Jobs Data Engineer

Компанія шукає досвідченого Data Engineer для участі у розробці та підтримці високонавантажених систем. Якщо ви глибоко розумієтесь на внутрішній архітектурі SQL Server, вмієте оптимізувати продуктивність запитів та маєте досвід побудови ETL-процесів — будемо раді бачити вас у нашій команді!

Вимоги до кандидата:

• Досвід роботи з MS SQL Server від 3 років.
• Робота з версіями SQL Server 2016 і вище.
• Досвід супроводу високонавантажених або критично важливих систем.
• Глибоке розуміння внутрішньої роботи SQL Server (query processor, execution plan, tempdb, buffer pool, indexes, statistics).
• Досвід оптимізації запитів, процедур, індексів, аналіз execution plans.
• Вміння налаштовувати та моніторити продуктивність СУБД.
• Досвід створення ETL-процесів з використанням SSIS, T-SQL або сторонніх інструментів (наприклад, Airflow).
• Знання job-менеджменту: SQL Agent Jobs, планувальники, сповіщення.
• Досвід автоматизації завдань (знання Python буде перевагою).

Технічний стек:

• MS SQL Server,
• T-SQL (рівень Advanced),
• SSMS, SSIS, SQL Profiler, Query Store,
• Git,
• Python (бажано).

Основні обов’язки:

1. Розробка та підтримка складних T-SQL скриптів, збережених процедур, тригерів, функцій і представлень.
2. Оптимізація продуктивності SQL-запитів, виявлення вузьких місць, робота з execution plans, індексами, статистикою.
3. Проєктування та рефакторинг схем баз даних відповідно до бізнес-вимог.
4. Підтримка та розвиток ETL-процесів, контроль якості даних, участь у побудові потоків даних.
5. Співпраця з розробниками, аналітиками, архітекторами, участь у командних рішеннях.
6. Налаштування моніторингу, створення алертів, звітність по стабільності та продуктивності систем.
7. Менторство молодших фахівців, участь у code review, обмін знаннями.
8. Документування рішень, участь у створенні внутрішніх стандартів і процедур.

Ми пропонуємо:

• Роботу над цікавими проєктами в стабільній компанії.
• Можливість розвиватися професійно та впливати на технічні рішення.
• Команду професіоналів та дружню атмосферу.
• Гнучкий графік, можливість віддаленої роботи.
• Конкурентну заробітну плату та бонуси за результатами роботи.

TemaBit Fozzy Group - ІТ-компанія, яка розробляє унікальні рішення для більш ніж 40 бізнесів групи. Ми спеціалізуємося на веб- та мобільній розробці, а також софті для менеджменту бізнес-процесів та інфраструктурних проєктів.    

Крім того, експериментуємо і піклуємося про команду та Гостя, топимо за співпрацю, проповідуємо чесність і відкритість. 

Шукаємо інженера, який візьме на себе розвиток централізованої платформи збору, обробки та аналізу логів і метрик на базі ELK Stack (Metrics, Events, Logs, Traces). Це не підтримка існуючого - команда активно розвиває платформу, тож знадобиться людина, яка розуміється на observability в широкому сенсі та готова приймати архітектурні рішення, а не тільки виконувати таски.

Задачі на посаді: 

• Розгортання, налаштування та підтримка ELK Stack (Elasticsearch, Logstash, Kibana)
• Проектування та підтримка pipeline збору та обробки логів і метрик
• Аналіз, оптимізація та управління даними в Elasticsearch
• Створення та підтримка dashboards, візуалізацій та алертів у Kibana
• Інтеграція ELK з іншими системами та джерелами даних

• Траблшутинг та вирішення інцидентів ELK інфраструктури

   

Наші вимоги: 

• Від 3 років досвіду на позиціях ELK Engineer / Elastic Stack Engineer, Observability Engineer, DevOps/Platform Engineer (з фокусом на logging/monitoring) або Monitoring Engineer
• Впевнене володіння Elasticsearch - ILM, mappings, DSL, troubleshooting
• Досвід роботи з Kibana - dashboards, KQL, alerting, RBAC
• Logstash - побудова pipelines, фільтрів, інтеграцій
• Досвід з Elastic Agents (Filebeat/Metricbeat, Fleet)
• Linux - робота з сервісами, мережею, bash-скриптинг
• Практичний досвід роботи з логами, метриками та observability pipeline у продакшн-середовищі
• Англійська - B2 (Upper-Intermediate)
   

Ми пропонуємо: 

• Гнучкий формат роботи: працюй з дому або з офісу (з надійним укриттям). 
• Підтримку Гіг-контракту.  
• Навчання для поглиблення твоєї експертизи у Fozzy Campus - нашому корпоративному університеті з топовими спікерами. 
• Бенефіти, які вибираєш самостійно - у нашому кафетерії кожен обирає свій ідеальний набір (чи то медичне страхування, чи то компенсація спорту). 
• Широчезна колекція приємних пропозицій від бізнесів Fozzy Group та наших партнерів.  
• Консьєрж-сервіс для працівників, який звільняє тебе від побутового клопоту. 

About the role

We're looking for a Middle DevOps Engineer to join our engineering team and help build, automate, and maintain reliable cloud infrastructure. You'll work closely with software engineers, QA, and architects to improve deployment processes, optimize cloud environments, and ensure high availability of our applications.

Responsibilities

• Design, implement, and maintain cloud infrastructure in AWS and Microsoft Azure.
• Build and improve CI/CD pipelines.
• Automate infrastructure provisioning using Infrastructure as Code.
• Monitor application performance and infrastructure health.
• Improve system reliability, scalability, and security.
• Collaborate with development teams to streamline deployment processes.
• Troubleshoot production issues and participate in incident response.
• Optimize cloud costs and infrastructure performance.
• Maintain documentation and operational best practices.

Requirements

• 4+ years of experience as a DevOps Engineer or Site Reliability Engineer.
• Hands-on experience with both AWS and Microsoft Azure.
• Strong knowledge of Linux administration.
• Experience with Docker.
• Experience with Infrastructure as Code (IaC) using Terraform.
• Experience building CI/CD pipelines using Bitbucket Pipelines or other modern CI/CD platforms (e.g., GitHub Actions, GitLab CI, Jenkins, Azure DevOps).
• Knowledge of networking fundamentals (DNS, VPN, Load Balancers, Firewalls).
• Experience with monitoring and logging tools (Prometheus, Grafana, ELK, Datadog, CloudWatch, Azure Monitor, etc.).
• Experience with scripting (Bash, Python, or PowerShell).
• Understanding of security best practices and IAM.
• Experience working with Git.
• Good communication skills in English.

Nice to have

• AWS and/or Azure certifications.
• Experience with Kubernetes.
• Experience with serverless solutions.
• Experience with PostgreSQL, MySQL, or SQL Server administration.
• Experience with Redis, RabbitMQ, or Kafka.
• Knowledge of FinOps and cloud cost optimization.

PLEASE NOTE that we are searching for candidates who are located in Lviv and are able to visit office in Lviv.

About us:

EveryMatrix is a leading B2B SaaS provider delivering iGaming software, content and services. We provide casino, sports betting, platform and payments, and affiliate management to 200 customers worldwide.

But that's not all! We're not just about numbers, we're about people. With a team of over 1000 passionate individuals spread across twelve countries in Europe, Asia, and the US, we're all united by our love for innovation and teamwork.

EveryMatrix is a member of the World Lottery Association (WLA) and European Lotteries Association. In September 2023 it became the first iGaming supplier to receive WLA Safer Gambling Certification. EveryMatrix is proud of its commitment to safer gambling and player protection whilst producing market leading gaming solutions.

Join us on this exciting journey as we continue to redefine the iGaming landscape, one groundbreaking solution at a time.

We are looking for a passionate and dedicated Strong Middle BI/DB Developer to join our team in Lviv!

What You'll get to do:

• Develop real‑time data processing and aggregation pipelines.
• Create and modify data marts to enhance the data warehouse.
• Manage internal and external integrations.
• Design and deliver various types of reports.
• Main Stack Databases: Google BigQuery, PostgreSQL, SQL ETL: Apache Airflow, Apache NiFi Streaming: Apache Kafka

What You need to know:

• Bachelor’s or Master’s degree in a STEM field.
• Solid understanding of Computer Science fundamentals: Software Engineering, Algorithms, Operating Systems, Networking, etc.
• Strong knowledge of at least one RDBMS (Google BigQuery, PostgreSQL, MSSQL, Oracle, MySQL), including: Query optimization Indexing strategies; Partitioning Practical experience with ETL/ELT processes.
• Experience in creating or supporting Data Warehouses.
• Hands‑on experience with at least one enterprise Business Intelligence platform.
• English: Intermediate+ (reading, writing, speaking).
   

Nice to have:

• Knowledge of analytical data warehouse systems (Google BigQuery, Azure Synapse Analytics, AWS Redshift, Snowflake).
• Programming skills in one language (Python or Java).
• Experience with additional tools and systems such as Apache Airflow and Apache NiFi.
  
  Here's what we offer:
• Start with 22 days of annual leave, with 2 additional days added each year, up to 32 days by your fifth year with us.
• 3 sick leave days per year, no doctor's note required; 30 medical leave days with medical allowance
• Hybrid work schedule is available after the first three months of employment with 80/20 office/home format until the end of 2026. Starting from 2027, the policy will transition to primarily office-based work, with up to 10 work-from-home days per year with manager approval.
• Benefit from two Free Fridays each year, limited to one per quarter.
• Daily catered lunch or monthly lunch allowance. 
• Private Medical Subscription. 
• Access online learning platforms like Udemy for Business, LinkedIn Learning or O’Reilly, and a budget for external training.
• Gym allowance.
• Corporate English lessons.
• Support for New Parents:
• 21 weeks of paid maternity leave, with the flexibility to work from home full-time until your child turns 1 year old.
• 4 weeks of paternity leave, plus the flexibility to work from home full-time until your child is 13 weeks old.

Our office perks include on-site massages and frequent team-building activities in various locations.

At EveryMatrix, we're committed to creating a supportive and inclusive workplace where you can thrive both personally and professionally. Come join us and experience the difference!

We're building a greenfield high-load media platform from scratch, allowing you to shape the architecture, choose the technology stack, and make key engineering decisions from the very beginning. This isn't about maintaining legacy systems—it's about designing and delivering scalable solutions that will evolve from PoC into production

You'll tackle complex engineering challenges around WebRTC, low-latency streaming, SFU/TURN infrastructure, and scaling the platform to 300,000 concurrent connections and 3M+ requests per second. As part of a small, highly skilled team, you'll have real ownership, fast decision-making, and the chance to build rare, highly valued expertise while making a visible impact on the product

In this role, you will

• Design and build the infrastructure for a greenfield streaming/WebRTC platform, ensuring scalability, low latency, and high availability
• Develop and maintain CI/CD pipelines and deployment strategies to support fast and reliable releases
• Manage cloud infrastructure and Kubernetes clusters using Infrastructure as Code tools
• Implement autoscaling, performance optimization, and load testing to ensure the platform can handle high traffic and peak loads
• Build and improve the platform's observability by implementing monitoring, logging, tracing, and alerting solutions
• Optimize infrastructure for performance, reliability, security, and cost efficiency
• Collaborate closely with backend engineers and product teams, contributing to architectural decisions and the evolution of the platform

It’s all about you

• 3+ years of experience as a DevOps Engineer in production environments
• Experience designing and building high-load infrastructure from scratch
• Hands-on experience with streaming, WebRTC, or social/multimedia products
• Production experience with Kubernetes, including scaling, autoscaling, and troubleshooting
• Expertise in Infrastructure as Code using Terraform and/or Ansible
• Experience with AWS or GCP, including compute, networking, and managed services
• Experience building CI/CD pipelines using GitLab CI or GitHub Actions, along with GitOps tools such as ArgoCD and Helm
• Knowledge of observability tools, including Prometheus, Grafana, logging, and distributed tracing
• Strong networking fundamentals, including UDP, RTP/RTCP, low-latency networking, and TURN/STUN (coturn)
• Experience with load testing and performance optimization for high-traffic production systems

Would be a plus

• Experience with media servers, such as mediasoup, LiveKit, Janus, or Jitsi
• Experience optimizing bandwidth-heavy streaming platforms and improving infrastructure cost efficiency
• Proficiency in scripting with Python, Go, or Bash

What we offer

Care and support: 

• 20 paid vacation days, 15 sick leave days, and 6 additional days off for family events
• 100% medical insurance coverage
• Sports and equipment reimbursement
• Team building events, corporate gifts, and stylish merch
• Financial and legal support
• Maternity Recovery Support Allowance
• Position retention and support for those who join the Armed Forces of Ukraine
• Participation in social initiatives supporting Ukraine

Comfortable working environment:

• Work from our Kyiv hub or remotely with a flexible schedule
• Modern equipment or depreciation of your own tools

Investment in your future:

• Collaborate with a highly-skilled team of Middle & Senior professionals, sharing practical cases and expertise in the social networking niche
• 70% of our heads and leads have grown into their roles here – so can you!
• Performance-oriented reviews and Individual Development Plans (IDPs)
• Reimbursement for professional courses and English classes
• Corporate library, book club, and knowledge-sharing events

Hiring process

• Intro call
• Technical Interview
• Final Interview
• Reference check 
• Offer
   

We are looking for a Senior/Lead Big Data Engineer who can help us to create the data pipelines for the data platform we are designing now.

-3+ years of hands-on experience in the big-data field: Hadoop, Spark, Spark Streaming, MR.

-3+ years of experience with relevant cloud data services (AWS, Azure, GCP) like EMR, Glue, S3, Lambda, Fargate, DynamoDB, ADF, Azure functions, Azure Blob Storage, DataProc & DataFlow, BigQuery.

-Knowledge of DataBricks will be significant benefit for the candidate.

-Excellent knowledge and hands-on experience of SQL in context of Big Data: Spark SQL, Hive QL

- Ability to understand and optimize Spark execution plans via Spark UI

- Excellent knowledge of Python or Scala

- Batch processing and ETL principles in Data Warehouses.

- Data completeness signals and orchestration

- Approaches for historical reprocessing and data correction

- Handling bad data and late data in inputs and outputs

- Schema migrations and datasets evolution

- B2 Strong speaking English.

- Ability to learn fast new set of tools and technology used internally: Radar, platform services, telemetry providers, Spark-as-a-Service, build system and much more.

Will be a plus

- Understanding of functional programming ideas and principles.

- Experience in building and using web services.

- Experience with any of Teradata, Vertica, Oracle, Tableau.

- Spark Streaming and Kafka.

- Experience or knowledge of: Apache Iceberg, Trino (Presto), Druid, Cassandra, Blob storage like AWS.

- Understanding or experience with Azkaban or Airflow.

Description

The Digital Health organization is technology team which focused on next generation Digital Health capabilities which deliver on the Medicine mission and vision to deliver Insight Driven Care. This role will operate within the Digital Health Applications & Interoperability subgroup of the broader Digital Health team, focused on patient engagement, care coordination, AI, healthcare analytics & interoperability amongst other advanced technologies which enhance our product portfolio with new services, while improving clinical & patient experiences.

The project is a cloud-based PaaS Ecosystem built with a privacy by design centric approach to provide a centralized cloud-based platform to store, classify, and control access to federated datasets in a scalable, secure, and efficient manner.

The ecosystem will allow Customer Operating Units (medical device departments) to store federated data sets of varying sizes and formats and control access to those data sets through Data steward(s). Source data sets can be exposed to qualified use cases and workflows through different project types.

The Healthcare Data Platform ecosystem will provide ML/AI project capabilities for streamlined development processes and a ML/AI workbench to enhance data exploration, wrangling, and model training.

In queue: 15+ OU’s. At this moment focused on – Nuero, Cardio, Diabetes is the OU that data platform is working with, but there could be more OU’s coming up with requirements in future.

GL Role: is to work on the enhancement of current capabilities, including taking over the work that AWS proserve team is doing, and develop new requirements that will keep coming from different OU’s in the future.

Requirements

• AWS Platform: Working experience with AWS data technologies, including S3, AWS RDS, and Lake Formation
• Programming Languages: Strong programming skills in Python
• Data Formats: Experience with JSON, XML, and other relevant data formats
• CI/CD Tools: Ability to deploy using established CI/CD pipelines using GitLab CI, Jenkins, Terraform or similar tools
• Scripting and automation: experience in scripting languages such as Python, PowerShell, etc.
• Monitoring and Logging: Familiarity with monitoring & logging tools like CloudWatch, Splunk, ELK, Dynatrace, Prometheus
• Source Code Management: Expertise with GitLab
• Documentation: Experience with markdown and in particula,r Antora for creating technical documentation
• Previous Healthcare or Medical Device experience
• Experience implementing enterprise grade cyber security & privacy by design into software products
• Experience working in Digital Health software
• Experience developing global applications
• Strong understanding of SDLC;
• Experience with Agile methodologies
• Software estimation
• Experience leading software development teams onshore and offshore

Job responsibilities

• Implement data pipelines using AWS services such as AWS Glue, Lambda, Kinesis, etc
• Implement integrations between the data platform and systems such as Atlan, Trino/Starburst, etc
• Complete logging and monitoring tasks through AWS and Splunk toolsets
• Develop and maintain ETL processes to ingest, clean, transform and store healthcare data from various sources
• Optimize data storage solutions using Amazon S3, AWS RDS, Lake Formation and other AWS technologies.
• Document, configure, and maintain systems specifications that conform to defined architecture standards, address business requirements, and processes in the cloud development & engineering.
• Participate in planning of system and development deployment as well as responsible for meeting compliance and security standards.
• Actively identify system functionality or performance deficiencies, execute changes to existing systems, and test functionality of the system to correct deficiencies and maintain more effective data handling, data integrity, conversion, input/output requirements, and storage.
• Document testing and maintenance of system updates, modifications, and configurations.
• Leverage platform process expertise to assess if existing standard platform functionality will solve a business problem or customization solution would be required.
• Test the quality of a product and its ability to perform a task or solve a problems.
• Perform basic maintenance and performance optimization procedures in each of the primary operating systems.
• Ensure system implementation compliance with global & local regulatory and security standards (i.e. HIPAA, SOCII, ISO27001, etc…)

Who Are We?

Welltech is a global wellness technology company with Ukrainian roots. Our mission is to build and scale wellness apps globally through state-of-the-art, tech-driven performance marketing.

We are one of the most established players in the wellness app space, and we are accelerating. Over 25.5 million people across the world use our apps — Muscle Booster, Yoga-Go, and WalkFit — to build healthier habits, move more, and feel better every day. Every subscription represents a real person making a real change in their life, and we take that seriously.

With 500+ people across hubs in Cyprus, Ukraine, Poland, Spain, and the UK, we combine the scale of a market leader and the drive of a team that's just getting started.

What We're Looking For

As a Senior Data Engineer, you will play a crucial role in building and maintaining the foundation of our data ecosystem. You’ll work alongside data engineers, analysts, and product teams to create robust, scalable, and high-performance data pipelines and models. Your work will directly impact how we deliver insights, power product features, and enable data-driven decision-making across the company.

This role is perfect for someone who combines deep technical skills with a proactive mindset and thrives on solving complex data challenges in a collaborative environment.

Challenges You’ll Meet:

• Pipeline Development and Optimization: Build and maintain reliable, scalable ETL/ELT pipelines using modern tools and best practices, ensuring efficient data flow for analytics and insights.
• Data Modeling and Transformation: Design and implement effective data models that support business needs, enabling high-quality reporting and downstream analytics.
• Collaboration Across Teams: Work closely with data analysts, product managers, and other engineers to understand data requirements and deliver solutions that meet the needs of the business.
• Ensuring Data Quality: Develop and apply data quality checks, validation frameworks, and monitoring to ensure the consistency, accuracy, and reliability of data.
• Performance and Efficiency: Identify and address performance issues in pipelines, queries, and data storage. Suggest and implement optimizations that enhance speed and reliability.
• Security and Compliance: Follow data security best practices and ensure pipelines are built to meet data privacy and compliance standards.
• Innovation and Continuous Improvement: Test new tools and approaches by building Proof of Concepts (PoCs) and conducting performance benchmarks to find the best solutions.
• Automation and CI/CD Practices: Contribute to the development of robust CI/CD pipelines (GitLab CI or similar) for data workflows, supporting automated testing and deployment.

Required skills:

• 4+ years of experience in data engineering or backend development, with a strong focus on building production-grade data pipelines.
• 2-3+ years of experience working with AWS services (Administration of Redshift is a must),
• Solid experience working with AWS services (Spectrum, S3, RDS, Glue, Lambda, Kinesis, SQS).
• Proficient in Python and SQL for data transformation and automation.
• Experience with dbt for data modeling and transformation.
• Good understanding of streaming architectures and micro-batching for real-time data needs.
• Experience with CI/CD pipelines for data workflows (preferably GitLab CI).
• Familiarity with event schema validation tools/ solutions (Snowplow, Schema Registry).
• Excellent communication and collaboration skills.
  Strong problem-solving skills—able to dig into data issues, propose solutions, and deliver clean, reliable outcomes.
• A growth mindset—enthusiastic about learning new tools, sharing knowledge, and improving team practices.

Tech Stack You’ll Work With:

• Cloud: AWS (Redshift, Spectrum, S3, RDS, Lambda, Kinesis, SQS, Glue, MWAA)
• Languages: Python, SQL
• Orchestration: Airflow (MWAA)
• Modeling: dbt
• CI/CD: GitLab CI (including GitLab administration)
• Monitoring: Datadog, Grafana, Graylog
• Event validation process: Iglu schema registry
• APIs & Integrations: REST, OAuth, webhook ingestion
• Infra-as-code (optional): Terraform

Bonus Points / Nice to Have:

• Experience with additional AWS services: EMR, EKS, Athena, EC2.
• Hands-on knowledge of alternative data warehouses like Snowflake or others.
• Experience with PySpark for big data processing.
• Familiarity with event data collection tools (Snowplow, Rudderstack, etc.).
• Interest in or exposure to customer data platforms (CDPs) and real-time data workflows.

Candidate journey: ⭕️ Recruiter call ➔ ⭕️ Technical call with the hiring manager ➔ ⭕️ Meet the future stakeholders

Locations: Cyprus; Ukraine, Estonia; Bulgaria; Hungary; Latvia; Lithuania; Romania

TJHelpers is committed to developing strong engineering teams through mentorship, real project experience, and our “Helpers as a Service” model. We provide structured growth, hands-on practice, and a supportive environment where engineers can evolve quickly and meaningfully.

We are looking for a Senior AI/LLM Data Engineer (Technical Consultant) to join our team and help design, build, and scale modern data pipelines and retrieval systems for AI-driven products in fintech, healthcare, telecommunications, automation, and other data-intensive domains.

This role is ideal for an engineer who combines strong data engineering fundamentals with hands-on experience in LLM and RAG systems and can contribute not only through implementation, but also through architecture design, technical planning, and consulting-driven engineering decisions.

Responsibilities

• Design and develop scalable data pipelines for AI/LLM products and internal data platforms 
• Build and maintain ingestion, transformation, chunking, enrichment, indexing, and retrieval workflows 
• Prepare and structure data for RAG systems, semantic search, embeddings, and LLM evaluation workflows 
• Support fine-tuning and data preparation workflows for LLM use cases 
• Work with structured, semi-structured, and unstructured data from documents, APIs, databases, and external systems 
• Design and optimize retrieval pipelines, including metadata strategies, filtering, ranking, and relevance improvements 
• Integrate LLM-based solutions with data platforms, vector storage systems, search platforms, and backend services 
• Participate in architecture design, technical planning, and engineering decision-making for AI/LLM initiatives 
• Improve system quality, scalability, reliability, observability, and cost efficiency 
• Diagnose and resolve complex issues in production AI/data environments 
• Collaborate closely with engineers, product teams, analytics, and AI teams 
• Transform business requirements into practical AI/data engineering solutions 

Requirements

• Strong commercial experience in data engineering with hands-on work building data pipelines, ETL/ELT workflows, and distributed data processing systems 
• Hands-on experience with AI/LLM systems, RAG pipelines, embeddings, semantic search, or vector search/retrieval systems 
• Strong Python and SQL skills 
• Experience working with structured, semi-structured, and unstructured data in production environments 
• Strong understanding of data modeling, data transformation, validation, and data quality practices 
• Experience designing scalable and maintainable data workflows 
• Experience with modern data platforms and tools such as Airflow, dbt, Spark, Kafka, or similar technologies 
• Experience with vector databases or search platforms such as Pinecone, Weaviate, Milvus, Elasticsearch, or OpenSearch 
• Understanding of data preparation and optimization techniques for LLM use cases, including chunking, metadata strategies, and retrieval quality improvements 
• Experience with cloud platforms such as AWS, GCP, or Azure 
• Experience with Docker, CI/CD pipelines, and production deployment practices 
• Ability to work independently, make technical decisions, and clearly communicate trade-offs and architectural choices 
• Experience participating in technical consulting, solution design, or client-facing technical discussions 
• English level: B2 or higher 

Nice to Have

• Experience with LLM evaluation frameworks, prompt pipelines, or fine-tuning workflows 
• Familiarity with LangChain, LlamaIndex, or similar orchestration frameworks 
• Experience with reranking, hybrid search, recommendation systems, or knowledge graphs 
• Understanding of MLOps, LLMOps, observability, and experimentation workflows 
• Experience with modern data warehouse or lakehouse platforms such as BigQuery, Snowflake, Redshift, or Databricks 
• Understanding of security, governance, and privacy practices in AI/data systems 

What We Offer

• Work on real-world AI/LLM and data-intensive products 
• Opportunity to participate in architecture, technical discovery, and solution design — not only implementation 
• Collaboration with strong engineers, architects, and product teams 
• Clear growth path toward AI Architect, Data Platform Architect, or Technical Lead roles 
• Open engineering culture focused on ownership, transparency, and continuous improvement 
• Long-term projects, flexible schedule, and fully remote work opportunities

TJHelpers is committed to developing strong engineering teams through mentorship, real project experience, and our “Helpers as a Service” model. We provide structured growth, hands-on practice, and a supportive environment where engineers can evolve quickly and meaningfully.

We are looking for a Junior Data Engineer to join our team and help build and maintain reliable data pipelines, transformations, and datasets for modern products in fintech, AI, telecommunications, healthcare, and other data-driven domains.

This is a great opportunity to work with real-world data, grow in data engineering, and gain hands-on experience with SQL, Python, ETL/ELT processes, and modern data platforms.

Responsibilities

• Support the development and maintenance of data pipelines and ETL/ELT processes 
• Collect, clean, transform, and load data from databases, APIs, files, and external systems 
• Write and optimize SQL queries for data preparation and transformation 
• Assist in building datasets for analytics, reporting, and internal products 
• Support data quality, consistency, and reliability across pipelines and datasets 
• Work with structured and semi-structured data 
• Participate in troubleshooting and improving data processes 
• Assist in monitoring and improving data pipeline reliability and performance 
• Collaborate with engineers, analysts, and product teams 

Requirements

• Basic understanding of data engineering concepts and data pipeline architecture 
• Hands-on experience writing SQL queries and working with Python 
• Understanding of relational databases such as PostgreSQL or MySQL 
• Ability to write SQL queries using joins, filtering, aggregations, and transformations 
• Basic understanding of ETL/ELT processes 
• Understanding of data modeling and data transformation principles 
• Familiarity with data formats such as CSV and JSON and working with APIs 
• Basic understanding of structured and semi-structured data 
• Analytical thinking and attention to detail 

• Motivation to learn and grow in a technical environment 

   

Nice to Have

• Basic experience with Pandas 
• Basic familiarity with Spark or PySpark 
• Familiarity with Airflow, dbt, or similar tools 
• Understanding of data warehouses such as BigQuery, Snowflake, or Redshift 
• Familiarity with cloud platforms such as AWS, GCP, or Azure 
• Familiarity with Git 
• Experience with BI or analytics tools 

• Interest in data platforms, analytics engineering, or ML/AI workflows 

   

What We Offer

• Work with real production data systems and modern technologies 
• Mentorship from experienced engineers and tech leads 
• Clear growth path to Middle Data Engineer level 
• Supportive engineering culture focused on learning and practical development 
• Flexible schedule and fully remote work opportunities

About us:
Gismart is a value-driven mobile app developer with a strong presence in the Health & Wellness, Utilities, and Music app markets. We have recently achieved a significant milestone of over 1 billion downloads worldwide, taking a step toward our mission of cultivating the well-being of people worldwide. With headquarters in London, UK, Gismart is a dynamic global company with a reach extending across Europe and far beyond. Our determined team consists of 250 individuals who bring diversity, creativity, innovation, and relentless drive to the company. Gismart unites professionals from diverse backgrounds in entertainment, music, and tech, allowing us to play to each other’s strengths and succeed as a team.
 

Our mission:
Become a stepping stone on our customers’ journeys of self-improvement.
 

Our values:

• Deliver what matters
• Respect and support others
• Initiate and own
• Voiceopenly
• Execute with quality
   

If you are passionate about mobile app development and want to join a company that’s reshaping the industry, Gismart is the place for you. We provide exciting career opportunities, a supportive workplace culture, and the chance to contribute to a team that is making a tangible impact. For more information on Gismart, visit gismart.com.
 

About project

FitMe is a fitness app created for people who want to stay active without long, repetitive workouts. It offers short, easy-to-follow routines that can be done at home with no equipment. FitMe is perfect for busy people who want to maintain their health, boost energy levels, and feel good every day — without going to the gym or spending hours on exercise.
 

What you will do:

• Stakeholder support: ad-hoc validation of figures, investigation of discrepancies between dashboards, ensuring availability of the BI platform.
• Development and support of ETL/ELT pipelines for analytical reports (cohort revenue, LTV, retention, KPI by creatives, post-purchase analytics).
• Support for attribution models (Web↔Mobile mapping, multi-locale cost-cohort resolve, last-click vs raw events).
• Integrations with external sources: Meta Marketing API, AppsFlyer, AppMetrica, Stripe, Tableau Server (TSC), Birch.
• Data quality assurance: schema/freshness/volume checks, broken-snapshot detection, anti-bot-traffic filtering.
• Performance optimization of queries and procedures in Redshift.
• Collaboration with BI Team, Product / UA / Billing analysts.
   

Key qualifications:

• 1-2 years of commercial experience in data engineering / analytics engineering / BI development.
• Experience with data warehouse, data lake and data lakehouse concepts.
• Proven experience in designing, implementing and supporting ETL/ELT pipelines.
• Experience with AWS, Amazon Redshift, Apache Airflow.
• Advanced SQL, hands-on experience in designing production-level Python code.
• Willingness to deal with business logic (subscription, monetization, attribution) — with team support.
   

Would be a plus:

• Experience with Infrastructure as Code (Terraform).
• Experience with dbt, Apache Spark, Apache Iceberg
• Experience with UA-attribution stack (AppsFlyer, AppMetrica, Adjust, SKAN, GA4) and UA cost APIs (Meta, Google Ads, TikTok, AppLovin).
   

Employee Benefits:

• Remote-First Culture: Our team is diverse and extensive, just like our product portfolio. We provide a flexible working schedule and let you work anywhere in the world, either remotely or in one of our corporate hubs.
• Сoworking Compensation: We provide 100% compensation for coworking spaces in Ukraine (except Kyiv, where we have a cozy and autonomous hub) and 50% compensation for coworking spaces worldwide to make sure that everyone has a comfortable and inspiring workspace.
• Free Office Lunches: We want you to stay fueled and focused, so we provide delicious free lunches for everyone working from our hubs. It’s one less thing for you to worry about during a productive workday.
• Public Holidays Policy: Gismart observes public holidays based on the Ukrainian or Polish holiday calendars. Employees working in other locations are entitled to 12 public holidays per year.
• 100% Sick Leave Compensation.
• Mental and Physical Health: To help you stay happy and healthy, Gismart will partially cover your medical insurance, sports activities, therapy costs.
• Personal Equipment Policy: Of course, we’ll provide you with all the equipment you need or cover the maintenance cost for your own tools.
• Personal Learning and Development: We love to see you learn and grow, so Gismart will cover 70% of your professional development courses. We’ll also pay for 100% of corporate English courses.
• Time-Off Policy: Every employee gets 18 working days of paid vacation and 3 personal days per year, with an extra day added for each year at Gismart.
• Corporate Events: We are remote-first, but we love meeting up in person. Whenever possible, we organize corporate events and team-building activities across all Gismart hubs.

About us
We're building the unified data layer for private credit fund managers. We ingest, reconcile, and make sense of the financial data that fund CFOs and controllers live inside every day — NAV calculations, LP returns, reconciliation across GP records and fund administrators, SBIC compliance filings — and turn it into a trusted, queryable foundation for every decision the fund makes.
We're a seed-stage company with real customers, real data, and real financial stakes. Design partners and early clients depend on the accuracy of our platform for their fund reporting today. A silent data error costs us a customer permanently. That trust is the moat, and it's what makes this role matter.

About The Role
We're making a deliberate bet that one AI-native engineer running multiple agents in parallel against a well-built harness outperforms three traditional full-stacks. We have evidence this is true. We also know the critical qualifier: only if the harness is real. Without it, you ship a house of cards. This role exists to make the harness real. You are the load-bearing infrastructure hire for our AI-native engineering model. Everything our product engineers ship — every agent-generated diff, every behavioral test that catches a regression, every eval that defines what "passes" — runs on infrastructure you own.

This is not DevOps in the traditional sense. It's a new category: AI engineering infrastructure. Your instincts come from platform and DevEx backgrounds, but your domain is non-deterministic systems, LLM-app observability, and the specific failure modes that emerge when agents write production code.
Here's what you're walking into: our current local dev environment cannot run a full agent iteration cycle. The background job system that LangGraph agents require doesn't exist. The eval suite doesn't exist. You're not inheriting a platform — you're building the foundation that makes the whole model work, and you'll be doing it alongside our lead product engineer from day one.

Crucially, this is a day one partnership with the Lead Product Engineer: you build the system/harness, and they ship the features against it—a tight, mutual dependency. You won't be writing day-to-day product features. Instead, you'll build the systems the engineers shipping product depend on.

Key Responsibilities
I. Foundation (Months 1-2): The work that unblocks the AI-native model.
- Local Dev Environment: Our importers are manual CLI runs disconnected from S3 events. An agent iterating locally today cannot test against a real ingestion run. Your first deliverable is a local dev environment where an agent's diff can be run end-to-end before it touches staging.
- Async Execution Infrastructure: An agent orchestration framework's workflows require async execution. We have no background job system today. You'll select and ship it — a lightweight queue + worker setup on our existing AWS/ECS stack — as part of Month 1-2.
- First Agent Workflow: Get a single workflow for an agent orchestration framework running end-to-end against our FastAPI/PostgreSQL stack. Nothing in our agent roadmap ships without this foundation.
II. The Agent Harness
- Skills & Eval Infrastructure: Build the skills system, prompt library, and eval suite that make agent-generated code production-grade. These are the shared tools every product engineer relies on.
- Automated Review Pipeline: Stand up multiple layers of automated review — Cursor bot, Claude reviewer, independent Claude agents — so that agent-generated diffs face real scrutiny before human eyes touch them.
- Behavioral Test Infrastructure: Build the test framework that gates product deploys. End-to-end behavioral tests catch what unit tests don't. You build the system; product engineers write the tests.
III. CI/CD & Observability
- Agent-Aware CI/CD: Extend our GitHub Actions pipeline with regression catches, schema contract tests against the data layer, and lint rules tuned to our common agent failure modes. The pipeline should catch what matters without making deploys slow.
- Agent Observability: Instrument every agent run — what prompt produced what diff, what tests caught what, where humans had to intervene. This instrumentation is also our SOC 2 audit trail for AI-generated changes. Build it with compliance in mind from day one.
- Prod-Like Dev Environments: Ensure local dev mirrors production closely enough that an agent's output can be trusted before review. This is load-bearing, not nice-to-have.

What Success Looks Like
Within your first 6-12 months, success will look like:
- The harness is real: A product engineer can run 4-10 agents in parallel against a local environment, get behavioral test results back, and know what they're shipping before it hits staging.
- Agent runs are observable: We can answer "what prompt produced this diff?" and "what tests caught the last regression?" from logs, not from memory.
- SOC 2 audit trail is complete: Every AI-generated change in production has a logged record of the prompt, review layers, and tests that gated it. The auditor has what they need.
- CI/CD catches agent failure modes: The pipeline has caught at least one class of agent-generated bugs that would have reached production without it.
- Product engineering throughput is compounding, not collapsing: The product team is shipping fast because the infrastructure is real — not fast in ways that will become rework.

The Ideal Candidate
You might be a strong fit if you:
- Have 5+ years of platform, DevEx, or infrastructure engineering — you've built developer tooling that other engineers actually relied on in production, not experiments that sat unused
- Are hands-on with AWS — we run ECS/Fargate, S3, RDS on PostgreSQL 18, SES; IaC fluency (Terraform or Pulumi) is expected
- Has built eval harnesses or test infrastructure specifically for AI-generated or non-deterministic outputs
- Have strong opinions about behavioral testing and evals for non-deterministic systems — you understand why golden-set test design for LLM outputs is different from traditional test engineering
- Have experience with LLM-app observability or agent system instrumentation — you know what to log to understand why an agent produced what it produced
- Are comfortable in Python and TypeScript — enough to read and reason about what the product engineers are shipping, even if you're not writing features yourself
- Approach infrastructure with a "what breaks under load?" mindset — you build for the failure mode, not the happy path

Nice to have (but not required):
- Experience with an agent orchestration framework, observability stack, or equivalent tools.
- Fintech or compliance context — understanding why the audit trail is load-bearing, not optional
- Multi-tenant environment isolation on AWS

Must-have skills

- Platform / DevEx / Infrastructure Engineering — 5+ years

Experience building internal developer platforms, local development environments, CI/CD pipelines, and developer tooling for other engineers.

- AI Agent / LLM Infrastructure — 2+ years

Experience with agent orchestration, evaluation harnesses, behavioral testing, LLM observability, and infrastructure for non-deterministic AI systems.

- AWS + Infrastructure as Code — 3+ years

Hands-on experience with AWS services (ECS/Fargate, S3, RDS), queues/workers, GitHub Actions, and Infrastructure as Code using Terraform or Pulumi.

English B2+
wokring hours till 24 Kiev time !!!!

We are looking for an Integration Engineer to design, build, and maintain reliable integrations between our advertising platform and external marketing services.
 

What you will do

— Develop and maintain integrations with Meta Marketing API and LinkedIn Marketing API: rate limits, async reports, breakdowns, attribution windows.

— Build and support data synchronization pipelines from Ad Platform APIs to BigQuery/ClickHouse via Cloud Run Jobs and n8n workflows.

— Ensure reliability of data sync: error handling, retry strategies, monitoring and alerting.

— Work with API rate limits, OAuth flows, and webhooks across advertising platforms.

— Participate in new integration projects from API evaluation through production rollout.

— Write production-grade Python code: error handling, logging, tests, documentation.

— Actively use AI-assisted development tools (Copilot, Cursor, Claude Code) for code generation, debugging, and pipeline design.
 

Requirements

— 5+ years in backend or data engineering with focus on API integrations.

— Hands-on experience with Meta Marketing API and/or LinkedIn Marketing API: real work with rate limits, async reports, breakdowns, attribution windows.

— Strong Python skills: production-grade code with error handling, logging, and tests.

— Solid understanding of data pipeline patterns: idempotency, backfill, incremental sync, schema evolution.

— Experience with GCP or comparable cloud (AWS/Azure) at service level: Cloud Run, BigQuery, or equivalents.
 

Nice to Have

— Knowledge of Programmatic ecosystem: DV360, The Trade Desk, OpenRTB.

— Experience with BigQuery and/or ClickHouse.

— Pulumi / Terraform for IaC.

— Understanding of advertising metrics: impressions, clicks, conversions, ROAS, attribution models.

— Experience with n8n or similar workflow orchestration tools.
 

What We Offer

— Fully remote with flexible hours (aligned with EU timezones for syncs).

— AI-first tooling — Claude Code licenses and cutting-edge AI development workflows.

— A team with no bureaucracy, decisions are made fast.

Не просто код, а твій вплив на мільйони українців!

Nova Digital — це технологічне серце екосистеми NOVA, де твій код стає частиною щоденного життя цілої країни.

Про масштаб наших сервісів:

• 50+ млн запитів щодня проходять через наші системи
• 10+ млн активних користувачів покладаються на наші рішення

Ми будуємо не просто продукт — ми створюємо технологічну інфраструктуру, яка об’єднує людей, бізнеси та можливості вже майже по цілому світу.

Що робитимеш як Middle Data Engineer:

• створення та підтримка масштабованих та надійних конвеєрів даних для прийому даних з різних джерел (внутрішні системи, APls, зовнішні платформи);
• робота зі структурованими, напівструктурованими даними, забезпечуючи якість, узгодженість та цілісність даних;
• розробка та підтримка процесів ETL/ELT; 
• обробка великих масивів даних в Spark (Data Lake); 
• оптимізація PySpark пайплайнів; 
• робота з структурами даних JSON, Parquet; 
• створення вітрин даних в BigQuery; 
• робота з Postgres та MSSQL.

Твій ідеальний профіль:

Must-have:

• 3+ років досвіду в сфері Data Engineering;
• професійний досвід роботи з Python, PySpark, GCP; 
• досвід роботи з SQL (MS, Postgres, BigQuery) ;
• досвід побудови пайплайнів міграції даних (ETL) ;
• досвід роботи з Apache Airflow; 
• навички роботи з GCP сервісами: (PubSub, Dataproc, Composer, CloudStorage); 
• досвід роботи з форматами JSON, Parquet.
  

Nice-to-have:

• досвід роботи з Tableau або іншими BI інструментами.

Чому експерти різних напрямів працюють з нами:

Технологічно:

• Високонавантажені системи з реальними викликами масштабування

• Сучасний стек та свобода технологічних рішень

• Можливість впливати на архітектуру продуктів, якими користуються мільйони

Професійно:

• Менторство від сеньйорів з досвідом enterprise-рішень

• Разом будуємо інновації, що працюють для мільйонів

Ідейно:

• Продукт, що змінює країну — не просто ще один стартап

• Тут команди стають драйверами технологічних змін

Benefits:

• Компенсація додаткових витрат, пов'язаних з робочими завданнями, здійснюються до внутрішніх політик компаній.

• Добровільне медичне страхування та страхування життя.

• Корпоративні знижки від партнерів NOVA.

• Підтримка ментального здоров'я. Можливість безоплатних консультацій з корпоративним психологом.

• Соціальна відповідальність та волонтерський рух “Свої для своїх”.

• Клуби за інтересами: біговий, шаховий та інші ініціативи для натхнення.

• Соціальні відпустки та компенсації відповідно до КЗпП України.

Наступний крок за тобою.
Ми  чекаємо на знайомство — залишилось лише отримати твоє резюме.

Очікуваний термін відповіді — до 10 робочих днів.

It's a product company at the core of Web3 infrastructure — the connectivity layer between wallets and apps across blockchains. Since 2018 they've grown to 75K+ apps, 700+ wallets, 50M+ users, backed by $38M (Union Square Ventures, Shopify, Coinbase Ventures, Circle Ventures, Uniswap Labs). They've just launched a crypto & stablecoin payments product — already live in Stripe, Coinbase Commerce, Shopify, and BitPay, plus an Ingenico deal reaching 40M+ terminals in 120+ countries.

This role sits at the intersection of data engineering and backend systems. You’ll build and operate event-driven data pipelines, maintain real-time processing systems, and ensure data quality across high-volume transactional workflows. You’ll also build backend services that expose data to internal platforms and APIs, so teams across the company can consume it.

Day-to-day, you’ll work with Python, SQL, ClickHouse, Airflow, and dbt within an event-driven architecture. You’ll own the systems you build end-to-end — including monitoring, reliability, and data correctness — and collaborate with product, engineering, and infrastructure teams to support new data use cases as the platform grows.

What they're after:

• 5+ years in data engineering — production pipelines you've built and operated
• Event-driven, real-time / near real-time processing
• Strong SQL + Python; modern stack (Airflow, dbt, ClickHouse, BigQuery, or similar)
• Nice to have: fintech/payments data, Web3, Rust

IMPORTANT: The company considers candidates only from fintech, payments, or high transaction volume products (e.g. Stripe, Adyen, Checkout.com, Revolut, and similar).