Jobs Data Engineer

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.

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.

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).

We are looking for an experienced Data Engineer to design and maintain robust data infrastructure across our systems. In this role, you will be responsible for building scalable data pipelines, ensuring data integrity, and integrating third-party data sources. Your primary focus will be to enable efficient data flow and support analytical capabilities across the organization. You will also contribute to the development of our data architecture, implement best engineering practices, and collaborate closely with cross-functional teams to turn raw data into actionable insights.

Requirements

• 3+ years of commercial experience in Data Engineering
• Experience gathering business requirements and communicating with stakeholders
• Strong knowledge of Data Warehouse (DWH) architecture and principles
• Hands-on experience designing data warehouses and building ETL pipelines
• Deep practical experience with Python
• Hands-on experience in one or more of the following areas: data processing using PySpark, Apache Spark, Pandas, or similar frameworks; data scraping; integration of third-party data sources and APIs
• Proficiency in SQL and relational databases such as PostgreSQL and MySQL
• Hands-on experience with column-oriented databases such ClickHouse, Snowflake, Cassandra, BigQuery (many tables with millions of records and above each)
• Solid understanding of software design patterns, algorithms, and data structures
• Intermediate English proficiency

Will be a plus

• Experience with messaging platforms such as RabbitMQ or Kafka
• Familiarity with DataOps practices and data pipeline automation
• Familiarity with CI/CD pipelines and Kubernetes environments
• Background in FinTech or Trading domains

Responsibilities

• Communicate with technical and non-technical stakeholders to gather and clarify business requirements
• Review and analyze data and business logic to ensure consistency, accuracy, and reliability
• Design, implement, and maintain data pipelines for efficient and scalable data processing
• Integrate, maintain, and support data solutions and third-party data sources
• Research and evaluate third-party tools, services, and components for potential use
• Follow engineering best practices, including code reviews, testing, refactoring, and continuous delivery
• Design, optimize, and maintain data storage solutions

What we offer:

• Tax expenses coverage for private entrepreneurs in Ukraine
• Expert support and guidance for Ukrainian private entrepreneurs
• 20 paid vacation days per year
• 10 paid sick leave days per year
• Public holidays as per the company’s approved Public holiday list
• Medical insurance
• Opportunity to work remotely
• Professional education budget
• Language learning budget
• Wellness budget (gym membership, sports gear and related expenses)