink, or similar.
• Familiarity with CI/CD pipelines for data engineering.
• Experience implementing data quality frameworks and governance practices.
• Experience with Infrastructure as Code (Terraform or similar).
• Bachelor's degree in Computer Science, Engineering, Mathematics, or a related field (or equivalent practical experience).

What We Offer

• Fully remote work ( shifts per USA time zone)
• Opportunity to work with modern cloud-based data platforms.
• Long-term international project.
• Collaborative engineering culture.
• Competitive compensation based on experience.
• Career growth opportunities and exposure to cutting-edge data technologies.

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

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

Intempt runs 36+ microservices on AWS EKS (Kubernetes 1.25) processing 350M+ events/month. Aurora PostgreSQL 13.8, MSK Kafka 3.3.1, ClickHouse, Apache Flink, HashiCorp Vault, and Redis are all managed through Terraform with SOPS-encrypted secrets, deployed via GitHub Actions CI/CD with OIDC auth.

The infrastructure works. We need someone to own it.

You'll manage the full lifecycle: EKS clusters with spot instances across node groups, Aurora provisioned instances with logical replication, MSK brokers with TLS and auto-scaling storage, Vault HA with KMS auto-unseal, cert-manager for Route53 DNS validation, ALB ingress controllers, cluster autoscaler, EFS, Noobaa object storage, and S3+CloudFront static site delivery. Every service has its own ECR repo with immutable tags, scan-on-push, and a dedicated GitHub Actions deployer role scoped to exactly the permissions it needs.

What you'll own

• EKS cluster operations — node group scaling, spot instance management, Fargate profiles, security groups, OIDC provider config
• Terraform IaC across all environments (staging/QA/production) with S3 state backend and SOPS+KMS secret management
• Database reliability — Aurora PostgreSQL 13.8 (provisioned, 2 instances, encrypted, logical replication), ElastiCache Redis, ClickHouse on Altinity
• Streaming infrastructure — MSK Kafka 3.3.1 (TLS, CloudWatch logs, Prometheus JMX/Node exporters, auto-scaling storage) and Flink Kubernetes Operator 1.4.0
• CI/CD pipeline — GitHub Actions with OIDC auth, 20+ per-service deployer roles mapping git repos to ECR repos, plan/apply workflow with manual production gates
• Secrets and service identity — HashiCorp Vault HA on EKS with PostgreSQL backend, KMS auto-unseal, Transit engine, AppRole auth
• Observability — DataDog agents, Prometheus exporters, CloudWatch, incident response and runbooks
• Backup and DR — AWS Backup (daily, 30-day retention) covering S3 and EFS, RDS automated backups, point-in-time recovery

You are

• 3+ years running production Kubernetes on AWS — not just deploying to it, actually operating clusters at scale
• Deep Terraform experience — you've managed multi-environment IaC with remote state, modules, and encrypted secrets
• Comfortable with managed Kafka (MSK or Confluent), stream processing (Flink/Spark), and the failure modes of distributed messaging
• Familiar with HashiCorp Vault operations — unsealing, secret rotation, Transit engine, AppRole patterns
• Someone who has set up and maintained CI/CD pipelines with least-privilege IAM roles and OIDC federation
• Strong in networking fundamentals — VPCs, security groups, NLBs, ALBs, DNS (Route53), TLS certificates (ACM/cert-manager)
• The person who automates themselves out of toil and writes the runbook before the pager goes off

Stack you'll live in

AWS (EKS, Aurora, MSK, ElastiCache, S3, CloudFront, Route53, ACM, EFS) · Kubernetes 1.25 · Terraform · GitHub Actions · HashiCorp Vault · Apache Flink · ClickHouse (Altinity Cloud) · Loki · Helm · SOPS + KMS · Docker / ECR · Prometheus

Not a fit if

• You've only used managed Kubernetes through a UI — we need someone who reads the Terraform and knows what every resource does
• You think infrastructure-as-code means a CloudFormation template someone else wrote
• You can't debug a pod that won't schedule without googling every error message