Jobs Data Engineer

1. CORE ВІДПОВІДАЛЬНІСТЬ (ГОЛОВНЕ)
1.1. Надійна передача всіх лідів у CRM
 

• 100% реєстрацій → CRM
• Побудова системи data validation
• Daily/weekly репорт:
  • % доставлених лідів
  • список недоставлених
  • причина (API error / mapping / timeout / etc.)
• Автоматичні алерти при просадці

1.2. Контроль і побудова CRM-флоу (pipeline automation)
 

• підтримка pipeline:
  • Signup → Appointment Setter
  • Meeting/Setup → Sales
  • Closed/Won → Customer Success
• Автоматичі тригери переходів між стадіями
• Fail-safe логіка:
  • якщо лід “завис” — алерт
  • якщо не відпрацював trigger — лог + репорт

 проблема наразі відсутність контролю флоу
2. ІНТЕГРАЦІЇ І DATA UNIFICATION
2.1. Єдиний профайл клієнта (Single Customer View)
Інтеграція:
 

• OpenPhone (дзвінки, логи)
• Zoho Desk (тікети)
• meeting tools (AI summaries / transcripts)

Результат:
 

• В CRM профайлі:
  • дзвінки
  • email
  • SMS
  • тікети
  • summary розмов

2.2. Двосторонні інтеграції з CRM клієнтів для дашборда
 

• Інтеграція через:
  • API
  • Zapier
• Передача:
  • ліди → клієнту
  • статуси ← назад у вашу систему
• Контроль статусів:
  • contacted / not contacted
  • deal stage

2.3. Робота з клієнтами (integration support)
 

• Написання документації
• Loom / відео-інструкції
• Hands-on інтеграція (за доступом)
• Комунікація з клієнтом технічною мовою

3. AUTOMATION (EMAIL / SMS / EVENTS) для Маркетингу 
3.1. Тригери і комунікації
 

• Налаштування:
  • email
  • SMS
  • event-based automation
• Тригери:
  • signup
  • booked meeting
  • inactivity
  • onboarding stage

3.2. Аналітика комунікацій
 

• Dashboard:
  • sent
  • delivered
  • failed
  • open rate
• Причини недоставки
• A/B тести (опціонально, але бажано)

4. ZOHO MASTER РІВЕНЬ (НЕ 3%)
Робота з:
 

• Zoho CRM
• Zoho ecosystem (Campaigns, Flow, Analytics, Desk)

Обов’язки:
 

• Виявлення нових можливостей Zoho
• Пропозиції по автоматизації департаментів
• Реалізація:
  • workflows
  • functions (Deluge)
  • кастомна логіка

Тут потрібен не юзер, а архітектор системи
5. AI & AUTOMATION LAYER
5.1. Використання AI в роботі
 

• Генерація:
  • summaries
  • email templates
• Автоматизація рутинних задач

5.2. Побудова внутрішніх AI-рішень
 

• Аналіз саппорт-тасків
• Автоматизація повторюваних процесів
• Інтеграція AI в:
  • support
  • sales
  • ops

6. MONITORING & ALERTING (ДУЖЕ ВАЖЛИВО)
 

• Система алертів:
  • зламалась інтеграція
  • впав delivery rate
  • зависли ліди
• Логи + прозорість
• Регулярні репорти

7. TECH STACK 
Обов’язково:
 

• Zoho CRM (advanced)
• API integrations
• Webhooks
• Zapier / Make
• Data mapping
• Basic scripting

Плюс:
 

• AI tools
• CRM architecture
• Experience з SaaS продуктами

8. EXPECTED OUTPUT 
Якщо коротко, ця позиція має:
 

• гарантувати 0% втрати лідів
• зробити прозору систему контролю
• об’єднати всі дані про клієнта в одному місці
• автоматизувати рутину
• підняти використання Zoho з 3% → 50%+

У нас немає наразі data ownership, monitoring, немає системного підходу до інтеграцій
Тому шукаємо не “спеціаліста”, а людину, яка:
Будує системи та їх контроль, відповідає за результат,

Project Description:
Our client is building data- and AI-driven solutions in a cloud-first environment, with a strong focus on GCP, BigQuery, and large-scale data workflows. The current work is centered around exploring and defining new solution directions, especially in voice-related use cases, where architecture decisions must balance feasibility, scalability, and production readiness.
The environment is highly collaborative and cross-functional, bringing together technical leadership, data scientists, and engineering teams to shape complex solutions from early discovery through implementation.

We are hiring a Lead Data Engineer to help define and shape solution architecture for new data- and AI-driven initiatives.
This is an architecture-focused role working on GCP-based systems, big data modeling, and agentic / LLM-oriented solution design, with a strong emphasis on turning ambiguous requirements into clear technical options.
You will work on early-stage solution design, feasibility analysis, production architecture planning, and proof-of-concept preparation. The role is especially relevant for candidates with experience in voice data, call-agent systems, or similar real-time / unstructured data environments.

Responsibilities:

• Evaluate technical feasibility of proposed voice-agentic systems
• Design production-grade solution approaches on GCP, especially around BigQuery
• Work with large, unstructured datasets and define storage / transformation strategies
• Support solution design involving LLMs and agentic workflows
• Prepare architecture documentation and technical recommendations
• Help shape proof-of-concept direction and technical scope
• Collaborate closely with technical leadership, data scientists, and engineering teams
  
  
  Required skills:
  Tech Stack:
• Python
• GCP
• BigQuery
• SQL / data modeling
• Large-scale data systems
• LLM / agentic solution design
• Streaming systems (nice to have)
• Voice / call-agent environments (strong plus)

What We’re Looking For

• Strong experience with GCP and cloud-native architecture;
• Strong Python background;
• Deep understanding of big data, data modeling, and analytical storage systems;
• Experience designing scalable, production-oriented architectures;
• Ability to operate in ambiguous environments and translate ideas into solution options;
• Strong communication and documentation skills;
• Ability to explain trade-offs clearly and collaborate across technical streams.

Interview process:

• EnglishCheck
• Internal Tech Interview
• Interview with the client

Nice to Have:

• Experience with LLM / agentic system design
• Experience with voice, speech, or call-agent platforms
• Experience with streaming architectures
• Experience working closely with data scientists on early-stage solution design

We are seeking an experienced CMDB Discovery Software Engineer to join our consulting team for a high-visibility initiative with a major enterprise banking client.

Following a strategic migration from ServiceNow to Jira, the client is now optimizing their configuration management landscape. You will be the technical lead focused on automating and enriching Jira Assets using Lansweeper SaaS and other enterprise data sources.

The Role

This is a remote-first consulting assignment requiring occasional quarterly travel to Riga, Tallinn, or Vilnius. You will join a lean, expert team of 4–5 specialists to build a reliable, high-integrity "Golden Record" for the client’s enterprise assets.

Core Objectives:

• Lansweeper Optimization: Mature the configuration of Lansweeper SaaS to improve discovery coverage and data quality.
• Jira Assets Mastery: Design and manage object schemas, attributes, and complex import configurations within Jira Assets (formerly Insight).
• Data Reconciliation: Build logic to merge data from Active Directory, Intune, and cloud inventories, resolving conflicts and deduplicating records.

Must-Haves

CMDB & Data Modeling (4+ Years)

• Deep expertise in enterprise CMDB environments and configuration management.
• Strong grip on CI classes, relationship mapping, lifecycle models, and ownership structures.

Jira Assets Expertise (3+ Years)

• Hands-on experience with Jira Assets (Insight): object schemas, types, and automated import configurations.

Discovery & Lansweeper (3+ Years)

• Advanced proficiency with Lansweeper SaaS.
• Proven ability to configure network scanning, credentials, and scan targets.
• Skill in reducing "false positives" and improving hardware/software inventory consistency.

Integration & Reconciliation (3+ Years)

• Experience reconciling multiple sources (e.g., AD/Azure AD, Intune, MECM, Virtualization/Cloud inventories).
• Practical knowledge of matching rules, unique keys, and "Golden Record" design.

The Bonus List

• Industry: Experience in Enterprise Banking or highly regulated sectors.
• Project History: Background in CMDB migrations (specifically ServiceNow to Jira) or post-migration stabilization.
• Automation: Experience automating CMDB enrichment or security platform integrations (e.g., QRadar).
• Consulting Mindset: Ability to balance "in-the-weeds" execution with high-level pragmatic solution design.

The company is a healthcare data analytics provider offering modern data infrastructure, reporting, and AI‑driven insights. Their technology focuses on improving how healthcare organizations manage, analyze, and use clinical data.

Core Solutions

•  Healthcare data platform: Consolidates structured and unstructured patient data in near real time to create a unified data foundation.

•  Longitudinal clinical data ecosystem: Enables comprehensive management and analysis of patient information.

•  Patient engagement platform: Integrates data from multiple sources to support secure communication and holistic patient care.

•  Population health management suite: Aggregates clinical and claims data, identifies at‑risk groups, and supports interventions to improve outcomes and reduce costs.

•  Care coordination and analytics tools: Provide a complete view of patient data to enhance quality, reduce costs, and support risk stratification.

•  AI and analytics services: Transform healthcare data into actionable insights for better care and operational efficiency.

Tech stack includes:

• SQL

• Python

• Data Warehousing

• ETL

• Snowflake and/or BigQuery

• AWS (Glue, Athena, Redshift is a plus)

• GCP

• Git

Conditions:

• Compensation: 5500–6500 USD/month

• Contract: B2B

• Remote‑friendly

PwC is a global network of more than 370,000 professionals in 149 countries that turns challenges into opportunities. We create innovative solutions in audit, consulting, tax and technology, combining knowledge from all over the world.

PwC SDC Lviv, opened in 2018, is part of this global space. It is a place where technology is combined with team spirit, and ambitious ideas find their embodiment in real projects for Central and Eastern Europe.

What do we guarantee?

• Work format: Remote or in a comfortable office in Lviv - you choose.
• Development: Personal development plan, mentoring, English and Polish language courses.
• Stability: Official employment from day one, annual review of salary and career prospects.
• Corporate culture: Events that unite the team and a space where everyone can be themselves.

As a global leader in IT services, PwC is supported by PwC Poland’s Data, Digital Solutions & AI team. We provide first-class services in all areas of Data Platforms, Data Analytics, Data Strategy and Data Management, just to name a few of our core capabilities. We support clients in the transition to and their adoption of modern data infrastructure, creation of new business models and streamlining their operational activities. 

Your future role:

• Building data platforms with critical components including data lakehouses, data warehouses and data lakes using tools like MS Fabric, Azure Databricks and Azure Data Factory for extraction, loading and transformation;
• Defining the flow of data through data platform from raw ingestion to business-ready consumption using most suitable data architecture patterns (e.g. medallion, lambda);
  Designing the migration plans for moving transactional and master data from legacy systems of record to systems of reference (new solutions);
• Conducting comprehensive data assessments alongside Data Modelers and Analysts across multiple systems of record and data domains to identify and remediate data quality issues;
• Liaising with client senior stakeholders and supporting Senior Data Architects to gather functional requirements to design modern data architecture;
• Supporting  Data Governance subject matter experts to define data standards and policies and specifically around Master Data Management and Data Quality;
• Some familiarizations with Data Science and Data Analytics use cases within the context of Consumer Goods, Retail, Manufacturing and/or Financial Service sectors will stand out.

Apply if you have:

• Minimum of 3 years in data engineering roles, although this can be considered alongside other relevant experience e.g., Business Intelligence, Data Science etc.;
• Hands‑on experience with data transformation platforms, with a strong preference for Azure‑based solutions such as Microsoft Fabric and Databricks; experience with other platforms (e.g. Snowflake, Azure Synapse, Google BigQuery) is also valued;
• Experience in building data warehouses, data lakes and data lakehouses using tools like Azure Data Factory and Azure Synapse Analytics;
• Familiarity with writing data transformation scripts using Python i.e. PySpark and SQL to query databases;
• Some experience in Data Engineering CI/CD practices and release management across Dev, QA and Production environments using tools like Azure DevOps, and/or Jira;
• Proficiency in Business English at B2 level or above, with confidence to write technical documentation e.g., designing documents with support from Project Manager;

• Experience with new technologies and AI‑based tools demonstrated in your daily work (e.g., task automation, information analysis, content creation).

   

Nice to have:

• Cloud certifications in Azure, AWS, or Google Cloud;
• Data Governance certifications e.g., DAMA;
• Evidence of training using online platforms e.g. Coursera, Udemy, Datacamp etc.;
• Application of data modelling frameworks including Kimball dimensional modelling to design and build logical and physical data models;
• Interest and some experience of experimenting with the application of Agentic AI to automate the extraction, transformation and loading of data using services like Azure Foundry;
• Proven experience in conducting data assessments across multiple data domains, including Product, and Customer and systems of record e.g. ERPs and CRMs;
• Experience of working on Data Strategy and Governance projects with a focus on improving Data Quality across key business functions;
• Familiarity with agile project management methodologies like Scrum to enable and scale minimal viable products;
• Some exposure to Data Science and Data Analytics use cases, particularly in the applications of Machine Learning and Generative AI techniques to help improve business forecasting, and demand planning;
• Experience in supporting senior stakeholders including Chief Data Officers in medium to large sized businesses across sectors such as Manufacturing, Consumer Goods, and/or Financial Services.
  
  Policy statements:
  https://www.pwc.com/ua/uk/about/privacy.html

We are looking for an experienced Infrastructure & Virtualization Engineer to manage, design, and improve server, storage, virtualization, and cloud infrastructure. This role is ideal for a hands-on infrastructure professional with a strong builder mindset - someone who has designed and implemented systems, not only supported them.

Key Responsibilities

• Manage and monitor company’s server and storage infrastructure, both on-premises and in the cloud.
• Install, configure, test, and maintain operating systems, application software, and system management tools.
• Ensure high availability, reliability, and performance of systems and infrastructure.
• Provide Tier 3 IT support to business units across the organization.
• Design and deliver solutions for complex IT infrastructure challenges.
• Collaborate with other departments to support company goals and technology initiatives.
• Identify opportunities to improve existing processes, automate repetitive tasks, and evaluate new technologies that enhance the end-user experience.

Requirements

Must-Have Experience

• 6+ years of hands-on infrastructure experience.
• Strong hands-on experience with VMware vSphere 6.x / 7.x, including installation, configuration, and system design.
• Strong knowledge of the Microsoft infrastructure stack, including:
  • Active Directory
  • DNS
  • DHCP
  • AD Connect
  • Windows Server
• Solid understanding of networking, operating systems, routing, and security fundamentals.
• Proven experience designing and building infrastructure environments, not only supporting existing systems.
• Security-conscious approach to system design, patching, access control, and infrastructure operations.

Cloud & Identity Management

• Hands-on experience with the Microsoft Azure ecosystem, including:
  • Microsoft Entra ID, formerly Azure AD
  • Identity and access management
  • SSO
  • Role-based access control
• Experience with Microsoft 365 services, including:
  • Exchange Online
  • Teams
  • SharePoint
• Experience with Microsoft Endpoint Manager / Intune.
• Experience with AWS services, especially:
  • EC2
  • S3
  • Route 53
  • FSx
• Understanding of hybrid cloud architectures and basic cloud security controls.

Virtualization & Infrastructure

• Hands-on experience with VMware-based infrastructure.
• Familiarity with physical servers and data center maintenance lifecycle.
• Experience with infrastructure design, implementation, upgrades, and ongoing optimization.

Operating Systems

• Strong working knowledge of:
  • Windows Server
  • Windows Client OS
  • Linux distributions
  • macOS
• Experience managing macOS endpoints with Jamf Pro or similar enterprise tools.

Storage & Backup

• Hands-on experience with NAS / SAN systems.
• Experience with storage platforms such as:
  • NetApp
  • QNAP
  • BlueXP
• Familiarity with backup systems, preferably Commvault / Metallic - advantage.

Scripting & Automation

• Proficiency in PowerShell and/or Python for system administration, automation, and process improvement.

   

Nice to Have

• Experience with NetApp or other enterprise storage platforms.
• Experience with Commvault / Metallic.

• Broader experience with hybrid cloud infrastructure and automation.

   

Soft Skills

• Self-managed and able to work independently.
• Proactive, improvement-driven, and solution-oriented.
• Strong troubleshooting and problem-solving skills in enterprise-scale production environments.
• Excellent interpersonal and communication skills.
• Ability to work effectively across teams and business units.
• Fluent English - written and verbal.

Although the role is focused on data migration, it is not in the traditional analytics or data science sense. The work involves migrating customer data into an application rather than into a data lake or data warehouse for analytical use. This won't be boring. One month you will be migrating data from Software A, the next from Software B and after that from a custom-built legacy app C, each with its own challenges and trade-offs.

We do understand that very few engineers specialize solely in migrations. So, if you are a software engineer, DB developer or DevOps professional with relevant migration experience, this is a great opportunity to join a serious product used by thousands of companies worldwide and make a real impact.

Requirements

• 2+ years of experience in data migrations.
• Proficiency in SQL.
• Hands-on experience with scripting in Python or Ruby (as popular ETL tools are not widely used in this role).
• Ability to take ownership of tasks with minimal direction and deliver high-quality results in a fast-paced environment.
• Self-starter who can work independently and collaboratively.
• Excellent communication, analytical, and problem-solving skills.
• Advanced level of English.

Responsibilities

• Work with data owners to understand legacy data, gather requirements, and design solutions to meet those needs.
• Produce detailed data mapping documentation.
• Develop and implement tools, scripts, queries, or applications for accessing, analyzing, converting, and migrating data between databases or from CSV files.
• Reverse-engineer data models from other vendors.
• Troubleshoot data quality issues and write scripts to cleanse data.
• Maintain data security, integrity, and availability in production environments.
• Collaborate with the Customer Success team to manage client expectations, communicate timelines, and resolve database issues.
• Serve as the technical point of contact during the migration process.

Nice to have

• Linux experience, including terminal usage and OS-level troubleshooting.
• Bachelor’s degree in Computer Information Systems or a related field.

Working conditions

• Mon — Fri, 8h/day, overlap with EST (US) at least 6 hours.

Interviewing stages

1. In-depth HR interview assessing your soft skills, English proficiency, etc.
2. Interview with CTO (chat + live coding test).
3. Final meet with your team lead (chat + live coding test).

Client

Our client is a prominent global wealth and asset management firm focused on delivering innovative investment solutions and a networked ecosystem of international opportunities. The organization operates within a highly regulated environment, prioritizing the transformation of complex concepts into actionable financial strategies for a global clientele.

Project overview

The project involves the development and expansion of a centralized, scalable data ecosystem. Having successfully ingested the initial data source, the team is now moving into a high-growth phase to integrate multiple high-value financial and operational data streams. The goal is to provide C-level executives and advisors with a unified, reliable reporting layer for strategic decision-making.

Position overview

As a Senior Data Engineer, you will be a technical cornerstone of the data platform team. You will be responsible for the end-to-end engineering of data pipelines, from ingestion to transformation, ensuring that the Snowflake warehouse is optimized for complex wealth management analytics. You will work at the intersection of sophisticated financial data and enterprise-grade engineering.

Responsibilities

• Design, build, and maintain scalable automated ETL/ELT pipelines to ingest data from diverse sources including Addepar, NetSuite, Salesforce, Morningstar, Bloomberg, and UKG.
• Architect and implement robust data models within Snowflake using DBT (Data Build Tool) to ensure high-performance transformations and clean data structures.
• Utilize Workato to orchestrate seamless integrations between third-party SaaS platforms and the central data warehouse.
• Monitor and optimize Snowflake performance, storage, and compute usage to ensure cost-effectiveness and reliability.
• Partner with Business Analysts and Tableau Engineers to ensure the data layer effectively supports complex business use cases and executive dashboards.
• Implement rigorous data validation and testing frameworks to maintain high data integrity, especially critical given the regulated nature of investment data.

Requirements

• Extensive hands-on experience as a Data Engineer focusing on Snowflake architecture, including advanced performance tuning and security features.
• Proven proficiency with DBT for data transformation and Workato (or similar enterprise integration platforms) for workflow automation.
• Strong ability to understand complex financial datasets and translate business-centric data needs into technical schemas.
• Solid understanding of software engineering best practices, including version control (Git) and CI/CD pipelines for data.
• Exceptional ability to communicate technical concepts effectively with both business stakeholders and cross-functional technical teams.

Nice to have

• Experience supporting reporting requirements for Tableau-based visualization layers.
• Experience within the Wealth Management or Investment Management sector, with specific familiarity handling investment and portfolio-related data.
• Understanding of regulatory requirements regarding financial data handling and privacy.
• Background in integrating market data providers such as Bloomberg or Morningstar.
• Advanced SQL skills and experience with Python for data engineering tasks.

🌎Akvelon is an American company with offices in Seattle, Mexico, Ukraine, Poland, and Serbia. Our company is an official vendor of Microsoft and Google. Our clients also include Amazon, Evernote, Intel, HP, Reddit, Pinterest, AT&T, T-Mobile, Starbucks, and LinkedIn. To work with Akvelon means to be connected with the best and brightest engineering teams from around the globe and working with an actual technology stack building Enterprise, CRM, LOB, Cloud, AI and Machine Learning, Cross-Platform, Mobile, and other types of applications customized to client’s needs and processes.

About the project:

The project is focused on building a modern data platform that processes and enriches data from multiple external sources and supports advanced analytics, machine learning workflows, and business decision-making.

About the role: 

As a Senior Data Engineer, you will design and build scalable data pipelines, data services, and ML-ready datasets for production use cases.

The role requires close collaboration with data science, engineering, and business teams. We are looking for someone with product-oriented data engineering experience, not only traditional DWH or reporting background.

Requirements:

Must have:

• Strong experience in Data Engineering
• Advanced Python
• Strong SQL
• Snowflake
• dbt
• Databricks / PySpark
• ETL/ELT pipeline design
• Experience supporting ML or advanced analytics workflows
• Experience building production-grade data systems
• Good English communication skills

Nice to have:

• Financial domain experience
• Feature engineering / ML-ready datasets experience
• APIs, data services, or data product integrations
• Real-time or iterative data processing experience
• Graph databases

Overlap: stay available until 8-9 PM CET

Working conditions and benefits:

• Flexible working schedule: 8 hours per day, 40 hours per week
• Paid vacation, sick leave (without a sickness list)
• Official state holidays – 11 days considered public holidays
• Professional growth while attending challenging projects and the possibility to switch your role, master new technologies and skills with company support
• Personal Career Development Plan (CDP)
• Employee support program (Discount, Care, Health, Legal compensation)
• Paid external training, conferences, and professional certification that meet the company’s business goals
• Internal workshops & seminars
• Corporate library (Paper/E-books) and internal English classes.

Step into your future – apply now 🚀 and send us your CV.

• Project Description:

  As a Senior Cloud Solution Architect at Lindt & Sprüngli, your primary goal is to design and implement cutting-edge cloud solutions, leveraging Microsoft Azure as the main hyperscaler. You will play a pivotal role in driving cloud adoption, ensuring scalability, reliability, and security for our clients' mission-critical systems.

• Responsibilities:

  The Senior Cloud Solution Architect is a key member of the Infrastructure Team, responsible for leading the design, architecture, and deployment of cloud solutions, with a focus on Microsoft Azure. This role requires a strategic mindset, hands-on technical expertise, and the ability to collaborate effectively with cross-functional teams and stay abreast of emerging technologies.

• Mandatory Skills Description:

  Technical Skills:
  • Master's Degree in Computer Science, IT, or similar field
  • 6+ years of commercial experience;
  • 2+ years of experience on a SA or similar role
  • Proven experience in designing and implementing complex, scalable, and secure cloud solutions on Microsoft Azure for enterprise-grade solutions (e.g. Cloud
  Adoption Framework, Well-Architected Framework, ).
  • Hands-on experience with a broad range of Microsoft Azure cloud services (IaaS, PaaS, Networking, Security, Data Services).
  • Experience with SAP solutions, containerization principles (e.g., Kubernetes, Docker), identity management, and data analytics and AI (e.g. Fabric, Databricks,
  Foundry) is a plus.
  • Proven experience designing hub-and-spoke topologies, cross-premises networking solutions in a hybrid-cloud environment (DNS, routing, VPN, ExpressRoute, Firewall).
  • Expertise in Infrastructure as Code (e.g., Terraform, ARM) and architectural principles for CI/CD.
  
  Soft Skills:
  • Strong problem-solving skills and attention to detail.
  • Strong commitment to quality, attention to detail, and continuous improvement.
  • Strong analytical and problem-solving skills, with the ability to troubleshoot and resolve complex technical issues across various cloud components.
  • Excellent communication, presentation, and leadership skills, with the ability to articulate complex technical concepts to diverse audiences.
  • Languages: English required, German a big plus, French / Italian / Spanish a plus

• Nice-to-Have Skills Description:

  German/French / Italian / Spanish

• Languages:
  • English: B2 Upper Intermediate

We are looking for a Big Data / Data Engineer to join our growing team. In this role, you will be responsible for the design and development of our big data processing engine — a heavy ETL pipeline handling complex logic including geo-location analysis, running across both cloud and on-prem environments.

Requirements:

• 4+ years of experience in Data Engineering
• 2+ years of hands-on experience with Scala (must) or Java (optional)
• 2+ years of experience with SQL and NoSQL DBs
• Hands-on experience with Spark & PySpark (must)
• Experience with Airflow (must)
• Experience with AWS and/or GCP
• Experience with Kubernetes (k8s) and on-prem deployments
• Solid understanding of distributed systems design, pipeline architecture, and partitioning strategies
• Deep understanding of Agile principles, practices and values
• Solid understanding of design patterns, software development techniques, and clean code practices
   

Advantage:

• Experience with Apache Iceberg, Helm Charts, or data catalog tools
• Experience with Spring Framework
• Experience with microservice architecture
• Experience working with DevOps and CI/CD practices
• Customer-facing experience or comfort working directly with clients
• Bachelor's, BSc or Master's degree in Computer Science or Engineering from a leading academic institution

About the Role

We are looking for a  Data Engineer to design, build, and operate large-scale data pipelines and lakehouse platforms in an enterprise environment. You will work hands-on with AWS data services, Apache Spark, and Python to deliver reliable, performant, and well-modeled data products that power analytics and downstream applications.

Key Responsibilities

• Design, implement, and maintain robust, reliable, and scalable data pipelines for batch and large-scale processing workloads.
• Build and evolve a Data Lakehouse on AWS using cloud object storage (S3), open table formats, and distributed processing frameworks.
• Develop ETL/ELT workflows in Python and Apache Spark, ensuring performance, cost-efficiency, and maintainability.
• Model data for analytical and reporting use cases, applying dimensional and analytical modeling best practices.
• Write advanced SQL for transformation, optimization, and ad-hoc analysis across large datasets.
• Operate and optimize AWS data services such as EMR, Glue, Athena, and S3-based data lakes.
• Troubleshoot pipeline and platform issues end-to-end, applying system-level thinking to identify root causes and durable fixes.
• Collaborate with analysts, data scientists, and platform engineers to translate business requirements into technical solutions.
• Contribute to data quality, observability, governance, and CI/CD practices for data workloads.

Required Qualifications

• Strong, proven hands-on experience in data engineering within enterprise environments.
• Top-notch advanced SQL skills and solid understanding of analytical and dimensional data modeling.
• Strong hands-on experience with Data Lakehouse or modern data platform concepts: cloud object storage, open table formats (e.g., Delta, Iceberg, Hudi), and distributed processing.
• Strong hands-on experience with AWS data services: EMR, Glue, Athena, and S3-based data lakes.
• Strong hands-on experience with Apache Spark for large-scale data processing.
• Strong Python skills for ETL development, data processing, and automation.
• Demonstrated experience designing, implementing, and maintaining robust and reliable data pipelines in production.
• Very strong analytical, problem-solving, and system-level thinking skills.

Nice to Have

• Experience with workflow orchestration tools (e.g., Airflow, Step Functions).
• Familiarity with infrastructure-as-code (Terraform, CloudFormation) and CI/CD for data.
• Exposure to data governance, cataloging (e.g., AWS Glue Data Catalog, Lake Formation), and data quality frameworks.
• Streaming experience (Kafka, Kinesis, Spark Structured Streaming).

Requirements

Total of 5+ years of development/design experience with a minimum of 5 years experience in Big Data technologies on-prem or on cloud.
Experience with architecting, building, implementing and managing Big Data platforms On Cloud, covering ingestion (Batch and Real time), processing (Batch and Realtime), Polyglot Storage, Data Analytics and Data Access
Good understanding of Data Governance, Data Security, Data Compliance, Data Quality, Meta Data Management, Master Data Management, Data Catalog
Proven understanding and demonstrable implementation experience of big data platform technologies on cloud (AWS and Azure) including surrounding services like IAM, SSO, Cluster monitoring, Log Analytics etc
Experience working with Enterprise Data Warehouse technologies, Multi-Dimensional Data Modeling, Data Architectures or other work related to the construction of enterprise data assets
Strong Experience implementing ETL/ELT processes and building data pipelines including workflow management, job scheduling and monitoring
Experience building stream-processing systems, using solutions such as Apache Spark, Databricks, Kafka etc…
Experience with Spark/Databricks technology is a must
Experience with Big Data querying tools
Solid skills in Python
Strong experience with data modelling and schema design
Strong SQL programming background
Excellent interpersonal and teamwork skills
Experience to drive solution/enterprise-level architecture, collaborate with other tech leads
Strong problem solving, troubleshooting and analysis skills
Experience working in a geographically distributed team
Experience with leading and mentorship of other team members
Good knowledge of Agile Scrum
Good communication skills

 #LI-OE1

#LI-Remote

Job responsibilities

Work directly with the Client teams to understand the requirements/needs and rapidly prototype data and analytics solutions based upon business requirements
Design, implement and manage large scale data platform/applications including ingestion, processing, storage, data access, data governance capabilities and related infrastructure
Support Design and development of solutions for the deployment of data analytics notebooks, tools, dashboards and reports to various stakeholders
Communication with Product/DevOps/Development/QA team
Architect data pipelines and ETL/ELT processes to connect with various data sources
Design and maintain enterprise data warehouse models
Take part in the performance optimization processes
Guide on research activities (PoC) if necessary
Manage cloud based data & analytics platform
Establishing best practices with CICD under BigData scope

What we offer

Culture of caring. At GlobalLogic, we prioritize a culture of caring. Across every region and department, at every level, we consistently put people first. From day one, you’ll experience an inclusive culture of acceptance and belonging, where you’ll have the chance to build meaningful connections with collaborative teammates, supportive managers, and compassionate leaders. 

Learning and development. We are committed to your continuous learning and development. You’ll learn and grow daily in an environment with many opportunities to try new things, sharpen your skills, and advance your career at GlobalLogic. With our Career Navigator tool as just one example, GlobalLogic offers a rich array of programs, training curricula, and hands-on opportunities to grow personally and professionally.

Interesting & meaningful work. GlobalLogic is known for engineering impact for and with clients around the world. As part of our team, you’ll have the chance to work on projects that matter. Each is a unique opportunity to engage your curiosity and creative problem-solving skills as you help clients reimagine what’s possible and bring new solutions to market. In the process, you’ll have the privilege of working on some of the most cutting-edge and impactful solutions shaping the world today.

Balance and flexibility. We believe in the importance of balance and flexibility. With many functional career areas, roles, and work arrangements, you can explore ways of achieving the perfect balance between your work and life. Your life extends beyond the office, and we always do our best to help you integrate and balance the best of work and life, having fun along the way!

High-trust organization. We are a high-trust organization where integrity is key. By joining GlobalLogic, you’re placing your trust in a safe, reliable, and ethical global company. Integrity and trust are a cornerstone of our value proposition to our employees and clients. You will find truthfulness, candor, and integrity in everything we do.

Pine Software Technology Ltd is a software company specializing in trading technology solutions for regulated brokers and trading firms. We build SaaS products that support electronic trading, brokerage operations, risk management, and financial data analysis.
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We are looking for a Lead Data Engineer for the Market Data Platform.
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Responsibilities

• Lead the design and development of the Data Platform, focusing on data pipelines, storage, and processing layers.
• Own architectural decisions around data storage, data modeling, and data access patterns.
• Design and build scalable data pipelines for ingestion, processing, and transformation (batch and streaming).
• Develop and maintain high-performance Python-based data processing components and services.
• Work with PostgreSQL and other storage systems to ensure correct schema design, partitioning, and performance optimization.
• Design and maintain streaming data pipelines for real-time market data processing (Kafka or similar).
• Implement data orchestration workflows (Airflow, Dagster, or similar).
• Ensure data reliability and quality: validation, monitoring, observability, and alerting.
• Optimize data systems for high throughput and low latency.
• Establish and drive best practices in data engineering, code quality, testing, and CI/CD.
• Define and maintain data contracts, schemas, and governance practices across teams.
• Mentor engineers and drive the technical growth of the data engineering team.
• Collaborate with platform, backend, and product teams to align data domains and interfaces.
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Job requirements

• 6+ years of professional experience in Data Engineering (with Python) and 1+ year in a Lead role.
• Strong experience building data-intensive systems and data platforms.
• Advanced proficiency in Python as a primary language for data engineering (data processing, pipelines, internal tooling).
• Strong experience with ETL/ELT pipelines (batch and streaming).
• Experience with distributed data processing frameworks (Apache Spark, Flink, or similar).
• Experience with streaming platforms and event-driven data pipelines (Apache Kafka or similar).
• Hands-on experience with data orchestration tools (Airflow, Dagster, or similar).
•  Strong practical experience with PostgreSQL and other data storage systems: schema design, query optimization, indexing, partitioning
•  Experience working with analytical databases/data warehouses/data lakes.
•  Strong knowledge of data modeling (OLTP, OLAP, dimensional modeling, time-series).
•  Experience designing and building high-throughput data ingestion and processing systems.
•  Experience implementing data quality, validation, and observability practices.
•  Experience with containerization and deployment practices (Docker, CI/CD).
•  Strong engineering discipline: clean architecture, testing, maintainability.
•  English level: B1-B2
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Nice to Have

• ClickHouse or other analytical / time-series databases, NoSQL solutions
• Kubernetes
• Experience with lakehouse technologies (Delta Lake, Iceberg, Hudi)
• Experience with real-time analytics systems
• Domain experience in trading/market data systems
• Familiarity with event sourcing
• Patterns: CQRS, Materialized Views, Snapshotting (in data context)
• Experience with cloud services (AWS S3, IAM, etc.)
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What We Offer

• Care from Day One — medical insurance from your first day, including dental care, massage, and professional psychological support.
• Work-Life Balance — 25 days of paid vacation + 30 days of paid sick leave.
• Investment in Your Energy — partial reimbursement for sports and fitness activities.
• Growth & Learning — coverage for English or Ukrainian language courses and a dedicated professional development budget.
• Knowledge Library — office books and access to the Kuka online library.
• Island Relaxation — up to 14 days per year at the company villa in Cyprus.
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 Please note, that only shortlisted candidates will be contacted. Thank you for considering Pine as your next career move!

We’re looking for a Data Engineer who:

— works with large-scale data (millions+ records)
— has strong Java (recent, hands-on)
— understands Kafka / streaming systems
— has experience with high-load systems or real-time data
— knows multithreading / concurrency
— is comfortable with system design and architecture decisions

What you’ll do:

— build data pipelines (batch / streaming)
— process high-volume data and real-time streams
— handle data quality (validation, deduplication)
— design architecture (Kafka, Redis, storage, etc.)
— optimize performance under load

Nice to have:

— Redis, Elasticsearch
— Cloud (AWS / GCP / Azure)

AI (secondary):

— uses tools like Copilot / Cursor (or willing to learn)
— can review AI-generated code

Important

This is not a typical ETL role.
We’re looking for engineers who understand scale, performance, and system design.