Jobs Data Engineer

On behalf of our client, we are looking for a Senior Data Engineer.

About the Project

A global platform managing over 700,000 hotel rooms across 124 countries, helping clients generate billions in revenue.

Responsibilities:

- Implement scaling of the case detection process (scanner)

- Split API into multiple API services

- Emulate pubsub/cloud run locally

- Extract and process data using PySpark + S3

- Work with Kafka/Kinesis data streams

- Write and optimize SQL queries on PostgreSQL/Redshift

- Use DynamoDB as a data source/sink

- Run and debug ETL jobs on Glue or EMR

- Monitor jobs via AWS console and Spark UI

Requirements:

- 5+ years of experience in Data Engineering

- 3+ years of experience with AWS (1+ year in the latest project)

- 2+ years of experience with Spark / PySpark (1+ year in the latest project)

- Strong experience with AWS S3

- Experience with Kafka or Kinesis

- Experience with DynamoDB

- Experience with PostgreSQL or MySQL

- Experience with AWS ECS Fargate

Nice to Have:

- AWS Glue

- EMR

- AWS Batch

- Flink

- Beam

- Cassandra / ScyllaDB

- AWS Step Functions

Company offers:

- Long-term employment with possibilities for professional growth

- Fully remote work

- Reasonably flexible schedule

- 15 days of paid vacation

- Regular performance reviews

We're looking for an AI Automation Engineer who builds workflow automations using n8n, Make/Zapier, and OpenAI. You'll work directly with clients to understand their processes, design automation flows, and ship working solutions fast.

This is a hands-on, execution-focused role. No endless meetings — you build, deploy, iterate.

What you'll do

• Design and build automation workflows in n8n and Make/Zapier
• Integrate OpenAI (GPT-4, Assistants API, function calling) into business workflows
• Connect third-party services via REST APIs (webhooks, OAuth, JSON parsing)
• Map client business processes and translate them into working automations
• Maintain and improve existing automation pipelines
• Communicate directly with clients (async-first, English)

What we're looking for

Must have:

• Hands-on experience with n8n or Make (Zapier is a plus)
• Understanding of REST APIs — you can read docs, set up webhooks, handle auth
• Experience integrating OpenAI API (prompt engineering, API calls, handling responses)
• Ability to decompose a business process into automation logic
• English sufficient for async client communication

Nice to have:

• Basic Python or JavaScript for custom nodes/scripts
• Experience with CRMs, Google Workspace, Notion, Slack, Airtable
• Understanding of LangChain or AI agent patterns

What we offer

• Remote, async-friendly work
• Real projects, real clients — not internal tooling
• Fast feedback loop: you ship, you see results
• Competitive rate (fixed or hourly — discussed individually)
• Opportunity to grow into LLM/chatbot and AI product projects

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)
• Flat and transparent internal communication
• Opportunity to switch between projects and technologies within Digis
• Full accounting and legal support

Job Description

Familiarity with Google Cloud Platform, including BigQuery, Cloud Composer (Airflow), Compute Engine, and Monitoring.
Strong proficiency in Python, including experience in building, testing, and deploying robust ETL/ELT pipelines in production
Experience developing data quality frameworks, including automated tests, cross-dataset validations, and anomaly detection across diverse data assets
Advanced SQL skills, including data modeling (star/snowflake/3NF), optimization, and writing performant queries tailored to BigQuery’s slot-based execution model
Solid working knowledge of DBT, including incremental models, testing, documentation, and advanced features like custom macros
Demonstrated ability to optimize BigQuery workloads through partitioning, clustering, materialized views, and cost-aware development practices
Experience working with ETL orchestration tools, ideally Cloud Composer or similar frameworks (Kestra, Dagster, etc.).
Hands-on experience consuming and managing APIs for data extraction.
Exposure to Site Reliability Engineering (SRE) best practices, including ticket triage, incident management, and documenting runbooks/SOPs
Familiar with Git and modern software development workflows, including pull requests and code reviews
Comfortable working in an agile team environment, with the ability to multitask and reprioritize based on changing project needs
Clear and effective communication skills, with the ability to engage technical and non-technical stakeholders alike

Job Responsibilities

Designing, building, and maintaining scalable, reliable data pipelines using Python,SQL, DBT, and Google Cloud Platform (GCP) services like BigQuery and Cloud Composer.
Contributing to the development and evolution of our data quality framework, ensuring robust automated testing and cross-dataset validation across all critical data assets
Writing and optimizing advanced SQL to power data models, analytics, and reporting pipelines, with a focus on performance and efficiency within BigQuery
Developing and maintaining DBT models, including testing, documentation, incremental loading strategies, and the creation of reusable macros
Supporting day-to-day incident and ticket resolution, including root cause analysis and documentation of runbooks/SOPs to drive platform reliability
Working with APIs and external data sources to extract, normalize, and integrate new datasets into the platform
Participating in agile ceremonies (stand-ups, retros, planning), contributing to sprint goals and helping support the wider team objectives
Actively contributing to code reviews, documentation, and peer learning - helping to raise engineering standards and share knowledge within the team
Monitoring system health and pipeline performance using GCP-native tools and dashboards, and proactively identifying opportunities for cost or performance optimization

Bonus points for

GCP Data Engineer certification
Prior experience in media, marketing, or digital advertising analytics
Experience implementing data quality frameworks and governance tools
Familiarity with cost optimization strategies for BigQuery and other GCP services

Department/Project Description

The client is transforming its global data infrastructure to deliver faster, more scalable, and more intelligent analytics capabilities. As part of this journey, we're hiring a Data Engineering to manage the technical delivery and operational resilience of our core data platform.

This role sits at the intersection of engineering leadership, platform reliability, and architecture - helping us ensure that data flows are healthy, scalable, and ready for production. You’ll work across project delivery, production support, and platform enhancement initiatives while mentoring a growing team of engineers.

Project Description

The client is transforming its global data infrastructure to deliver faster, more scalable, and more intelligent analytics capabilities. As part of this journey, we're hiring a Data Engineering to manage the technical delivery and operational resilience of our core data platform.

Job Description

- Familiarity with Google Cloud Platform, including BigQuery, Cloud Composer (Airflow), Compute Engine, and Monitoring.
- Strong proficiency in Python, including experience in building, testing, and deploying robust ETL/ELT pipelines in production
- Experience developing data quality frameworks, including automated tests, cross-dataset validations, and anomaly detection across diverse data assets
- Advanced SQL skills, including data modeling (star/snowflake/3NF), optimization, and writing performant queries tailored to BigQuery’s slot-based execution model
- Solid working knowledge of DBT, including incremental models, testing, documentation, and advanced features like custom macros
- Demonstrated ability to optimize BigQuery workloads through partitioning, clustering, materialized views, and cost-aware development practices
- Experience working with ETL orchestration tools, ideally Cloud Composer or similar frameworks (Kestra, Dagster, etc.).
- Hands-on experience consuming and managing APIs for data extraction.
- Exposure to Site Reliability Engineering (SRE) best practices, including ticket triage, incident management, and documenting runbooks/SOPs
- Familiar with Git and modern software development workflows, including pull requests and code reviews
- Comfortable working in an agile team environment, with the ability to multitask and reprioritize based on changing project needs
- Clear and effective communication skills, with the ability to engage technical and non-technical stakeholders alike

Job Responsibilities

- Designing, building, and maintaining scalable, reliable data pipelines using Python,SQL, DBT, and Google Cloud Platform (GCP) services like BigQuery and Cloud Composer.
- Contributing to the development and evolution of our data quality framework, ensuring robust automated testing and cross-dataset validation across all critical data assets
- Writing and optimizing advanced SQL to power data models, analytics, and reporting pipelines, with a focus on performance and efficiency within BigQuery
- Developing and maintaining DBT models, including testing, documentation, incremental loading strategies, and the creation of reusable macros
- Supporting day-to-day incident and ticket resolution, including root cause analysis and documentation of runbooks/SOPs to drive platform reliability
- Working with APIs and external data sources to extract, normalize, and integrate new datasets into the platform
- Participating in agile ceremonies (stand-ups, retros, planning), contributing to sprint goals and helping support the wider team objectives
- Actively contributing to code reviews, documentation, and peer learning - helping to raise engineering standards and share knowledge within the team
- Monitoring system health and pipeline performance using GCP-native tools and dashboards, and proactively identifying opportunities for cost or performance optimization

Bonus points for

GCP Data Engineer certification
Prior experience in media, marketing, or digital advertising analytics
Experience implementing data quality frameworks and governance tools
Familiarity with cost optimization strategies for BigQuery and other GCP services

About the role

We are sourcing a senior payments engineer for a US fintech client running a number of card tokenization deployments. The work centers on Mastercard Digital Enablement Service (MDES) and Visa Token Service (VTS) integrations — payment credential tokenization, lifecycle management, network certification, and supporting infrastructure for fintech rollouts.

This is not a generic "fintech experience" role. We are specifically looking for engineers who have shipped MDES or VTS in production, ideally at a card issuer, processor, or BaaS platform.

What you will work on

Card network tokenization flows (MDES and/or VTS) Token provisioning, lifecycle, and de-tokenization Network certification and compliance work Integration with card management systems, HSMs, and issuer/processor APIs Cross-functional work with payments product, risk, and infrastructure teams

Required

5+ years in payments engineering Production experience with MDES or VTS (not adjacent, not "exposure" — actual ship-to-prod work) Strong backend engineering (Java, Go, Python, or Node.js depending on stack) Familiarity with PCI DSS scope, HSM integration patterns, tokenization standards Comfortable working directly with a US-based product team in their working hours (some overlap required)

Nice to have

Background at Mastercard, Visa, Marqeta, Galileo, Stripe Issuing, Adyen, Thredd, GPS, Worldpay, Fiserv, or a similar issuer/processor/BaaS EMV / 3DS / ISO 8583 working knowledge Experience with Apple Pay / Google Pay / Samsung Pay provisioning flows Card issuing background (BIN sponsorship, KYC integrations, dispute flows)

Engagement details

Start: ASAP (within 2-3 weeks of selection) Duration: Multi-deployment scope, initial commitment 3-6 months with strong likelihood of extension Mode: Embedded full-time (40h/week) or senior project consulting (20-30h/week) depending on your availability Working hours: Some overlap with US Eastern timezone required (at least 3-4 hours)

How to apply

Reply with your CV and a short note covering:

1. The specific MDES or VTS production work you have shipped (network, issuer, processor, what role you played)
2. Your current availability and earliest possible start date

Thank you. 

About the Role

We're looking for a VoIP Engineer; this role sits at the intersection of telecom operations and integration work, with real ownership and direct business impact. You'll be responsible for the full lifecycle of communication channels: voice, SMS, email, and WhatsApp, keeping them reliable, optimized, and well-integrated across the business.

Key Responsibilities

- Own day-to-day operations of IP telephony, SMS/RCS, email, and WhatsApp Business API (WABA) 

- Configure, troubleshoot, and administer platforms such as Twilio, Vonage, Voximplant, and similar providers 

- Build and optimize call routing logic: IVR, voicemail, business hours, transfers, CLI, call recordings 

- Support telecom components integrated into the CRM: logs, templates, escalations, and routing modifications 

- Deliver integrations across communication systems using APIs, webhooks, and WebSockets 

- Handle internal support requests via a ticketing system; collaborate with QA during incidents and testing  

What We're Looking For

Required:

• Strong understanding of SIP, VoIP, trunks, routing logic
• Hands-on experience troubleshooting voice, SMS, email, or messaging channel incidents
• Ability to work with APIs, webhooks, JSON, logs, and provider documentation
• Self-sufficient, proactive, and comfortable managing vendors independently
• Fluent English

Nice to have:

• Experience with Twilio, Vonage, Voximplant, or similar platforms
• WABA operational knowledge
• Email deliverability and blacklist management
• SQL and spreadsheet skills
• Contact centre or high-volume comms environment background
• Scripting or automation experience

What We Offer

• Fully remote position (European timezone)

Не просто код, а твій вплив на мільйони українців

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

Про масштаб наших сервісів:

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

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

Що робитимеш як Data Engineer:

• Проектування, оптимізація та підтримка кластера Airflow, та коду на python.
• Розробка логіки ETL процесів.
• Проектування інтеграційної взаємодії систем, розробка сервісів інтеграції та обміну даними.

Твій ідеальний профіль:

Must-have:

• Професійний досвід роботи з Airflow.
• Досвід не менше 5 років в якості data engineer (python).
• Досвід роботи з Bash, Docker, Dbt, Gitlab CI\CD.
• Досвід роботи з MSSQL Server, Postgresql.

Nice-to-have:

• Досвід роботи з Apache Kafka, Pub/Sub, BigQuery, Apache Spark.

Чому експерти різних напрямів працюють з нами:

Технологічно:

• Високонавантажені системи з реальними викликами масштабування

• Сучасний стек та свобода технологічних рішень

• Можливість впливати на архітектуру продуктів, якими користуються мільйони

Професійно:

• Менторство від сеньйорів з досвідом enterprise-рішень

• Разом будуємо інновації, що працюють для мільйонів

Ідейно:

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

• Тут команди стають драйверами технологічних змін

Benefits:

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

• Добровільне медичне страхування та страхування життя.

• Корпоративні знижки від партнерів NOVA.

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

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

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

• Соціальні відпустки та компенсації відповідно до КЗпП України.

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

Очікуваний термін відповіді — до 10 робочих днів.

For our client in the energy industry, we are currently looking for an AI Engineer / Data Engineer
EU only !!!

Project & Role Overview
The role focuses on building production-grade AI applications and LLM pipelines, with a strong emphasis on scalability, observability, and modern development practices.

Key Responsibilities

• Develop production-grade Python applications using FastAPI, including async patterns and clean/easy patterns
• Build and manage LLM pipelines using OpenAI SDK, LangChain, or LangGraph
• Apply prompt engineering techniques, including structured outputs and Human-in-the-Loop (HITL) design
• Ensure LLM observability, meaning continuous monitoring, understanding, and analysis of LLM behavior in production (e.g., GPT, Copilot)
• Work with REST APIs and event-driven architectures
• Handle PostgreSQL databases and manage upstream/downstream data contracts
• Use AI coding tools such as GitHub Copilot, Codex, Claude Code, or similar
• Implement CI/CD pipelines, Docker-based environments, and follow testing best practices (testing pyramid)

Must-Have !!!

• Strong Python expertise with production-grade development (FastAPI, async patterns)
• Experience with LLM pipelines (OpenAI SDK, LangChain, LangGraph or similar)
• Solid prompt engineering skills (structured outputs, HITL concepts)
• Understanding of LLM observability (monitoring and analyzing LLMs in production environments)
• Experience with CI/CD pipelines, Docker, and testing strategies (testing pyramid)
• Experience with REST APIs and/or event-driven APIs
• Database experience, especially PostgreSQL
• Familiarity with AI coding tools (GitHub Copilot, Codex, Claude Code, etc.)
• Knowledge of data contracts (upstream/downstream integration)
• English fluency (mandatory)

Nice-to-Have Skills

• Experience with event-driven architecture (Azure Service Bus, Kafka, RabbitMQ or equivalent)
• Knowledge of async workers, fan-out / join patterns
• Experience with Azure-native services (Container Apps, KEDA autoscaling, IAM, secrets management)
• General Azure experience

Start: asap
Duration: 6 months (option of extension)
Location: remote
Language: English

About the Client

Our client is building advanced spatial computing and AI-powered solutions that transform large-scale visual data into accurate, high-quality 3D models. Their platform leverages cutting-edge computer vision, cloud infrastructure, and emerging technologies to solve complex real-world problems across industries.

About the Role

We are looking for a Senior Computer Vision & Photogrammetry Engineer to join the client’s team. This is a senior, high-impact role for someone who can bridge deep algorithmic expertise with scalable, production-grade infrastructure.

You will lead the design and deployment of high-performance 3D reconstruction pipelines, working closely with engineering and infrastructure teams to turn massive datasets into precise spatial outputs.

What You’ll Do

• Design and implement photogrammetry pipelines, including Structure from Motion (SfM), Multi-View Stereo (MVS), and bundle adjustment;
• Build and optimize high-performance 3D reconstruction workflows for large-scale datasets;
• Architect and manage compute infrastructure using Docker and Kubernetes;
• Develop data processing pipelines for ingesting, cleaning, and analyzing image and sensor data;
• Optimize algorithms for accuracy, performance, and scalability in production environments;
• Integrate multi-sensor data (e.g., IMU, GPS, LiDAR) for improved spatial accuracy;
• Apply state estimation techniques such as Kalman Filters for sensor fusion;
• Explore and integrate emerging approaches like Neural Radiance Fields (NeRF) and Gaussian Splatting;
• Optimize cloud-based processing workflows, particularly within AWS environments;
• Collaborate with cross-functional teams to productionize research-driven solutions;
• Monitor and improve system performance, reliability, and cost efficiency;
• Contribute to technical direction and best practices across computer vision and infrastructure.

Core Requirements

• 7+ years of experience in computer vision, photogrammetry, or spatial data engineering;
• Strong programming expertise in Python, including data processing with Pandas;
• Deep understanding of 3D geometry, camera models, and coordinate transformations;
• Proven experience with Structure from Motion (SfM) and Multi-View Stereo (MVS) pipelines;
• Strong experience with Docker and Kubernetes in production environments;
• Hands-on experience with large-scale data processing and optimization;
• Experience with at least one key 3D/vision library (e.g., Open3D, PCL, or Ceres Solver);
• Strong problem-solving skills and ability to work on complex technical systems;

Nice to Have

• Experience with SLAM (Simultaneous Localization and Mapping);
• Practical experience with NeRF or Gaussian Splatting;
• Experience implementing Kalman Filters or similar estimation techniques;
• Strong AWS experience (EC2 GPU, S3, Lambda, Batch, SageMaker);
• Background in real-time systems or sensor fusion;
• Experience with Kotlin.

What We Offer

• Competitive market salary;
• Fully remote work;
• Flexible working hours with overlap requirements;
• 28 days of paid time off per calendar year;
• Opportunity to work on impactful, cutting-edge technology;
• Collaboration with a highly professional, international team;
• Challenging projects with strong opportunities for growth and learning.

Success Metrics

• High-performance, scalable 3D reconstruction pipelines deployed to production;
• Measurable improvements in model accuracy and processing efficiency;
• Reliable and cost-optimized cloud infrastructure;
• Successful integration of advanced techniques into production workflows.

• Work confidently with SQL (BigQuery), Python, dbt, Google Cloud Platform (GCF, GCS, Cloud Build, Cloud Scheduler, Pub/Sub, IAM), and Data Modeling.
• Enjoy working with data at the infrastructure level and want to build a strong foundation for analytics.
• Feel comfortable handling large-scale datasets, complex transformations, and multiple data sources at the same time.
• Can identify potential issues in data and processes before they affect business results.
• Like working closely with analysts and cross-functional teams to build practical and scalable data solutions.
• Combine technical depth, systematic thinking, and ownership of results.

• Building and maintaining ELT processes for collecting, transforming, and loading data from multiple sources into BigQuery.
• Developing and scaling the dbt project for data modeling (stage, base, intermediate, dimension, report layers) used for analytics and reporting.
• Optimizing pipeline performance, SQL queries, and data models to improve efficiency and reliability.
• Validating, testing, and ensuring data quality across all stages of the data pipeline.
• Setting up monitoring and alerting for data pipelines and key infrastructure components.
• Integrating data from multiple sources (mobile app, finance, marketing), including APIs and external systems.
• Working closely with analysts to ensure data is well-structured, easy to use, and supports business needs.
• Maintaining up-to-date documentation for data architecture, ELT processes, and dbt models.
• Tools you’ll work with: SQL, Python, dbt, and GCP cloud services for building and maintaining data pipelines.

• 3+ years of experience as a Data Engineer or in a related role with a strong focus on pipelines and data modeling.
• Deep knowledge of SQL: complex queries, optimization, and understanding of Data Warehousing principles.
• Hands-on experience with BigQuery, Snowflake, Redshift, or other analytical data warehouses.
• Practical experience with dbt, including testing, documentation, and CI/CD integration.
• Experience building and maintaining ELT / ETL pipelines.
• Strong Python skills for integrations, automation, and data processes.
• Confident use of Git and experience working with GitHub / GitLab.
• Experience with GCP or other cloud platforms.
• Strong attention to detail, problem-solving mindset, and ownership of results.
• Experience working closely with analysts and understanding their data needs.

• Experience optimizing cost efficiency and query performance in cloud environments.
• Experience with real-time / streaming data solutions.
• Ability to explain technical solutions clearly to business stakeholders.

Are you an experienced Data Engineer ready to tackle complex, high-load, and data-intensive systems? 
We are looking for a Senior professional to join our team in Ukraine, Europe, working full-time on a project that will make a real impact in the public sector.

At Sigma Software, we specialize in delivering innovative solutions for enterprise clients and public organizations. In this role, you will contribute to building an integrated platform that collects, processes, and visualizes critical indicators, enabling better decision-making and analytics.

Why join us? You will work with a modern big data stack, have end-to-end involvement from ingestion to machine learning workflows, and be part of a professional team that values ownership, collaboration, and continuous improvement.
 

Project
You will be involved in developing an integrated platform that processes both batch and streaming data, ensures secure and governed data environments, and supports advanced analytics and machine learning workflows. The solution will leverage modern big data technologies to provide actionable insights for the public sector.
 

Responsibilities

• Design and implement data ingestion pipelines for batch and streaming data
• Configure and maintain data orchestration workflows (Airflow, NiFi) and CI/CD automation for data processes
• Design and organize data layers within Data Lake architecture (HDFS, Iceberg, S3)
• Build and maintain secure and governed data environments using Apache Ranger, Atlas, and SDX
• Develop SQL queries and optimize performance for analytical workloads in Hive/Impala
• Collaborate on data modeling for analytics and BI, ensuring clean schemas and dimensional models
• Support machine learning workflows using Spark MLlib or Cloudera Machine Learning (CML)
   

Requirements

• Proven experience in building and maintaining large-scale data pipelines (batch and streaming)
• Strong knowledge of data engineering fundamentals: ETL/ELT, data governance, data warehousing, Medallion architecture
• Strong SQL skills for Data Warehouse data serving
• Minimum 3 years of experience in Python or Scala for data processing
• Hands-on experience with Apache Spark, Kafka, Airflow, and distributed systems optimization
• Experience with Apache Ranger and Atlas for security and metadata management
• Upper-Intermediate English proficiency
   

Will be a plus

• Experience with Cloudera Data Platform (CDP)
• Advanced SQL skills and Hive/Impala query optimization
• BS in Computer Science or related field
• Exposure to ML frameworks and predictive modeling
   

Personal profile

• Ownership mindset and proactive approach
• Ability to drive initiatives forward and suggest improvements
• Team player with shared responsibility for delivery speed, efficiency, and quality
• Excellent written and verbal communication skills
   

Ти досвідчений Data Engineer і прагнеш реалізовувати складні, високонавантажені та орієнтовані на дані рішення? Ми шукаємо Senior-спеціаліста, який приєднається до нашої команди та допоможе створити продукт, що матиме значний вплив на державний сектор.

У Sigma Software ми розробляємо сучасні та інноваційні рішення для корпоративних клієнтів і державних установ. У цій ролі ти станеш частиною команди, яка будує інтегровану платформу для збору, обробки та візуалізації ключових показників, щоб забезпечити якісну аналітику та підтримати прийняття рішень.

Чому варто приєднатися? Ти працюватимеш із передовим стеком big data, матимеш можливість впливати на всі етапи розробки — від ingestion до machine learning, і будеш у команді, де цінують ініціативність, командну роботу та постійний розвиток.
 

Проект
Ти братимеш участь у створенні інтегрованої платформи, яка працює як з batch, так і з streaming даними, забезпечує захищене та кероване середовище даних, а також підтримує розширену аналітику та machine learning процеси. Рішення базуватиметься на сучасних big data технологіях, щоб надавати корисні інсайти для державного сектору.
 

Обов’язки

• Розробляти та впроваджувати data ingestion pipelines для batch та streaming даних
• Налаштовувати та підтримувати workflows для оркестрації даних (Airflow, NiFi) та CI/CD автоматизацію
• Проєктувати та організовувати шари даних у Data Lake архітектурі (HDFS, Iceberg, S3)
• Створювати та підтримувати безпечне та кероване середовище даних за допомогою Apache Ranger, Atlas та SDX
• Писати SQL-запити та оптимізувати їх продуктивність для аналітичних навантажень у Hive/Impala
• Брати участь у моделюванні даних для аналітики та BI, створюючи чисті схеми та багатовимірні моделі
• Підтримувати machine learning workflows, використовуючи Spark MLlib або Cloudera Machine Learning (CML)
   

Вимоги

• Досвід створення та підтримки масштабних конвеєрів даних (batch та streaming)
• Глибокі знання основ data engineering: ETL/ELT, data governance, data warehousing, Medallion architecture
• Впевнене володіння SQL для роботи з Data Warehouse
• Мінімум 3 роки досвіду роботи з Python або Scala для обробки та трансформації даних
• Практичний досвід роботи з Apache Spark, Kafka, Airflow та оптимізацією розподілених систем
• Досвід впровадження практик безпеки та управління метаданими (Apache Ranger, Atlas)
• Рівень англійської — Upper-Intermediate
   

WILL BE A PLUS:

• Досвід роботи з Cloudera Data Platform (CDP)
• Поглиблені навички SQL та оптимізація запитів у Hive/Impala
• Ступінь бакалавра в галузі Computer Science або суміжній сфері
• Знайомство з ML-фреймворками та predictive modeling
   

PERSONAL PROFILE:

• Відповідальність та проактивність
• Здатність просувати ідеї та пропонувати покращення
• Командний гравець, який розділяє відповідальність за швидкість, ефективність та якість
• Відмінні комунікативні навички — письмові та усні

We are looking for a Data Engineer to design and build scalable data platforms that support analytics, reporting, and data-driven decision-making across the organization. In this role, you will develop robust data pipelines, contribute to the evolution of our cloud data platform, and ensure reliable and efficient data processing across multiple projects and teams.

Responsibilities:

• Design and develop scalable and reliable data platforms and/or data pipelines for analytical and operational use cases
• Design and implement data processing workflows using distributed processing frameworks such as Apache Spark/PySpark (Databricks)
• Contribute to the evolution of the organization’s cloud data platform using Azure technologies (e.g., Azure Data Factory, Synapse, Microsoft Fabric, Databricks, Event Hub, Azure Data Lake Storage)
• Apply strong data modelling practices to support analytics, reporting, and downstream data consumption
• Integrate and process data from multiple internal and external sources while ensuring data consistency, quality, and reliability
• Take ownership of data pipeline reliability, monitoring, and performance to ensure scalable and maintainable data processing workflows
• Collaborate with data analysts, data scientists, and engineering teams to translate business and analytical requirements into robust data solutions
• Drive improvements in data engineering practices, including pipeline design standards, testing approaches, and operational reliability
• Participate in evaluating and introducing new tools and technologies within the data engineering ecosystem

Requirements:
 

• Strong hands-on experience (3+ years) in data engineering or building data processing platforms
• Strong SQL skills and solid experience with Python for building and maintaining data pipelines
• Experience working with distributed data processing frameworks such as Apache Spark/PySpark (Databricks experience is a strong advantage)
• Practical experience designing and implementing data pipelines in cloud environments, preferably within the Azure ecosystem
• Experience designing data pipelines and data models for production-scale analytical systems
• Strong understanding of data engineering concepts including ETL/ELT design, dimensional modeling, and data warehousing principles
• Experience working with modern data lake architectures and data formats such as Parquet and JSON
• Experience with workflow orchestration tools (e.g., Airflow)
• Experience with database development and performance optimization
• Ability to design scalable and maintainable data solutions with minimal supervision
• Strong collaboration and communication skills
• Professional working proficiency in English

Ми шукаємо Data Engineer, який допоможе проєктувати та будувати масштабовані платформи даних, що підтримують аналітику, звітність та прийняття рішень на основі даних в організації. У цій ролі ви розроблятимете надійні data pipelines, робитимете внесок у розвиток нашої хмарної платформи даних та забезпечуватимете надійну й ефективну обробку даних у межах кількох проєктів і команд.

Обов’язки:

• Проєктування та розробка масштабованих і надійних платформ даних та/або data pipelines для аналітичних і операційних сценаріїв використання
• Проєктування та реалізація workflow обробки даних із використанням розподілених фреймворків обробки даних, таких як Apache Spark/PySpark (Databricks)
• Участь у розвитку хмарної платформи даних організації з використанням технологій Azure (наприклад, Azure Data Factory, Synapse, Microsoft Fabric, Databricks, Event Hub, Azure Data Lake Storage)
• Застосування практик data modelling для підтримки аналітики, звітності та подальшого використання даних
• Інтеграція та обробка даних із різних внутрішніх і зовнішніх джерел із забезпеченням узгодженості, якості та надійності даних
• Відповідальність за надійність data pipelines, моніторинг і продуктивність для забезпечення масштабованих і підтримуваних workflow обробки даних
• Співпраця з data analysts, data scientists та інженерними командами для трансформації бізнесових і аналітичних вимог у надійні data-рішення
• Покращення практик data engineering, включно зі стандартами проєктування pipelines, підходами до тестування та операційною надійністю
• Участь в оцінці та впровадженні нових інструментів і технологій в екосистемі data engineering

Вимоги:

• Практичний досвід (3+ років) у data engineering або створенні платформ обробки даних
• Сильні навички SQL і впевнений досвід роботи з Python для побудови та підтримки data pipelines
• Досвід роботи з розподіленими фреймворками обробки даних, такими як Apache Spark/PySpark (досвід із Databricks буде значною перевагою)
• Практичний досвід проєктування та реалізації data pipelines у хмарних середовищах, бажано в екосистемі Azure
• Досвід проєктування data pipelines і моделей даних для аналітичних систем у продакшені
• Ґрунтовне розуміння концепцій data engineering, включно з ETL/ELT, dimensional modeling та принципами data warehousing
• Досвід роботи з сучасними архітектурами data lake та форматами даних, такими як Parquet і JSON
• Досвід роботи з інструментами оркестрації workflow (наприклад, Airflow)
• Досвід розробки баз даних і оптимізації продуктивності
• Здатність проєктувати масштабовані та підтримувані data-рішення з мінімальним наглядом
• Сильні навички комунікації та співпраці
• Високий рівень англійської мови