Jobs Data Engineer

Our customer is a leader in global prestige retail, teaching and inspiring clients to play in a world of beauty. The company has earned its reputation all over the world as a beauty trailblazer with its expertise, innovation, and entrepreneurial spirit. Our project is about developing a full-stack e-Commerce application for the world's biggest cosmetics retailer chain of stores.

PROJECT TECHNOLOGIES AND TOOLS

SQL, HIVE

Hadoop

Kafka

Spark

Spark Streaming

Cloud (Azure)

Scala or Python

RESPONSIBILITIES

Investigation and requirements clarification

Solution architecture design from scratch

PoC development

Full project delivery

Interactions with the customer development team and 3-rd party vendor

REQUIREMENTS

5+ years of experience in Java/Scala or Python

Experience with HIVE

Strong communication skills

Intermediate or higher English level, both spoken and written (B1+)

NICE TO HAVE

Databricks

Avro

Spark

Apache Hadoop

WE OFFER

Competitive compensation depending on experience and skills

Individual career path in engineering

Social package - medical insurance, sports

Compensation for sick lists and regular vacations

English classes with certified English teachers

Flexible work hours

We are looking for a Senior / Lead Data Analytics and Visualization Engineer passionate about data to extend our team of professionals. In this role, you will work with clients from various business domains – Finance, Telecom, Media, Insurance, Oil&Gas, Pharma and others.

The remote option applies only to the Candidates who will be working from any location in Ukraine.

Responsibilities

• Build advanced-level dashboards and reports
• Design and build data models, conduct data preparation and profiling
• Perform detailed analysis of business problems and technical environments
• Manage security and administrate the reporting environment
• Participate in architecture and testing processes to ensure they meet best practice specifications
• Participate in architecture and testing processes to ensure they meet best practice specifications

Requirements

• 5+ years of practical experience with one of the reporting tools – Power BI (preferable)
• Proficiency in Data Analytics and Data Visualization concepts
• Skills in developing reports and dashboards
• Advanced SQL knowledge and background in relational databases such as MS SQL Server, Oracle, MySQL, and PostgreSQL
• Understanding of landing, staging area, data cleansing, data profiling, data security and data architecture concepts (DWH, Data Lake, Delta Lake/Lakehouse, Datamart)
• Familiarity with Cloud technologies (AWS, Azure, GCP, Snowflake)
• Expertise in data products testing
• Ability to work in an agile development environment (SCRUM, Kanban)
• Understanding of CI/CD principles and best practices
• English level – Upper-Intermediate and higher

We offer

• Work on a flexible schedule remotely or from any of our comfortable offices or coworking spaces in Ukraine
• Receive the necessary equipment to perform your work tasks
• Change projects and technology stacks within EPAM
• Gain experience in various business domains (Insurance, E-commerce, Healthcare, Finance, Travelling, Media, Artificial Intelligence, and more)
• Consider relocation options in over 30 countries worldwide
• Participate in volunteer, charity programs and communities (both technical and interest-based)
• You can plan your individual career path together with your manager
• Receive regular feedback from colleagues
• Improve your English for free with certified teachers (Speaking Clubs, client interview preparation courses, etc.)
• Get the opportunity to undergo free training and certification in AWS, GCP, or Azure Clouds
• Use the internal E-learn training program (18,200+ specialized training and mentoring programs)
• Access corporate accounts on LinkedIn Learning, Get Abstract and other partner resources
• Study at EPAM Solution Architecture School with the instructors who are practicing architects
• Develop as a leader, join Delivery Management, Resource Management, Leadership Essentials school and more
• Participate in internal communities (500+ meetups, technical discussions, brainstorming sessions, online events and conferences annually)
• Vacation and sick leave (including a sick leave without a medical certificate)
• A wide range of Voluntary Medical Insurance programs providing both medical treatment and various preventive options (including sports activities)
• Medical insurance for family members at corporate rates
• Company support during significant life events (childbirth or adoption, marriage, etc.)
• Support for psychological comfort: discounts on services from mental health specialists or coaches, thematic training
• E-kids program - a free programming language training program for EPAMers' children

EPAM strives to provide its global team of over 52,800+ professionals in more than 55 countries with opportunities for professional growth from day one of collaboration. Our colleagues are the source of EPAM's success, so we value cooperation, strive to always understand our clients' business and aim for the highest quality standards. No matter where you are, you will join a dedicated, diverse community that will help you realize your potential to the fullest.

We are seeking a skilled Big Data Engineer to become an essential part of this forward-looking and dynamic team.

In this role, you will leverage advanced cloud technologies to deliver impactful solutions.
 

If you excel at tackling complex challenges, creating robust cloud-based solutions, and driving meaningful business outcomes, this opportunity offers the chance to join a fast-paced, collaborative environment where your work shapes global success.

The remote option applies only to the Candidates who will be working from any location in Ukraine.

Responsibilities

• Build scalable, cloud-based systems in Azure using tools like Azure Data Factory, Azure Data Lake Storage, and Databricks to enhance seamless, high-performance data pipelines
• Migrate on-premises MS SQL databases to Azure Data Lake, utilizing the Delta Lake format to optimize operational performance
• Develop interfaces that connect non-Microsoft proprietary applications, enabling interoperability and unlocking valuable data insights
• Provide expertise in Data Lakes, Data Warehouses (DWH), and Delta Lakehouse architectures to guide transformative business solutions
• Assess new feature proposals, prioritize them based on business value, and collaborate to make impactful product development decisions
   

Requirements

• Expertise in Azure Data Services, including Data Factory, Data Lake Storage, and Databricks
• Strong SQL skills with experience in Python, Scala, or C# (versatility is highly valued)
• Background in working with Agile or XP methodologies, thriving in fast-moving, adaptive environments
• Good English communication skills (Upper-Intermediate/B2+ or higher) to engage effectively with diverse teams and stakeholders
   

Nice to have

• Proficiency in advanced Azure tools such as Synapse Analytics, Cosmos DB, or Apache Synapse
• Flexibility to use Core Python or Scala for automation and advanced data processing
   

We offer

• Work on a flexible schedule remotely or from any of our comfortable offices or coworking spaces in Ukraine
• Receive the necessary equipment to perform your work tasks
• Change projects and technology stacks within EPAM
• Gain experience in various business domains (Insurance, E-commerce, Healthcare, Finance, Travelling, Media, Artificial Intelligence, and more)
• Consider relocation options in over 30 countries worldwide
• Participate in volunteer, charity programs and communities (both technical and interest-based)
• You can plan your individual career path together with your manager
• Receive regular feedback from colleagues
• Improve your English for free with certified teachers (Speaking Clubs, client interview preparation courses, etc.)
• Get the opportunity to undergo free training and certification in AWS, GCP, or Azure Clouds
• Use the internal E-learn training program (18,200+ specialized training and mentoring programs)
• Access corporate accounts on LinkedIn Learning, Get Abstract and other partner resources
• Study at EPAM Solution Architecture School with the instructors who are practicing architects
• Develop as a leader, join Delivery Management, Resource Management, Leadership Essentials school and more
• Participate in internal communities (500+ meetups, technical discussions, brainstorming sessions, online events and conferences annually)
• Vacation and sick leave (including a sick leave without a medical certificate)
• A wide range of Voluntary Medical Insurance programs providing both medical treatment and various preventive options (including sports activities)
• Medical insurance for family members at corporate rates
• Company support during significant life events (childbirth or adoption, marriage, etc.)
• Support for psychological comfort: discounts on services from mental health specialists or coaches, thematic training
• E-kids program - a free programming language training program for EPAMers' children
   

EPAM strives to provide its global team of over 52,800+ professionals in more than 55 countries with opportunities for professional growth from day one of collaboration. Our colleagues are the source of EPAM's success, so we value cooperation, strive to always understand our clients' business and aim for the highest quality standards. No matter where you are, you will join a dedicated, diverse community that will help you realize your potential to the fullest.

We're building an AI system that reads content and automatically determines:
 

1. Whether it contains a paid endorsement (yes / no)
2. What type of endorsement it is, based on our classification spec
3. Which brand it refers to — matched against our existing brand database, with a suggested new brand name when there's no match
    

We already have a labeled set of examples across the different endorsement types that you can use for training and evaluation. 
 

What you'll do

• Build a classification pipeline that flags paid vs. non-paid endorsements and categorizes endorsement type per our specification
• Build brand matching (entity resolution) against our database using fuzzy and/or semantic matching, with a "suggest a new brand" fallback when nothing matches
• Use our labeled examples to train and/or tune the system, and set up an evaluation framework so we can measure and improve performance per task
• Process large volumes of entries efficiently and cost-effectively

• Document the approach and hand off a maintainable system

   

What you should have

• Strong experience building NLP / text-classification systems
• Hands-on work with modern LLMs (e.g., Claude, GPT) — prompt engineering, structured outputs, and/or fine-tuning
• Experience with entity resolution / record linkage — fuzzy or semantic matching, embeddings, vector search
• A rigorous, evaluation-driven approach — you measure performance properly rather than by feel
• Comfort with our stack: Python, SQL, working with APIs and a database

Workload — Full-time
Duration — A couple of months to start with, and it has some extension potential.
Location — EU

Working in a staff augmentation model for a US-based AI-native marketing intelligence platform (connected marketing platform).

The client expects a couple of hours of overlap until 11:30 EST (5:30 PM CET). 

Bachelor's degree in Computer Science or related field 5+ years of professional backend software development experience Strong Python development experience Experience building REST APIs using FastAPI, Flask, or similar frameworks Strong understanding of HTTP, REST, authentication, and API design Experience integrating with relational databases and cloud data platforms Experience building secure, scalable backend applications Familiarity with AWS cloud services Experience using Git and modern CI/CD workflows Strong debugging and problem-solving skills Excellent written and verbal communication skills Preferred Qualifications Experience building AI-enabled applications Experience developing platform services or internal developer platforms Familiarity with MCP (Model Context Protocol) or AI tool integration patterns Experience with Snowflake or Databricks Experience working with event-driven architectures Familiarity with Redis or distributed caching Experience integrating with third-party SaaS platforms Experience working in media, advertising, or marketing technology Familiarity with agentic AI development workflows

Primary

Python 

FastAPI 

REST APIs 

PostgreSQL 

Redis 

AWS 

Docker 

Git 

Nice to Have

Snowflake 

Databricks 

OpenAI APIs 

MCP 

LangGraph / LangChain 

Kubernetes 

Terraform

Our Customer:

Our customer is an international technology company developing a security-focused enterprise platform used by organizations with high requirements for device protection and user authentication. As part of its product ecosystem, the company is building a desktop application for macOS that integrates deeply with operating system capabilities to deliver secure authentication, device management, and identity-related functionality.

Your Tasks:

• Design, develop, and maintain low-level macOS application components that interact with system frameworks and operating system services.
• Build and enhance integrations with macOS security, authentication, and credential management capabilities.
• Ensure compatibility with new macOS releases by evaluating platform changes, API updates, and system behavior across OS versions.
• Research and implement modern Apple platform capabilities related to identity, authentication, and device security.
• Develop reliable background services, inter-process communication mechanisms, and secure application workflows.
• Improve software quality through secure build and release processes, diagnostics, logging, and issue investigation.
• Troubleshoot complex platform-specific issues and collaborate with cross-functional teams to deliver robust solutions.
• Contribute to technical design discussions and continuously improve the architecture of macOS platform components.

Required Experience and Skills:

• 8+ years of commercial software development experience.
• At least 4 years of hands-on experience developing applications for macOS with a strong focus on system-level functionality.
• Strong proficiency with Swift and/or Objective-C.
• Along with practical experience using C/C++.
• Solid experience working with macOS system frameworks, background services, inter-process communication, security mechanisms,
• and application permissions.
• Good understanding of Unix/Linux operating system concepts, including processes, permissions, IPC, and system services.
• Experience building security-sensitive software, including secure data storage, authentication flows, and cryptographic principles.
• Strong debugging and troubleshooting skills, particularly for platform-level issues and complex system interactions.
• Ability to independently drive technical investigations and deliver solutions for complex engineering challenges.
• Bachelor’s degree in Computer Science, Engineering, Mathematics, or a related technical field.
• English level Upper-Intermediate or higher.

Would Be a Plus:

• Experience with identity and access management technologies or enterprise authentication solutions.
• Familiarity with modern authentication standards and security protocols.
• Experience integrating applications with enterprise device management solutions.
• Knowledge of macOS endpoint security technologies or other advanced Apple platform capabilities.
• Previous experience working on enterprise desktop software deployed at scale.
• Exposure to low-level operating system development or performance optimization.

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 
• 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) 
• 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

About the role:

The role will involve designing, developing, maintaining, and improving the company's data warehouse, data pipelines, and analytical data models. You will work with high-volume event data from multiple internal and external sources - supporting a growing analytical layer used for operational monitoring and business analytics.

This is not only a maintenance role. We are looking for someone who can take ownership of data solutions end to end, improve data reliability, optimize data flows, support scalable data modeling, and proactively introduce better practices in data engineering, data quality, and data warehousing.

Requirements:
 

• 4+ years of experience as a Data Engineer, Analytics Engineer, BI Engineer, or similar role.
• Advanced SQL skills and strong experience working with large datasets.
• Strong experience with BigQuery or similar cloud data warehouses; experience with Google Cloud 
• Experience designing, building, and maintaining scalable ETL / ELT pipelines.
• Experience with dbt or a similar data transformation framework.
• Experience with orchestration tools such as Apache Airflow, Prefect, Dagster, or similar.
• Experience building data quality checks, validation rules, monitoring, and troubleshooting processes.
• Experience optimizing data processing, query performance, and warehouse costs.
• Ability to identify root causes of data issues and propose practical, scalable improvements.
• Ability to create and maintain documentation for data flows, models, dependencies, and known limitations.
• Strong end-to-end ownership of data solutions.
• Ability to translate analytical and business needs into reliable technical data solutions.
• Detail-oriented mindset and high standards for data reliability.
• English level B1-B2 or higher.

Nice to have

• Experience integrating and maintaining data from third-party platforms such as marketing systems, CRM tools, tracking platforms, or attribution systems.
• Familiarity with BI/reporting environments such as Looker Studio/Tableau/Power BI or similar.
• Experience designing or maintaining pipelines for high-volume event-level data, logs, or time-series datasets.
• Experience with Git and version control for data pipelines, SQL models, or data projects.
• Experience with Python

Responsibilities:

• Design, develop, maintain, and improve scalable data warehouse solutions and ETL / ELT pipelines.
• Work with high-volume data from APIs, third-party platforms, event data, manual imports, and internal sources.
• Ensure key analytical datasets are updated correctly, on time, and with clear ownership.
• Improve pipeline reliability, monitoring, error handling, query performance, and warehouse costs.
• Build and maintain data quality checks, validation rules, and monitoring processes.
• Detect and investigate missing, duplicated, delayed, inconsistent, or incorrect data.
• Identify root causes of data issues and implement controls to prevent recurring problems.
• Ensure data is reliable, consistent, complete, and ready for reporting and analytics.
• Define and apply standards for table structure, naming conventions, joins, keys, metric logic, and documentation.
• Support clear data layers: raw, staging, analytical, and business-ready datasets.
• Standardize similar datasets and reduce duplicated or inconsistent transformation logic.
• Work closely with Business Analytics to understand analytical needs and data blockers.
• Translate analytical and business requirements into technical data structures and pipeline improvements.
• Support BI and reporting needs by ensuring datasets are reliable, consistent, and well-documented.
• Share best practices, provide technical guidance, and proactively introduce improvements in data engineering and warehousing.

What it means to be part of our Team:
 

• Multinational and intercultural experience
• Corporate library
• A world-class team to work with
• Growth opportunities
• Cutting-edge frameworks and technologies
• Competitive salary
• Plenty of engaging team-building and social events
• Bonuses according to the policy
• 21 paid vacation days & 14 paid sick leaves;
• Cozy office in Warsaw, Kyiv available for you whenever you need it
• Coffee, tea, Red Bull, sweets, fruits, and more snacks

💌 Interested?

We’re always on the lookout for passionate, driven, and curious people to join our team.If that sounds like you — we’d love to hear from you!

Start: ASAP
Long-term project
Candidate location: EU !!!
Location: Berlin (Hybrid) or fully remote
Department: Technology / Digital Transformation

You'll own the infrastructure, automation, and delivery pipelines that power our internal platforms and integrations — working across cloud (Azure/GCP), containerized workloads, and enterprise systems (SAP, NestJS-based services, and internal tooling). This is a senior, hands-on role with real architectural ownership: you'll shape how we build, secure, and scale our platform, not just maintain what already exists.

What You'll Do
• Own CI/CD and delivery pipelines end-to-end — design, harden, and continuously improve pipelines with built-in security gates (SAST/DAST, dependency and container scanning, IaC compliance checks) rather than bolting security on after the fact.
• Build and evolve infrastructure as code (Terraform, and/or Pulumi) across cloud environments, treating Git as the single source of truth (GitOps) with full auditability and rollback.
• Design and operate Kubernetes-based container platforms — clusters, Helm charts, and where relevant, service mesh (Istio/Linkerd) for multi-service, multi-cluster environments.
• Drive platform engineering initiatives — build internal developer platforms / self-service tooling that reduce cognitive load for application teams (standardized environments, templated deployments, golden paths).
• Own the technical pipeline for the Secure Software Development Lifecycle (SSDLC), including security gates at each stage of build and release.
• Drive vulnerability mitigation — triage findings from scanning tools and coordinate timely remediation across teams.
• Own patch management — track, prioritize, and apply patches across infrastructure and dependencies on a defined cadence.
• Bring AI into operations (AIOps) — apply anomaly detection, intelligent alerting, and automation to reduce noise and enable self-healing pipelines and infrastructure; use AI-assisted engineering tools (e.g., Cursor, Claude Code) daily as a core part of how you build and ship.
• Own observability — instrument systems for metrics, logs, and traces; build dashboards and alerting that reflect real business and system risk, not just infrastructure noise.
• Take responsibility for cost (FinOps) — monitor cloud spend, rightsize resources, and build budget guardrails across environments.
• Support MLOps/AI infrastructure needs as our AI tooling and agentic workflows scale — model/version registries, secure API access patterns (e.g., workload identity federation), and sandboxing for autonomous agents.
• Act as a technical bridge between development, security, operations, and business stakeholders — explain trade-offs clearly, coordinate incidents calmly, and contribute to architecture discussions, not just implementation.

What You Bring
Core technical foundation!!!
• 5+ years in DevOps/SRE/Platform Engineering roles, with at least 2 years operating at a senior/lead level (system design, mentoring, on-call ownership). Strong hands-on DevSecOps experience, including SAST, DAST, SCA, container image scanning, secrets management, vulnerability remediation, security policy enforcement, and Secure Software Development Lifecycle (SSDLC).
• Deep hands-on experience with at least one major cloud provider (Azure or GCP strongly preferred given our stack; AWS a plus), including IAM, networking, and workload identity patterns. Strong understanding of networking fundamentals, including TCP/IP, HTTP/HTTPS, TLS, UDP, DNS, load balancing, ingress, and cloud networking architectures.
• Strong command of containerization and orchestration: Docker, Kubernetes in production, Helm.Strong Linux administration skills, including file permissions, ownership, process management, networking tools, shell scripting, and troubleshooting production systems.
• Proven experience with Infrastructure as Code (Terraform preferred) and GitOps workflows (ArgoCD, Flux, or equivalent).
• Solid scripting/automation skills (Python, Bash, or Go) and comfort reading/writing CI/CD pipeline configs (GitHub Actions, GitLab CI, Jenkins, or Azure DevOps).
• Required: daily hands-on experience with AI-assisted coding tools (Cursor, Claude Code, GitHub Copilot, or similar) as part of your development and infrastructure workflow — this is a must-have, not a nice-to-have. Experience with modern AI platforms or services such as Amazon Bedrock, Azure AI Foundry, Vertex AI, OpenSRE, HolmesGPT, LangChain, MCP, or similar is highly desirable.
Security & compliance
• Practical DevSecOps experience: vulnerability scanning (Snyk, OWASP Dependency-Check or similar), secrets management, and policy-as-code/compliance tooling.
• Understanding of zero-trust network design and enterprise IAM governance (relevant to regulated, multi-entity organizations).
Emerging / 2026-relevant skills
• Familiarity with AIOps concepts and tools — using AI/ML signals for incident detection, capacity planning, or pipeline self-healing.
• Working knowledge of platform engineering principles and building internal developer platforms (IDPs).
• Exposure to MLOps or AI infrastructure (GPU scheduling, model registries, agent sandboxing/network isolation) is a strong plus given our growing AI governance and agentic tooling initiatives.
• Comfort operating in a FinOps mindset — cost visibility and optimization as a shared responsibility, not a separate team's job.
Soft skills (non-negotiable at senior level)
• Strong written and verbal communication — able to explain technical trade-offs to both engineers and non-technical stakeholders.
• Calm, structured incident coordination under pressure.
• A systems-thinking mindset: understanding failure modes and designing for resilience rather than reacting to outages.
• Collaborative, low-ego approach to working across dev, security, QA, and business teams.

Nice to have
• Experience in real estate, financial services, or another regulated, multi-entity enterprise environment.
• Familiarity with SAP-adjacent integration landscapes or large-scale enterprise system migrations.
• Cloud certifications (Azure DevOps Engineer Expert, Google Professional Cloud DevOps Engineer, or equivalent).

 

We are looking for a Senior Data Engineer to design and build scalable data platforms that process large volumes of data for analytics, reporting, and business-critical applications.

You will work with distributed data processing systems, cloud infrastructure, streaming platforms, and modern data pipelines. We are looking for an engineer who can independently own production solutions and solve complex performance and architecture challenges.

Mandatory Skills

Programming & Data Processing

• Strong Python development skills
• Advanced SQL (complex queries, optimization, execution plans)
• Strong commercial experience with Apache Spark / PySpark
• Experience optimizing Spark jobs (partitioning, shuffle, joins, skew handling)

Data Engineering

• Experience building production-grade ETL / ELT pipelines
• Strong experience with Apache Airflow
• Strong hands-on experience with Apache Kafka
• Understanding of batch and streaming data processing architectures

Infrastructure & Storage

• Experience with relational databases (PostgreSQL, MySQL or similar)
• Data modeling and query optimization
• Hands-on experience with at least one cloud platform (AWS, Azure or GCP)
• Experience working with Docker, Linux, Git, and basic CI/CD pipelines

Desired Skills

• Databricks, Snowflake or similar cloud data platforms
• Kubernetes
• CDC pipelines (Debezium or similar)
• Modern analytical/storage systems (ClickHouse, Trino, Iceberg, Delta Lake)
• Monitoring tools (Grafana, Prometheus)

Responsibilities

• Build scalable batch and streaming data pipelines
• Develop and optimize Spark/PySpark data processing jobs
• Build Kafka-based ingestion and event-driven pipelines
• Design and maintain Airflow orchestration workflows
• Optimize SQL queries and improve pipeline performance
• Investigate production issues and improve system reliability
• Participate in architecture and technical design discussions

Senior-Level Expectations

• Independently design scalable data pipelines
• Debug and optimize distributed production systems
• Solve performance bottlenecks in Spark and SQL workloads
• Make technical decisions with minimal supervision
• Take ownership of production solutions end-to-end

Soft Skills

• Strong problem-solving skills
• Ownership and accountability
• Ability to work independently
• Good communication and collaboration skills
• Proactive engineering mindset

The CHI Software team is not standing still. We love our job and give it one hundred percent of us! Every new project is a challenge that we face successfully. The only thing that can stop us is… Wait, it’s nothing! The number of projects is growing, and with them, our team too. And now we need a Middle/Senior Data Engineer.
 

Requirements:

• 4+ years of experience as a Data Engineer;
• Completed Data Engineering Professional certification;
• Minimum 2 projects delivered with hands-on experience in development on Databricks;
• Experience in Apache Spark Programming with Databricks;
• Experience with Azure cloud;
• Upper-Intermediate English level.

We are looking for a Senior Data Engineer Consultant to join an AI consulting engagement focused on LLM architecture, RAG, data strategy, and AI platform advisory.
 

This is an advisory role rather than a full-time implementation position. The consultant will work with AI architects, ML engineers, MLOps specialists, and the client’s engineering team to assess the current data landscape, review proposed solutions, and provide practical technical recommendations.
 

Responsibilities
 

Data Strategy
 

• Review the existing enterprise data landscape and available data sources.
   
• Assess data readiness for foundation model training, fine-tuning, evaluation, and RAG.
   
• Recommend data acquisition, prioritization, and preparation approaches.
   
• Advise on multilingual data preparation strategies.
   

Data Pipelines
 

• Review the current ETL/ELT architecture and data processing workflows.
   
• Recommend pipeline designs for model training, inference, and evaluation.
   
• Evaluate orchestration, dataset versioning, and data traceability approaches.
   
• Assess pipeline scalability, reliability, maintainability, and performance.
   

RAG Data Engineering
 

• Review document ingestion architecture for enterprise knowledge bases.
   
• Recommend parsing, chunking, metadata enrichment, embedding, and indexing approaches.
   
• Evaluate vector database and search integration strategies.
   
• Advise on incremental updates, synchronization, access-aware retrieval, and retrieval optimization.
   

Data Governance and Quality
 

• Review data lifecycle management and data governance practices.
   
• Assess PII handling, data masking, retention policies, access control, lineage, and auditability.
   
• Recommend data validation and quality-control frameworks.
   
• Review training and evaluation datasets.
   
• Advise on monitoring data freshness, consistency, completeness, and data drift.
   

Documentation and Consulting
 

• Prepare technical recommendations, architecture assessments, and implementation guidelines.
   
• Review technical documentation, diagrams, and proposed designs.
   
• Participate in architecture reviews, design discussions, and technical workshops.
   
• Conduct knowledge-transfer sessions with the client’s engineering team.
   

Technology Stack
 

Python, SQL, Apache Airflow, Apache Kafka, Hadoop, Apache Superset, n8n, ETL/ELT, RAG Pipelines, Vector Databases, Data Governance, Cloud (AWS, Azure or GCP).
 

Preferred Domain Experience
 

Experience in banking, fintech, financial services, or another highly regulated domain is highly desirable.
 

The ideal candidate should understand domain-specific requirements related to:
 

• sensitive and confidential data;
   
• PII protection and data masking;
   
• role-based access control;
   
• data retention and auditability;
   
• regulatory and compliance requirements;
   
• secure use of enterprise data in AI and LLM solutions.
   

Engagement Details
 

• Engagement model: Part-time consulting.
   
• Workload: Flexible and non-uniform, depending on the current project phase.
   
• Expected activities: Architecture reviews, workshops, document reviews, technical assessments, and advisory sessions.
   
• Duration: Approximately 6 months.
   
• Project type: AI/LLM consulting engagement.
   
• Client interaction: Direct collaboration with the client’s engineering and architecture teams.
   
• Availability: The consultant should be able to join scheduled sessions and provide asynchronous reviews between meetings.
   

EverHelp is a team of professionals, that’s developing outsourcing support services for plenty of products all over the world at a dynamic tempo. The project launched in 2021, and last year we experienced a yearly growth rate of +82%. Since February 2022, we've managed to preserve all our workplaces and, most importantly, we continue to strengthen our team while maintaining an employee satisfaction rate of over 90%.

In 2026, EverHelp received 9 international workplace and employer awards. The company ranked #1 in the Top 30 Inspiring Workplaces in Europe, was named the #1 employer among European companies with 500–4,999 employees, and earned Best-in-Class recognition across 6 categories: Culture & Purpose, Leadership, Inclusion & Belonging, Wellbeing, Employee Voice, and Employee Experience. EverHelp was also named one of the 28 Best Places to Work by Business Intelligence Group — a global award recognizing companies with strong workplace cultures and outstanding employee experience.

Our statement:

• We’re against war and unjustified aggression,
• We evacuated all the teammates and their families from the frontline, helped them find a new place to live and provided financial support,
• We provided the team with charging stations,
• We continue to work together for the future of Ukraine.

Your future responsibilities include:

• Building, optimizing, and maintaining ETL pipelines that extract data from ERP
  systems, databases, and APIs, transform it into a usable format, and load it into
  BigQuery
• Automating data ingestion, transformation, and loading processes to reduce manual
  intervention and ensure efficiency
• Monitoring and troubleshooting data pipelines proactively — catching performance issues
  issues, errors, and data quality problems before they escalate
• Managing and optimizing data storage: partitioning, indexing, and performance tuning
  in BigQuery
• Designing data models that represent the structure and relationships within a business
  data
• Implementing data quality checks and validation rules at every stage of the pipeline
• Identifying and resolving data inconsistencies, errors, and missing values
• Conducting data audits and comparing results with business user needs — proposing
  solutions to close existing gaps
• Collaborating with analysts, data scientists, and business stakeholders to understand
  their data needs and translate them into scalable solutions

Why this role might be interesting for you:

If you love structure and enjoy optimizing processes, this is your playground. You'll make real-world architectural decisions, not just execute tickets. Every pipeline you build or improve directly powers business decisions at the highest level, so the impact of your work is visible and immediate. And if you want to be the person who shapes a data-driven culture from the inside — that's exactly the role we're offering.

Needed experience & skills:

• 2-4+ years of hands-on experience as a Data Engineer
• Advanced knowledge of SQL and Python
• Hands-on experience with GCP, in particular BigQuery
• Strong ETL and data warehousing skills: Apache Airflow, dbt
• Clear understanding of both the technical and business sides of data products
• Clear and concise communication; comfortable working cross-functionally with nontechnical stakeholders
• Proactive problem-solving mindset — analytical thinking and attention to detail
• English level — B1-В2

Nice to have skills:

• Experience at a large systematic company (retail, banking, telecom, FMCG, logistics)
• Comfort working autonomously as the only Data Engineer on a team
• Adaptability in a high-paced, fast-changing environment

Hiring Process:

CV Screening → Questionnaire → Intro Call → Tech & Soft Interview → Bar Raising

Work with EverHelp is about:

• Opportunity to join the Ukrainian company and help the Ukrainian economy,
• 20+ vacation days and unlimited sick leaves, corporate doctor & psychologist,
• Medical insurance and +10 Healthcare leaves for mental & physical recovery,
• Systematical learning & development inside a team and on an individual level: compensation for professional webinars, courses, conferences, etc.,
• Ability to work from Lviv & Kyiv offices with free breakfasts and lunches or fully remotely,
• Team of professionals who’s ready for knowledge sharing, internal professional communities, team buildings,
• Corporate discounts for gym membership and for other different services like medical services, language schools, etc.

Submit your resume and join our team!

Tieto Tech Consulting, is looking for a highly skilled and motivated Junior Telco Engineer, a professional who will join a project within a Telecom Team for our respectful client BICS.

Join the team of our customer BICS – a global telecommunication enabler with a physical network stretching through the globe! Grow your expertise through interacting with A-level mobile carriers from all over the world. Get your hands on the vast network with on land, underwater, and space points of presence.Join our decade-long partnership with BICS to ensure confidence in your future and long-term growth! Tieto-BICS team has been growing since 2010… and we are looking forward to grow with you!

• Develop your telecom expertise in diverse portfolio of BICS products, including Voice, Cloud, Signaling, LTE, IoT, etc.
• Enjoy unmatched growth opportunities with BICS vast network and customers around the world.

Tieto - BICS team has been growing since 2010… and we are looking forward to growing with you!

Responsibilities

• Ensure accurate documentation of the Fixed Services product portfolio (e.g. Voice, VoIP, Signaling, Capacity) in inventory tools, based on project low-level design.
• Maintain both service and network data by creating and updating low-level configurations in dedicated inventory systems, in line with internal routing guidelines.
• Collaborate with Regional Technical Managers (RTMs) and support both high-level and low-level design activities for projects (e.g. TDM/VoIP implementations).
• Ensure data quality and consistency, and support continuous improvement and cleanup of documentation.

Qualifications

• Experience in a mobile or fixed telecom operator is an asset.
• Understanding of telecom networks and topology, including core network elements and their functions.
• Knowledge of service fulfillment and telecom operational processes is an advantage.
• Familiarity with protocols and services such as voice switching and routing (TDM, VoIP), transmission (SDH/IP), and basic SS7 signaling.
• Interest in working with configuration data across different systems and tools.
• Strong analytical skills, attention to quality, and results-oriented mindset.
• Good command of spoken and written English.

About the role:

As a Senior Data Engineer, become a part of a cross-functional development team engineering experiences of tomorrow.

Design, build, and optimize enterprise data pipelines and lakehouse solutions aligned to client’s data architecture, governance standards, and cloud-first strategy. Partner with cross-functional teams to deliver secure, scalable, and high-quality data solutions that enable analytics, reporting, and AI-driven capabilities.

Responsibilities:

• Design, develop, and maintain scalable ETL/ELT pipelines across enterprise systems including ERP, CRM, and operational platforms 
• Build and support client’s cloud-based data lakehouse architecture (aligned to medallion layers and governance standards) 
• Develop and maintain data models, semantic layers, and curated datasets for analytics and business intelligence 
• Translate business requirements into technical data solutions in collaboration with product, engineering, and business stakeholders 
• Ensure data quality, integrity, and security in alignment with client;s data governance and compliance standards 
• Optimize SQL queries, data pipelines, and storage performance across AWS and Azure platforms 
• Support data integration initiatives including Data Lake, D365 ERP, and CRM/AMS platforms 
• Monitor pipeline health, troubleshoot issues, and ensure high availability and reliability of data systems 
• Contribute to continuous improvement of data architecture, standards, and best practices 

• Support AI and analytics initiatives by enabling high-quality, accessible data for downstream consumption 

   

Technical Requirements (Must Have):

• Bachelor’s degree in Computer Science, Information Systems, or related field 
• 4+ years of experience in data engineering or data platform development 
• Strong experience designing and building ETL/ELT pipelines in cloud environments 
• Hands-on experience with AWS (S3, Redshift, Glue, DMS) and Azure (Data Factory, SSIS) 
• Strong proficiency in SQL and relational database design 
• Solid understanding of data warehousing, data lakes, and lakehouse architecture 

• Experience with structured, semi-structured, and unstructured data processing 

   

Non-Technical Requirements (Nice to Have):

• Ability to establish positive working relationships with multiple disciplines of Information technology department & staff levels
• Demonstrated ability to collaborate and receive feedback regarding ongoing projects
• Demonstrated ability to respond to business issues with the appropriate sense of urgency
• Sense of when to escalate a problem or ask for assistance
• Organized, self-starter with outstanding written and verbal communication skills
• Problem solving skills and strong attention to details
• Ability to identify and document business/system requirements
• Ability to work in a high energy, team focused environment
• Ability to work and deliver against aggressive timelines to meet the project schedules

• Ability to work productively from home (including access to a reliable internet connection) is required

   

Location and Hiring Model

• Locations ONLY: Bulgaria
• Hiring Model: Direct Hire ONLY (B2B)