Jobs Data Engineer

We are looking for a Senior/Lead Data Engineer who is passionate about building scalable, cloud-native data solutions and eager to grow into a broader architecture role. You will lead the technical delivery of modern data platform solutions while engaging with clients and internal stakeholders to design, implement, and optimize enterprise-grade data systems.

Responsibilities

• Lead end-to-end development and implementation of scalable data pipelines, data lakes, and cloud-native data platforms
• Ensure performance, security, and reliability of data solutions through CI/CD, testing, and automation best practices
• Mentor and guide a team of engineers; review code, enforce standards, and foster knowledge sharing
• Participate in solution design with architects and senior stakeholders - contribute to data architecture, system integrations, and technology selection
• Translate business needs into data models, transformation logic, and orchestration workflows
• Gradually take on architecture ownership for projects and support pre-sales with technical scoping and effort estimation
• Work closely with business and technical stakeholders to clarify requirements, demonstrate value, and refine deliverables
• Participate in pre-sales activities: help shape proposals, provide technical insights, and create solution roadmaps
• Stay on top of modern data platform trends (e.g., Data Mesh, Lakehouse, real-time analytics, observability)

• Explore new tools and techniques - contribute to N-iX’s internal Data & Analytics accelerators and reference architectures

   

Requirements

• 5-7 years of hands-on experience in data engineering
• Strong SQL, Python, and Spark skills
• Strong expertise in Azure and Databricks modern data platforms
• Knowledge of Airflow, dbt, Kafka, or similar tools preferred
• Proven experience building data lakes, lakehouses, data warehouses, and streaming pipelines
• Familiarity with architectural concepts like Data Mesh, Data Fabric, and cloud-native data architectures
• Experience leading delivery teams or mentoring other engineers
• Excellent verbal and written communication in English
• Willingness to travel for business (when needed) and to engage directly with clients
   

We offer*:

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

*not applicable for freelancers

Digis is looking for a Senior Data Engineer to join our long-term partnership with a US-based global leader in hospitality analytics.

About the Project

Our client is a premier SaaS provider that transforms front-desk staff into revenue generators for the world’s most iconic hotel brands, including Hilton and Marriott. Their platform operates in over 2,000 properties across 124 countries, managing billions in revenue.

The project is in an active development stage, focusing on processing massive data volumes to deliver real-time business value.
You will join a large, distributed team (approx. 50 people) and collaborate directly with the US-based CTO.

Your Responsibilities
 

• Manage data pipelines from ingestion to ready-to-use analytical models.
• Help scale case detection processes and improve existing services by splitting them into smaller microservices.
• Build, debug, and optimize ETL jobs using AWS Glue, EMR, and Spark.
• Write and improve SQL queries for PostgreSQL/Redshift, and work with DynamoDB where needed.
• Support workflows in AWS ECS Fargate and set up local environments for testing and deployment.
   

Requirements
 

• 5+ years of experience as a Data Engineer.
• 2+ years of hands-on production experience with Spark or PySpark.
• 3+ years of experience with the AWS ecosystem (specifically Glue, EMR, S3, and Redshift).
• English: High level (Upper-Intermediate/Advanced) for frequent technical meetings and direct collaboration with the US CTO.

We Offer
 

• 20 paid vacation days per year
• 5 paid sick leaves per year (no medical documents required)
• Personalized development plan with training compensation
• English courses compensation
• Work equipment if needed (PC / laptop / monitor)
• Opportunity to switch between projects and technologies within Digis
• Full accounting and legal support

Profisea is an Israeli boutique DevOps and Cloud company with a full cycle of services. For more than nine years, we have been implementing best practices of GitOps, DevSecOps, and FinOps, and providing Kubernetes-based infrastructure services to help businesses of all sizes —SMB, SME, or large enterprise clients to stay innovative and effective.     

We are looking for a Data Engineer with 3+ years of experience building and maintaining scalable data platforms in cloud environments. The ideal candidate will design, implement, and optimize data pipelines that support analytics and data-driven applications across AWS and GCP ecosystems.
Responsibilities

• Design, develop, and maintain scalable data pipelines and ETL/ELT workflows.
• Build and manage data processing solutions using AWS Athena, AWS Glue, Glue Data Catalog, EMR, and S3.
• Implement data ingestion and replication pipelines using AWS DMS and other integration tools.
• Develop and orchestrate workflows using Apache Airflow and GCP Cloud Composer.
• Manage and optimize analytical workloads in Google BigQuery.
• Perform database migrations using AWS DMS and GCP Database Migration Service.
• Work with relational and NoSQL databases including PostgreSQL, MongoDB, Amazon RDS, DocumentDB, OpenSearch/Elasticsearch, and CloudSQL.
• Ensure data quality, reliability, and performance across data platforms.
• Collaborate with data analysts, data scientists, and software engineers to enable efficient data access and analytics.

Requirements

• 3+ years of experience in Data Engineering or related roles.
• Hands-on experience with AWS data services including Athena, Glue, Glue Data Catalog, EMR, DMS, and S3.
• Experience working with GCP data platforms, especially BigQuery and Cloud Composer.
• Experience with database migration tools such as AWS DMS or GCP Database Migration Service.
• Strong knowledge of SQL and data modeling.
• Experience working with PostgreSQL, MongoDB, and search platforms such as OpenSearch or Elasticsearch.
• Experience managing relational databases like RDS and CloudSQL.
• Familiarity with workflow orchestration tools such as Airflow.
• Understanding of data warehousing, data lakes, and distributed data processing concepts.

Nice to Have

• Experience with large-scale data lake architectures.
• Experience optimizing BigQuery or Athena query performance and cost.
• Knowledge of infrastructure-as-code and CI/CD for data platforms.
• Experience working in multi-cloud environments (AWS + GCP).

What we Offer: 

• Competitive salary   
• Remote work 
• Flexible schedule 
• Career growth 
• Sport compensations 
• Professional working environment, where you’d be an essential member of our company 
• Corporate culture, mutual support. 

Looking for Backend with #Python #Machine learning #AWS stack

We are looking for a Senior Data Engineer to build and scale a modern, AWS-based data platform powered by serverless pipelines, DuckDB, and Delta Lake architecture. You will work on integrating multiple SaaS and operational data sources into a robust data warehouse used for analytics and Tableau reporting. This role requires a hands-on engineer comfortable with Python-based data processing, AWS services, and non-traditional data stack components (DuckDB, Polars, etc.).

Seniority: Senior
English: Upper
Start date: April 4, 2026
Duration: 1-3 month

Project Description:

With more than 15 years of experience, the company blends human expertise with artificial intelligence to unlock new opportunities for individuals, organizations, and society. Its solutions turn complex data into clear insights — helping to understand past events and guide what can, could, or should be done next to transform industries and better serve people.

As a diversified leader in data science and AI, the company operates across various sectors and continues to grow at a rapid pace, creating new opportunities along the way. The team values individuals who are curious, driven, and passionate about solving complex challenges.

The organization brings together a multidisciplinary team of professionals, including data scientists, actuaries, statisticians, business analysts, strategy consultants, engineers, and product developers — all working together to leverage data for meaningful and transformative impact.

There is a strong focus on fostering a culture of growth, ownership, and continuous development. At the same time, the company emphasizes the importance of balance, offering a flexible and supportive environment where individuals feel valued and empowered.

Required Skills:

We are looking for candidates with strong hands-on experience in the following areas:

Cloud

• Google Cloud Platform (GCP)
• BigQuery
• Vertex AI
• Cloud Composer
• Cloud Functions

Programming

• Python
• SQL
• dbt

DevOps & Infrastructure

• Docker
• Kubernetes
• GitHub
• CI/CD pipelines

Additional

• Experience with AI / ML

Important:
A strong GCP background is critical for this role. Candidates without proven GCP experience are unlikely to be a strong fit.

We are looking for a Data Engineer to design and implement scalable data pipelines that support Generative AI applications. You will work with large-scale datasets, optimize performance, and ensure seamless data integration across AI workflows.

Responsibilities:

• Design and develop scalable data pipelines to support AI/ML models.
• Work with structured and unstructured data for training and inference.
• Optimize ETL workflows for real-time and batch processing.
• Ensure data quality, governance, and security in cloud environments.
• Collaborate with AI/ML engineers to streamline data workflows.

• Deploy and manage data infrastructure on AWS, GCP, or Azure.

   

Requirements:

• 3+ years of experience in Data Engineering and Big Data technologies.
• Expertise in ETL pipelines, data warehousing, and distributed computing.
• Strong knowledge of SQL, NoSQL, and data lakes.
• Experience with cloud-based data services (AWS Glue, BigQuery, Azure Data Factory).
• Proficiency in Python, Spark, Kafka, Airflow.

• Experience with CI/CD, DevOps, and Agile methodologies.

   

  What We Offer: 

  🚀 A role with real ownership and influence on delivery

  🌍 International eCommerce projects with global clients

  📈 Transparent growth path toward Middle+ → Senior PM

  🎓 Company-supported learning & certification programs

  🏠 Fully remote work with a flexible schedule

  🏝 Paid vacation & sick leave

  💰 Competitive compensation

  🔎 Mature processes and open team culture

We are looking for an experienced Data Engineer to design and implement scalable data pipelines, own core storage layers, and help build the foundations of a modern DataOps lifecycle.
 

Job requirements

• 3+ years of professional experience in Data Engineering / DWH development.
• Strong SQL expertise and solid Python skills (pandas, pyarrow).
• Production experience with Apache Airflow (production DAGs, scheduling, operators).
• Hands‑on work with PostgreSQL (schema design, migrations, partitioning) and ClickHouse (MergeTree engines, materialized views, performance tuning). 
• Experience with Data warehouse design — layered architecture, data modelling, denormalisation.
• Experience integrating REST APIs and third-party data sources
• Experience with Docker / Docker Compose — containerised services and multi-service environments
• Fluency in English.

Nice to Have:

• Experience with Apache Superset (RLS, dashboard layer).
• Familiarity with AI/LLM tooling for data (NL-to-SQL, vector databases). 
• Experience in the Fintech field: FX, brokerage, CRM/BO systems.
• Experience with multi-tenant data architectures.

Job responsibilities

• Design, build, and maintain ETL/ELT pipelines rom multiple product datasources.
• Model and optimise data structures in ClickHouse (views, engines, schema evolution).
• Orchestrate workflows using Apache AirflowCollaborate with BI teams (Superset) and backend teams (FastAPI/Python) to build reliable data products.
• Contribute to architectural decisions.
• Collaborate closely with product managers, BI developers, and DevOps to deliver data products end‑to‑end.

Job benefits

● Competitive and Attractive Pay.
● Flexible hours for a better work-life balance.
● Work your way: Hybrid flexibility to fit your life.
● 21 vacation + 7 no-questions-asked sick days per year.
● Career growth: Continuous Development & Performance Reviews.
 

The Role

We are looking for a Senior Data Engineer.

This is not a standard ETL role. We are building a dynamic data ecosystem where AI is deeply integrated—both as a productivity multiplier and as a core component of our data processing logic for identity data enrichment and data scoring.

You will own the infrastructure that handles over 10,000 executions per minute, ensuring stability, scalability, and data integrity. You will work with a modern stack on Google Cloud Platform, utilizing Cloud Functions and Kubernetes.

We are looking for an engineer who improves infrastructure, automates everything, and is eager to implement LLM-based logic directly into high-load data flows.

Responsibilities

• AI-Driven Data Scoring: Design and implement pipelines that utilize LLMs to analyze and score identity data in real-time. You will integrate AI models directly into the decision-making loop, balancing accuracy with latency and cost.
• Own the Data Architecture: Architect scalable data solutions using GCP and Python. You will manage data storage and retrieval using BigQuery and Apache Iceberg to support querying of TBs of data.
• Heavy Data Processing: Utilize Apache Spark for data transformations and batch processing when lightweight cloud functions are not enough.
• Manage High-Load Orchestration: Maintain and optimize our system instances. It involves complex dataflows, custom Python nodes, and performance tuning for 10k+ execs/minute.
• Release Lifecycle (CI/CD): Take ownership of the deployment process, ensuring that updates to pipelines and infrastructure are released safely with proper testing and rollback strategies.
• Database Optimization: Manage PostgreSQL performance under heavy load, optimizing complex queries and indexing strategies.
• Active AI Usage: Use Claude Code and other AI engineering tools to accelerate your own development, refactoring, and testing processes.
• Incident Resolution: Proactively monitor the system. When alerts fire, you investigate the root cause—whether it’s a database lock or an LLM hallucination—and fix it permanently.

Requirements

• 4-5+ years of experience in Data Engineering or Backend Engineering with a strong data focus.
• Production AI Integration: Experience integrating LLMs (OpenAI, Anthropic, Gemini) into production applications via API. You understand latency, token limits, and how to structure data for AI scoring.
• Expertise in GCP: Understanding of Google Cloud Platform (Cloud Functions, IAM, Networking).
• Strong Python: You write clean, efficient, and testable code. You are comfortable building custom logic where standard tools fall short.
• Big Data Stack: Experience with BigQuery, Apache Spark, and modern table formats like Apache Iceberg.
• Kubernetes (K8s): Experience deploying and scaling services in containerized environments.
• Workflow Automation: Understanding of workflow orchestration tools at a deep technical level. N8N is a big part of our domain, so familiarity with it is highly valuable.
• PostgreSQL Mastery: Proven ability to handle heavy write/read loads and optimize schemas.
• English: B2+ (Upper-Intermediate) or higher.

Culture & Mindset

• Self-improvement: You are a fast learner. You don't fear AI replacing you; you master it to replace your manual tasks.
• Ownership: You treat the Identity domain as your own business. If a scoring model drifts or a pipeline slows down, you notice it and fix it without being asked.
• Internal Locus of Control: You take responsibility for outcomes. If an external API fails, you build a fallback mechanism instead of just blaming the provider.
• Get It Done: You prioritize shipping value. You know when to use a simple script and when to build a complex architecture.

Openness: You share knowledge freely. If you find a better way to prompt the AI for scoring, you share it with the team.

Are you passionate about building large-scale cloud data infrastructure that makes a real difference? We are looking for a Senior Data Engineer to join our team and work on an impactful healthcare technology project. This role offers a remote work format with the flexibility to collaborate across international teams.

At Sigma Software, we deliver innovative IT solutions to global clients in multiple industries, and we take pride in projects that improve lives. Joining us means working with cutting-edge technologies, contributing to meaningful initiatives, and growing in a supportive environment.

CUSTOMER
Our client is a leading medical technology company. Its portfolio of products, services, and solutions is at the center of clinical decision-making and treatment pathways. Patient-centered innovation has always been, and will always be, at the core of the company. The client is committed to improving patient outcomes and experiences, regardless of where patients live or what they face. The Customer is innovating sustainably to provide healthcare for everyone, everywhere. 

PROJECT
The project focuses on building and maintaining large-scale cloud-based data infrastructure for healthcare applications. It involves designing efficient data pipelines, creating self-service tools, and implementing microservices to simplify complex processes. The work will directly impact how healthcare providers access, process, and analyze critical medical data, ultimately improving patient care.

Responsibilities:

• Collaborate with the Product Owner and team leads to define and design efficient pipelines and data schemas
• Build and maintain infrastructure using Terraform for cloud platforms
• Design and implement large-scale cloud data infrastructure, self-service tooling, and microservices
• Work with large datasets to optimize performance and ensure seamless data integration
• Develop and maintain squad-specific data architectures and pipelines following ETL and Data Lake principles
• Discover, analyze, and organize disparate data sources into clean, understandable schemas

Requirements:

• Hands-on experience with cloud computing services in data and analytics
• Experience with data modeling, reporting tools, data governance, and data warehousing
• Proficiency in Python and PySpark for distributed data processing
• Experience with Azure, Snowflake, and Databricks
• Experience with Docker and Kubernetes
• Knowledge of infrastructure as code (Terraform)
• Advanced SQL skills and familiarity with big data databases such as Snowflake, Redshift, etc.
• Experience with stream processing technologies such as Kafka, Spark Structured Streaming
• At least an Upper-Intermediate level of English 

Are you passionate about building large-scale cloud data infrastructure that makes a real difference? We are looking for a Senior Data Engineer to join our team and work on an impactful healthcare technology project. This role offers a remote work format with the flexibility to collaborate across international teams.

At Sigma Software, we deliver innovative IT solutions to global clients in multiple industries, and we take pride in projects that improve lives. Joining us means working with cutting-edge technologies, contributing to meaningful initiatives, and growing in a supportive environment.

CUSTOMER
Our client is a leading medical technology company. Its portfolio of products, services, and solutions is at the center of clinical decision-making and treatment pathways. Patient-centered innovation has always been, and will always be, at the core of the company. The client is committed to improving patient outcomes and experiences, regardless of where patients live or what they face. The Customer is innovating sustainably to provide healthcare for everyone, everywhere. 

PROJECT
The project focuses on building and maintaining large-scale cloud-based data infrastructure for healthcare applications. It involves designing efficient data pipelines, creating self-service tools, and implementing microservices to simplify complex processes. The work will directly impact how healthcare providers access, process, and analyze critical medical data, ultimately improving patient care.

Responsibilities:

• Collaborate with the Product Owner and team leads to define and design efficient pipelines and data schemas
• Build and maintain infrastructure using Terraform for cloud platforms
• Design and implement large-scale cloud data infrastructure, self-service tooling, and microservices
• Work with large datasets to optimize performance and ensure seamless data integration
• Develop and maintain squad-specific data architectures and pipelines following ETL and Data Lake principles
• Discover, analyze, and organize disparate data sources into clean, understandable schemas

Requirements:

• Possibility to meet clients annually in Europe
• Hands-on experience with cloud computing services in data and analytics
• Experience with data modeling, reporting tools, data governance, and data warehousing
• Proficiency in Python and PySpark for distributed data processing
• Experience with Azure, Snowflake, and Databricks
• Experience with Docker and Kubernetes
• Knowledge of infrastructure as code (Terraform)
• Advanced SQL skills and familiarity with big data databases such as Snowflake, Redshift, etc.
• Experience with stream processing technologies such as Kafka, Spark Structured Streaming
• At least an Upper-Intermediate level of English 

Чи захоплюєтесь ви створенням масштабної хмарної інфраструктури даних, яка має реальний вплив? Ми шукаємо Senior Data Engineer, який приєднається до нашої команди та працюватиме над важливим проєктом у сфері медичних технологій. Ця роль передбачає віддалений формат роботи з можливістю співпрацювати з міжнародними командами.

У Sigma Software ми створюємо інноваційні ІТ-рішення для глобальних клієнтів у різних галузях і пишаємося проєктами, які покращують життя людей. Приєднавшись до нас, ви працюватимете з передовими технологіями, робитимете внесок у значущі ініціативи та розвиватиметеся в підтримуючому середовищі.

Клієнт:
Наш клієнт — провідна компанія у сфері медичних технологій. Її портфель продуктів, сервісів та рішень знаходиться в центрі процесів клінічного прийняття рішень і побудови шляхів лікування. Інновації, орієнтовані на пацієнтів, завжди були і залишаються основою діяльності компанії. Клієнт прагне покращувати результати лікування та досвід пацієнтів незалежно від того, де вони живуть і з якими викликами стикаються. Компанія інноваційно розвивається, щоб забезпечити доступ до медицини для кожного, всюди.

Проєкт:
Проєкт зосереджений на створенні та підтримці масштабної хмарної інфраструктури даних для медичних застосунків. Він включає проєктування ефективних data pipelines, створення self-service інструментів та реалізацію мікросервісів для спрощення складних процесів. Робота безпосередньо впливатиме на те, як медичні установи отримують доступ до критично важливих медичних даних, обробляють їх та аналізують, що зрештою покращує якість медичної допомоги пацієнтам.

 

Обов'язки: 

• Співпрацювати з Product Owner та технічними лідами для визначення та проєктування ефективних pipelines і схем даних
• Будувати та підтримувати інфраструктуру для хмарних платформ за допомогою Terraform
• Проєктувати та впроваджувати масштабну хмарну інфраструктуру даних, self-service інструменти та мікросервіси
• Працювати з великими наборами даних для оптимізації продуктивності та забезпечення безперебійної інтеграції даних
• Розробляти та підтримувати архітектури даних і pipelines для команди відповідно до принципів ETL та Data Lake
• Виявляти, аналізувати та впорядковувати різнорідні джерела даних у зрозумілі та чисті схеми

Вимоги:

• Можливість раз на рік зустрічатися з клієнтами в Європі
• Практичний досвід роботи з хмарними сервісами для даних та аналітики
• Досвід data modeling, reporting tools, data governance та data warehousing
• Впевнене володіння Python і PySpark для розподіленої обробки даних
• Досвід роботи з Azure, Snowflake та Databricks
• Досвід роботи з Docker та Kubernetes
• Знання infrastructure as code (Terraform)
• Просунуті навички SQL та знайомство з big data базами даних, такими як Snowflake, Redshift тощо
• Досвід роботи зі stream processing технологіями, такими як Kafka, Spark Structured Streaming
• Рівень англійської не нижче Upper-Intermediate

Our customer is one of the world's largest food and beverage companies, operating in 189 countries with over 2000 brands. The company's diverse portfolio includes products such as bottled water, dairy products, breakfast cereals, coffee, confectionery, frozen food, pet foods, snacks, and baby food.

We are looking for a Middle Data Engineer to design, build, and maintain scalable data systems that support analytics, reporting, and machine learning use cases. This role requires strong ownership, solid SQL skills, and experience working with large datasets in production environments.

Responsibilities

• Build and maintain data pipelines (batch and near real-time).
• Develop and optimize data models for analytics and BI tools.
• Write efficient SQL queries for large-scale datasets.
• Support development and maintenance of ETL/ELT processes.
• Ensure data quality, integrity, and consistency across systems.
• Collaborate with data analysts, data scientists, and product teams to understand data requirements.
• Monitor and troubleshoot data pipelines and workflows.
• Contribute to improving the performance of the existing data infrastructure.
• Work with cloud-based data platforms and modern data stack tools.

Requirements

• 2–4 years of experience in Data Engineering or a related role.
• Main technical skills are: Snowflake, dbt, ADF.
• Solid SQL skills (joins, aggregations, window functions).
• Understanding of data governance and data quality concepts.
• Proficiency in Python.
• Experience with ETL/ELT tools.
• Hands-on experience with the Azure cloud platform.
• Azure Ops experience: provisioning and configuring.
• Experience working with data warehouses (e.g., Snowflake, BigQuery, Redshift).
• Understanding of data modeling concepts (e.g., star schema).

Nice to have

• Basic knowledge of Docker or containerization.
• Experience with data processing frameworks (e.g., Spark).

Soft skills

• Strong analytical thinking and problem-solving skills.
• Ability to work independently with some guidance.
• Good communication skills with technical and non-technical stakeholders.
• Willingness to learn and grow in a collaborative environment.

We offer*:

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

*not applicable for freelancers

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
   

  NICE TO HAVE:
   

• 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
• Experience with FHIR
   

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…)

Project Overview

UADAMAGE is hiring a Data Engineer to join a cross-functional team working on a national-scale Big Data platform for Ukraine. The project focuses on building a geospatial platform for multifactor analysis of territories to support demining and recovery planning. The system integrates remote sensing, environmental and socio-economic indicators, and includes both Big Data infrastructure and AI/ML modules. The platform is under active development with support from governance and international partners.

Role Summary

Design and maintain scalable and sustainable data pipelines within the platform to ensure timely, accurate, and consistent integration of multi-source data. Develop and support workflows for data ingestion, cleansing, normalization, and transformation from internal and external sources (e.g. government systems, commercial registers, API feeds). Ensure compatibility of all data pipelines with downstream use in GIS systems, land analysis models, dashboards and reports. Execute basic data analysis. Collaborate with product, analytics, and engineering teams to maintain data quality and feasibility for decision-support tools. Support data architecture evolution, implement data processing best practices, and contribute to technical documentation.

Qualifications required

• Bachelor’s or Master’s degree in Computer Science, Information Systems, Data Engineering, or related fields.
• 3+ years of experience in data engineering or data platform development.
• Proven experience in building and maintaining data pipelines (ETL/ELT), performing data cleansing, normalization, and transformation of structured and unstructured datasets.
• Hands-on experience with technologies such as Python, PySpark, Scala, SQL, Pandas, NumPy and tools including Apache Spark, Hadoop, and Amazon EMR.
• Experience working with AWS-based platforms, including S3 and cloud-native data processing services.
• Practical knowledge of streaming frameworks and distributed data processing patterns, such as MapReduce and real-time cloud pipelines.
• Experience integrating data from diverse sources (relational databases, APIs, satellite/geospatial data, file systems) for use in analytical models and data management platforms.
• Understanding of data integration strategies, API/data services, and long-term system maintainability.
• Familiarity with best practices in data documentation, versioning, metadata tracking, and validation.
• Familiarity with geospatial data formats, geo coordinate systems, and spatial preprocessing is an asset.
• Experience working in complex or multi-stakeholder environments is an asset.

• Proficiency in Ukrainian and English is required.

   

We offer

• Competitive salary
• Motivated and engaged team
• Open communication and active knowledge sharing
• Direct support from project leadership
• Clear specifications and well-defined requirements
• Opportunity to contribute to a high-impact, nationally relevant initiative

Project Description:

We are seeking a skilled, hands-on Data Engineer with demonstrated experience in Databricks, Apache Spark, Python, and real-time data streaming solutions.

Responsibilities:

- Implement resource composition logic provided by the Product team into scalable and efficient PySpark code.
- Develop, optimize, and maintain PySpark applications within the Databricks environment.
- Utilize and maintain existing CI/CD pipelines in Databricks for automated build, testing, and deployment.
- Write and maintain unit tests to ensure high code quality and reliability.
- Perform data validation and quality checks to ensure compliance with defined business rules
- Support and manage production deployments, ensuring system stability and performance.
- Troubleshoot and resolve issues across development, testing, and production environments.
- Collaborate with Product, QA, DevOps, and healthcare domain teams to ensure accurate implementation.
- Maintain technical documentation for code, workflows, and deployment processes.
- Pull from and push code to GitHub repositories, following version control and branching best practices.

Mandatory Skills Description:

- 5+ years of experience in data engineering roles
- Bachelor’s degree in Computer Science, Engineering, or related field (or equivalent experience).
- 4+ years of experience with Databricks data pipelines
- Strong hands-on experience with PySpark and/or Apache Spark.
- Experience working with CI/CD pipelines and DevOps best practices.
- Proficiency with CI/CD, GitHub (pull requests, branching, code reviews).
- Experience writing unit tests and performing data validation
- Experience supporting production systems and deployments
- Strong analytical and troubleshooting skills.

Nice-to-Have Skills Description:

- Knowledge of FHIR (Fast Healthcare Interoperability Resources) standards.
- Experience with healthcare data integration projects.
- Familiarity with REST APIs and FHIR server integrations.
- Experience in Agile/Scrum development environments.

Languages:

English: C1 Advanced

    We are looking for an experienced Head of Analytics / Analytics Manager to lead the development and maintenance of company-wide reporting, manage core data sources, and drive the implementation of modern analytics and AI-enabled solutions. 
    This role combines hands-on expertise in Power BI, SQL, and Python with ownership of analytics processes, data quality, and a small analytics team. You will play a key role in ensuring reliable management reporting, supporting business growth, and evolving our analytics ecosystem.


Key Responsibilities

• Design, build, and maintain Power BI dashboards and reports for company management and business stakeholders ;
• Own and manage global data sources, including:
 - HRM system ;
 - Time tracking system ;
 - Agent schedules and workforce data ;

• Fully build and support reporting and data logic for the company’s main project, ensuring data accuracy and consistency ;

• Implement reporting for new projects, including: 
- Connecting to new data sources o Integrating data via APIs ;
- Creating new dashboards and data models; 

• Develop and improve data models and DAX calculations in Power BI ;

• Write and optimize SQL queries and data transformations; 

• Participate in the development of Microsoft Fabric capabilities within existing processes; 

• Coordinate implementation of ML / forecasting solutions together with external vendors; 

• Lead and manage a small team: Reporting & Data Analyst and Operational Analyst;
• Define priorities, distribute tasks, and review results;

• Ensure documentation, stability, and reliability of reporting solutions;

• Collect, process, and analyze Customer Experience (CX) data (CSAT, NPS, CES, QA scores, customer feedback, complaints, etc.)
• Build CX dashboards and analytical views to monitor service quality and customer satisfaction
  
  Required Qualifications
   
• Higher education in IT, Computer Science, Mathematics, Finance, or related field;
• 3+ years of hands-on experience with Power BI;
• Strong and practical knowledge of DAX;
• 3+ years of experience with SQL and building complex queries;
• 1+ year of experience with Python (for data processing / automation / ETL tasks);
• Experience connecting to external systems via APIs;
• Solid understanding of data modeling and BI best practices;
• Experience working with large datasets;
• English level: B1 or higher;

Nice to Have
 

• Experience with Microsoft Fabric (Dataflows Gen2, Lakehouse/Warehouse, Notebooks, Pipelines);
• Exposure to forecasting or machine learning concepts;
• Experience in BPO / Contact Center / Operations analytics;

What We Offer

• Opportunity to build and shape the analytics function
• Direct impact on management decision-making
• Participation in AI-driven analytics transformation
• Professional growth in a fast-scaling company