Jobs Data Engineer

We’re looking for a Data Engineer to improve our data infrastructure and integration workflows.

This role is a great fit for someone who can quickly step into an existing environment, bring strong technical expertise, and help us build reliable, scalable solutions with a practical hands-on approach.

What you’ll do:

• Design and build data templates for integration workflows
• Optimize and improve existing data pipelines
• Ensure smooth and reliable integration across SaaS systems
• Work closely with the team to improve performance, stability, and maintainability of data flows

What we’re looking for:

• Commercial experience as a Data Engineer
• Hands-on experience with Azure
• Knowledge of Snowflake
• Python skills for data engineering tasks
• Experience working with SaaS products and integrations
• Understanding of building efficient, scalable, and maintainable data pipelines

Would be a plus:

• Experience with ETL / ELT
• Experience with cloud-based data platforms and modern data stack
• Ability to work independently and move fast in a short-term project setup

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

Project Description:

It is a real-time data processing and analytics solution for a high-traffic web application. 
Tech stack.
AWS: AWS Glue Studio, Redshift, RDS, Airflow, AWS Step Function, Lambda, AWS Kinesis, Athena, Apache Iceberg, AWS Data Brew, S3, OpenSearch, Python, SQL, CI/CD, dbt, Snowflake

 Responsibilities:

• Design a scalable and robust AWS cloud architecture;
• Utilize AWS Kinesis for real-time data streaming and aggregation;
• Implemente AWS Lambda for serverless data processing, reducing operational costs;
• Configured AWS RDS (Relational Database Service) for structured data storage and AWS DynamoDB for NoSQL requirements;
• Ensured data security and compliance with AWS IAM (Identity and Access Management) and encryption services;
• Developed and deployed data pipelines using AWS Glue for ETL processes;
• Wrote Python scripts and SQL queries for data transformation and loading;
• Set up continuous integration and continuous deployment (CI/CD) pipelines using AWS CodePipeline and CodeBuild;
• Monitored system performance and data quality using AWS CloudWatch and custom logging solutions;
• Collaborated with other teams to integrate data sources and optimize data flow;
• Achieve a highly scalable real-time data processing system, resulting in a 40% increase in data analysis efficiency and a significant reduction in operational costs.
• Build ETL pipelines from S3 to AWS OpenSearch by AWS Glue
• Upper-Intermediate or higher English level.

About the Role
 

Company domain - automotive industry.
We are looking for Data Engineers to join a managed service team delivering modern data products.
 

The role is focused on hands-on implementation under defined standards and senior guidance. You will contribute to building data products, ensuring quality and compliance with established frameworks.
 

Responsibilities
 

• Implement pipelines and data transformations
• Build analytical and source-aligned data products
• Follow established standards (data contracts, modeling patterns, testing strategies)
• Work in cross-functional domain teams
• Participate in pair-programming and knowledge transfer
• Support monitoring and operational excellence of delivered data products
   

Required Technical Stack
 

Mandatory experience with:
 

• AWS
• Azure
• Snowflake
• dbt
• Witboost
• Dreamio
• Modern ELT/ETL practices
• CI/CD in data environments
• Automated testing for data pipelines
   

Required Experience
 

• 1–3 years in Data Engineering
• Previous assignments delivering pipelines and data products
• Familiarity with Data Mesh
• Basic understanding of DataOps
• Understanding of governance, lineage, SLAs
• Comfortable working in Agile cross-functional teams

We are looking for an experienced Data Engineer to leverage their skillset in a fast-paced financial trading environment. You will be responsible for designing, developing, and maintaining data pipelines and infrastructure across GCP , and Oracle-based systems, ensuring high-performance data flows that support trading, risk, and compliance functions. This role requires a deep understanding of cloud architecture, large-scale data processing, and a strong grasp of agile delivery practices.
 

About the client
 

An international consulting firm that helps companies of all sizes have a better impact on the world. Company capabilities focus on supporting the private and public sectors with their people, processes, and digital technology challenges.
 

What You Will Do
 

● Design, build, and maintain scalable data pipelines primarily within Google Cloud Platform
 

● Develop integration and transformation workflows between cloud data services and on-prem Oracle databases
 

● Work closely with trading, risk, and analytics teams to understand data requirements and deliver real-time and batch data solutions
 

● Optimise and monitor performance of data systems to support latency-sensitive trading applications
 

● Collaborate with cross-functional teams using Agile/Scrum methodologies to deliver business-critical data projects
 

● Ensure robust data governance, lineage, and compliance (including MiFID II, FCA, and other regulatory standards)
 

● Automate data workflows using Terraform, CI/CD pipelines, and containerisation tools (Docker/Kubernetes)
 

What you will bring
 

● Strong experience with Google Cloud Platform (GCP) e.g. BigQuery, DataPlex, DBT, Pub/Sub, Dataflow, S3, Glue, Redshift
 

● Expertise in Oracle SQL, PL/SQL, and working with complex stored procedures and large datasets
 

● Proficiency in programming languages such as Python, Java, or Scala
 

● Experience with streaming and messaging systems (e.g. Jenkins, GitLab), and container orchestration (Kubernetes)
 

● Experience working with Infrastructure as Code, preferably Terraform, to manage cloud data infrastructure.
 

● Deep understanding of data modelling, data warehousing, and ETL/ELT design patterns
 

● Familiarity with Agile development practices (Scrum, Kanban, Jira)
 

● Exposure to financial markets, trading systems, or related high-performance environments is a strong plus
 

Nice to have
 

● GCP certification (e.g., Professional Data Engineer or similar) will be considered a strong advantage.
 

● Experience with Amazon Web Services (AWS)
 

● Knowledge of regulatory reporting, market data, or trade surveillance systems
 

● Experience with Apache Airflow, DBT, or similar orchestration tools
 

● Understanding of data security practices and compliance frameworks

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.

🚀 About the Project

Our client is rebuilding their core technology stack with a strong focus on Azure cloud infrastructure and .NET backend services. This is a high-impact modernization initiative where data plays a critical role in business operations.

We are looking for a Data Engineer who will drive backend data services development, optimize ETL processes, and ensure reliable data flows across the system. You’ll work with large-scale datasets and contribute to building a scalable, cloud-native data infrastructure.

Engagement model: Long-term outstaff collaboration

Your Responsibilities:

• Design, develop, and maintain backend data services using .NET and Azure
• Build and optimize ETL pipelines for integrating data from multiple sources
• Ensure seamless and reliable data flow from SQL Server to document generation (PDFs) and printing systems
• Manage large datasets and implement efficient storage solutions in Azure
• Collaborate with cross-functional engineers to ensure scalability, performance, and system efficiency
• Contribute to architectural decisions within the new cloud-based stack
   

Required Skills & Experience:

• 5+ years of strong commercial experience with .NET backend development
• Solid hands-on experience with Azure cloud infrastructure
• Deep expertise in SQL Server (performance tuning, complex queries, data modeling)
• Proven experience building and maintaining ETL processes
• Experience working with large datasets and designing scalable data solutions
• Strong problem-solving skills in backend data processing and system optimization

• Good communication skills and ability to work in a collaborative environment

   

 Nice to Have:

• Experience with document generation workflows
• Background in system modernization or legacy migration projects

• Understanding of distributed systems and performance optimization

   

👉 What we offer:

📈 Professional Growth opportunities:

• Ambitious goals and interesting projects;
• Regular & transparent performance review and feedback process;
• Possibility for both vertical or horizontal growth (in case you want to try a different path).

🎁 Benefits program

• 18 working days of fully paid vacation;
• Free tax reporting support by our Financial department;
• Help with individual entrepreneurs’ questions and accounting support;
• Financial support and additional days off for various occasions (e.g. marriage, childbirth, etc.);

😌 Comfortable Working conditions

• Flexible working hours;
• Provision of required equipment;
• Remote working model.
   

We are looking for a Senior Data Engineer. This is not a standard ETL role. You will work on a high-load system processing 10,000+ executions per minute, building scalable pipelines where AI and LLM logic are embedded directly into production data flows.

The role combines data engineering, backend thinking, infrastructure ownership, and real production AI integration.

What you will do:

• Design and maintain scalable data pipelines in Python on Google Cloud Platform
• Build and optimize AI-driven scoring flows using LLMs for real-time identity enrichment
• Work with BigQuery, Apache Spark, and Apache Iceberg for heavy data processing
• Maintain high-load orchestration with custom Python nodes and complex workflows
• Own deployment and release processes (CI/CD)
• Optimize PostgreSQL performance under heavy load
• Investigate incidents and resolve root causes permanently

• Use AI engineering tools such as Claude in daily development

   

Requirements:

• 4+ years of experience in Data Engineering / Backend Engineering
• Strong Python skills
• Commercial experience with production LLM integration (OpenAI / Anthropic / Gemini)
• Strong knowledge of GCP (Cloud Functions, IAM, Networking)
• Experience with BigQuery, Spark, Iceberg
• Good understanding of Kubernetes
• Experience with workflow orchestration tools (n8n is a strong plus)
• Strong practical knowledge of PostgreSQL

• English level B2+

   

What is important for us:

• Ownership mindset
• Fast learning ability
• Strong problem-solving approach
• Active AI usage in engineering work
• Focus on practical results over unnecessary complexity

Team Lead Python Data Engineer (Python)

Our client is an Israeli startup specializing in geodata.

We are looking for a Team Lead Python Data Engineer to lead the design and operation of large-scale data pipelines that generate property attributes from imagery using our internal AI models.

This role focuses on leading the development of distributed processing systems running on Kubernetes clusters and on-prem GPU infrastructure, capable of processing massive geospatial datasets at national scale.

You will work closely with AI engineers and SaaS platform teams to guide the development of robust pipelines that transform imagery into structured property intelligence used by the insurance and financial industries.

Responsibilities

• Design and build large-scale Python processing pipelines for satellite and street-level imagery

• Develop distributed workloads running on Kubernetes clusters

• Build and maintain orchestration workflows using Airflow

• Design and manage data storage and processing workflows using PostgreSQL

• Integrate large-scale AI inference pipelines running on GPU infrastructure

• Optimize processing performance for massive imagery datasets

• Improve observability, monitoring, and reliability of production pipelines

• Collaborate with AI engineers to support large-scale computer vision inference workflows

• Integrate pipelines with AWS-based services

Requirements

• 7+ years of Python engineering experience

• Strong experience designing distributed data pipelines or large-scale data processing systems

• Experience running workloads on Kubernetes

• Hands-on experience with Airflow or similar orchestration frameworks

• Experience processing large datasets (imagery, geospatial, or other high-volume data)

• Strong understanding of ETL architectures and distributed data systems

Nice to Have

• Experience working with satellite imagery, aerial imagery, or remote sensing datasets

• Experience with GPU-based inference pipelines

• Experience working with on-prem compute clusters

• Experience with C#

Our client is an Israeli startup specializing in geodata.

Our client is an Israeli startup specializing in geodata.

We are looking for a Senior Python Data Engineer to design and operate large-scale data pipelines that generate property attributes from imagery using our internal AI models.

This role focuses on building distributed processing systems running on Kubernetes clusters and on-prem GPU infrastructure, capable of processing massive geospatial datasets at national scale.

You will work closely with AI engineers and SaaS platform teams to build robust pipelines that transform imagery into structured property intelligence used by the insurance and financial industries.

Responsibilities

• Design and build large-scale Python processing pipelines for satellite and street-level imagery

• Develop distributed workloads running on Kubernetes clusters

• Build and maintain orchestration workflows using Airflow

• Design and manage data storage and processing workflows using PostgreSQL

• Integrate large-scale AI inference pipelines running on GPU infrastructure

• Optimize processing performance for massive imagery datasets

• Improve observability, monitoring, and reliability of production pipelines

• Collaborate with AI engineers to support large-scale computer vision inference workflows

• Integrate pipelines with AWS-based services

Requirements

• 7+ years of Python engineering experience

• Strong experience designing distributed data pipelines or large-scale data processing systems

• Experience running workloads on Kubernetes

• Hands-on experience with Airflow or similar orchestration frameworks

• Experience processing large datasets (imagery, geospatial, or other high-volume data)

• Strong understanding of ETL architectures and distributed data systems

Nice to Have

• Experience working with satellite imagery, aerial imagery, or remote sensing datasets

• Experience with GPU-based inference pipelines

• Experience working with on-prem compute clusters

• Experience with C#

Our client is an Israeli startup specializing in geodata.

About the Company

Established in 2004, ALLSTARSIT was founded with a clear vision: to enhance the landscape of global IT employment by bridging the gap between companies and skilled professionals. The core belief was that assembling a team shouldn't be hindered by geographical constraints. Fast forward to the present day, ALLSTARSIT stands as an international outstaffing service provider committed to change the way businesses recruit, compensate, and oversee top talent worldwide. 

With operational hubs scattered across Europe, Asia, and LATAM, and its headquarters situated in San Francisco, US, the company boasts a workforce of over 1,000 adept professionals. Spanning across more than 20 countries, ALLSTARSIT offers a diverse range of skilled employees across various verticals, including AI, cybersecurity, healthcare, fintech, telecom, media, and so on.

About the Project

The client’s company is revolutionizing the way new drugs and vaccines are approved for market by replacing manual processes with deep tech. Their core product, the project, is an AI-powered statistical analysis workspace designed to improve workflows and accelerate regulatory approval processes.
Accurate analysis of clinical research data is critical to helping millions of people receive safe and effective medical treatments faster. The project provides assurance that the data underpinning these analyses are of the highest integrity. By joining the client’s team, you can directly impact the speed at which new medications reach patients—many of whom may be your family or friends. You will also help drive the translation of meaningful ideas into beneficial products with the support of an inclusive and diverse group of highly talented professionals.
We are seeking a highly motivated and experienced Senior Data Engineer to join the client’s team.

Required skills:

• 3+ years of experience in Python development (or 1+ year of Python plus 2+ years in another language)
• 2+ years of experience in production data environments
• Strong experience with modern data engineering tools and libraries (e.g., Pandas, PySpark, SQLAlchemy)
• Hands-on experience with Databricks or other distributed data processing frameworks
• Proficiency in working with structured and semi-structured data from various sources (databases, APIs, files, etc.)
• Experience with Agile methodologies and tools
• Familiarity with data modeling, data warehousing, and performance optimization
• Excellent analytical and problem-solving skills
• Strong English communication skills, both written and verbal
• Team player with strong collaboration and interpersonal abilities

Advantages

• Experience with Databricks or similar platforms for large-scale data processing and analytics, as well as data orchestration tools and MLOps frameworks
• Experience delivering AI-ready datasets and knowledge of AI/ML frameworks
• Proficiency with regular expressions
• Experience with NoSQL databases (e.g., MongoDB)
• Familiarity with cloud services (AWS and/or Azure)
• Hands-on experience with Python testing and debugging tools such as PyTest
• Experience building and maintaining CI/CD pipelines
• Background in the pharmaceutical or life sciences industry
• Bachelor’s degree in Computer Science, Engineering, a related technical field, or equivalent practical experience

Scope of work:

• Design and implement robust, scalable data pipelines and workflows using modern data engineering frameworks
• Collaborate closely with Data Scientists, Analysts, Developers, and Product Managers to support data needs and model deployment
• Take ownership of data quality, data architecture, and production readiness across systems
• Build and optimize data extraction, transformation, and loading (ETL) processes across structured and unstructured datasets
• Develop reusable data processing components and libraries
• Troubleshoot data issues, performance bottlenecks, and maintain high data integrity across environments
• Contribute to the evolution of the client’s cloud-based data infrastructure
• Document data workflows and participate in the development and execution of test strategies for data systems

Looking for a Data Engineer to join the Dataforest team. If you are looking for a friendly team, a healthy working environment, and a flexible schedule ‒ you have found the right place to send your CV.

Skills requirements:
• 2+ years of experience with Python;
• 2+ years of experience as a Data Engineer;
• Experience with Pandas;
• Experience with SQL DB / NoSQL (Redis, Mongo, Elasticsearch) / BigQuery;
• Familiarity with Amazon Web Services;
• Knowledge of data algorithms and data structures is a MUST;
• Working with high volume tables 10m+.

Optional skills (as a plus):
• Experience with Spark (pyspark);
• Experience with Airflow;
• Experience with Kafka;
• Experience in statistics;
• Knowledge of DS and Machine learning algorithms..

Key responsibilities:
• Create ETL pipelines and data management solutions (API, Integration logic);
• Different data processing algorithms;
• Involvement in creation of forecasting, recommendation, and classification models.

We offer:

• Great networking opportunities with international clients, challenging tasks;

• Building interesting projects from scratch using new technologies;

• Personal and professional development opportunities;

• Competitive salary fixed in USD;

• Paid vacation and sick leaves;

• Flexible work schedule;

• Friendly working environment with minimal hierarchy;

• Team building activities, corporate events.

SKELAR — is a Ukrainian venture builder that creates international tech businesses. Together with co-founders, we assemble strong teams to succeed in global markets.

We are currently looking for an Infrastructure engineer to join our partner company TENTENS Tech. In this role, you will manage and scale a highly available database infrastructure handling up to 2 PB of data and 100,000 operations per second. You’ll be responsible for database architecture decisions, performance optimization, and reliability improvements, while closely collaborating with DevOps, Security, and Software Engineering teams.

TENTENS Tech is a Ukrainian IT company that develops platforms in the social discovery domain. The TENTENS Tech team has successfully launched dozens of platforms used by millions of people worldwide. Their slogan, “We don’t think limits,” reflects both the company’s strategic mindset and the team’s drive to always move far beyond the horizon.

Strategic challenges and objectives:

• Database health monitoring and troubleshooting.
• Work with massive amounts of data.

Key areas of responsibility:

• Collaborate with engineers, DBAs, and DevOps teams on technical issues.
• Design and develop infrastructure on GCP.
• Provide support to developers and QAs as required.
• Maintain system monitoring of the database servers. Slow query reporting.
• Participate in database restructuring and management.
• Work on schema design and data modeling.

Technical requirements:

• Proven experience as a Site Reliability Engineer on GCP or other cloud platforms.
• Skilled in infrastructure design and development.
• Experience with administering MySQL server.
• Basic performance, query, and index optimization.
• Confident knowledge of MySQL backup solutions.
• Good understanding of monitoring requirements.
• Good understanding of replication principles.
• Comfortable with collaborative tools, such as Slack, wikis, Subversion, and basic ticket tracking systems (YouTrack, Jira).

Non-technical requirements:

• Fast learner and creative thinker with strong problem-solving skills.
• Effective team member with a high level of motivation and ability to work with little supervision.
• Dynamic self-starter with high attention to detail, highly responsible and reliable.

Desirable skills:

• Previous work experience with Python, Golang, Shell, or other programming languages.
• Previous work experience with relational databases, such as Oracle, PostgreSQL, and NoSQL DBs: MongoDB, Elasticsearch, Redis, etc.
• Good understanding of load balancers, DNS, networking, and/or client-side drivers.

By choosing us you get:

• Opportunity to work with a multi-million audience.
• Career growth and professional development with various internal training and seminars, access to an extensive book library, chance to participate in key IT industry events worldwide (attending the conferences).
• Work in a great team. We pay special attention to the recruitment and development of talent. All the members of our team are young, active, and highly motivated for creative problem-solving.
• Employee wellness program, which includes running sessions, football, basketball, and other sports. The cost of sports activities is covered by the company. In-house doctor support is also available on demand.
• Health insurance is available for all employees.

Let's build the next big everything together!

Transcenda is a global provider of design and engineering services. We put people first and strive to be agents of change by building a better future through technology. We are dedicated to empowering organizations to rapidly scale, digitally transform, and bring new products to market.

Recognized by Newsweek as one of America’s greatest workplaces of 2025, Transcenda is home to 200+ engineers, designers, analysts, and advisors solving complex business challenges through technology. By approaching our work through a variety of cultures and perspectives, we take calculated risks to design and develop innovative solutions that will have a positive impact tomorrow.

Interesting Facts:

• Over 200 team members
• Fully remote — we let people work where they work best.
• We work with clients who value our opinion and thought leadership, and where we can make a meaningful contribution to architectural decisions, engineering decisions, and product decisions.
• We have a strong social agenda and promote diversity and inclusion, and participate in a variety of charity initiatives throughout the year.
• We have fun team-building activities.
• Since we are rapidly growing, the ability to grow and advance your career is available and at a fairly quick rate.

Must Haves:

• Strong experience with Python, Java, or other programming languages
• Advanced knowledge of SQL, including complex queries, query modularization, and optimization for performance and readability
• Familiarity with the modern data stack and cloud-native data platforms, such as Snowflake, BigQuery, or Amazon Redshift
• Hands-on experience with dbt (data build tool) for data modeling and transformations
• Experience with data orchestration tools, such as Airflow or Dagster

‍

Nice to Have:

• Experience with GitOps, continuous delivery for data pipelines
• Experience with Infrastructure-as-Code tooling (Terraform)

‍

Key Responsibilities:

• Design and build a data platform that standardizes data practices across multiple internal teams
• Support the entire data lifecycle
• Build and maintain integrations across data processing layers, including ingestion, orchestration, transformation, and consumption
• Collaborate closely with cross-functional teams to understand data needs and ensure the platform delivers value
• Document architectures, solutions, and integrations to promote best practices, maintainability, and usability

Since 2001, FutureLog has been creating and developing digital procure-to-pay solutions for the hospitality and gastronomy industries.  We are a world-class procurement management platform serving over 10,000 clients across 20+ countries, delivering near real-time reporting with complex data models and advanced permission structures. 

We are looking for a highly skilled Data Engineer (Azure) to design and build the next generation of our high-load data platform. 

The primary goal of this role is to architect and implement a modern, scalable data pipeline based on Microsoft Fabric and Azure technologies (or other relevant solutions) to significantly enhance the performance, scalability, and speed of our current Power BI environment, which is built on MS SQL Managed Instance and SQL-based queries. 

This is a high-impact engineering role focused on platform modernization and long-term data architecture evolution. 

Key Responsibilities 

• Design and implement next-generation high-load data pipelines using Microsoft Fabric and Azure services 
• Optimize and modernize the current MS SQL Managed Instance-based architecture 
• Improve Power BI performance, scalability, and near real-time capabilities 
• Design and implement scalable Lakehouse / Data Warehouse architectures 
• Build and optimize ETL / ELT processes 
• Ensure data quality, reliability, monitoring, and governance 
• Design data models that support complex reporting and permission structures 
• Collaborate closely with BI engineers, product managers, and infrastructure teams 
• Contribute to architectural decisions and technical roadmap planning 
• Support migration from legacy SQL-based architecture to modern Azure-based solutions 
  
  
  Must-Have Skills & Experience  
• Strong hands-on experience with Azure data services including Microsoft Fabric, Azure Data Factory, and Event Hub 
• Deep expertise in designing and optimizing high-load and distributed data pipelines, including Apache Spark processing 
• Strong experience with MS SQL and PostgreSQL, including performance tuning and query optimization 
• Experience designing modern Lakehouse, Data Warehouse, and hybrid data architectures using Fabric or similar platforms 
• Hands-on experience with ETL / ELT development using orchestration and transformation tools such as dbt; experience with Apache Airflow is highly desirable 
• Strong practical knowledge of CDC implementation using tools such as Debezium and integration with streaming or near real-time ingestion pipelines 
• Solid understanding of Power BI architecture, including performance optimization, Gateway configuration, embedding scenarios, and Row-Level Security (custom and Active Directory-based) 
• Experience working with large-scale datasets and complex access control and permission models 
• Experience deploying and managing containerized data workloads using Docker and Kubernetes in cloud-native environments 
• Strong analytical thinking, data modeling, and system design capabilities 

• Fluent English (written and verbal communication) 

   

  Nice to Have 

• Experience migrating legacy SQL environments to modern Azure-based platforms 
• Experience with near real-time or streaming data processing 
• Knowledge of CI/CD for data engineering workflows 
• Experience working in high-scale SaaS platforms 
  
  What We Offer 
• Opportunity to build and shape a next-generation Azure data platform 
• High ownership and architectural impact 
• Work on a global system serving thousands of enterprise customers 
• Collaboration with strong BI, product, and engineering teams 
• A dynamic and international working environment 
  20 working days of paid holidays. 
• Paid sick leaves. 
• All necessary equipment for work. 
• Flexible working hours. 

• 300 EUR Wellness compensation annually (can be used for health insurance, education, gym, sports activities, etc.). 

   

Main Responsibilities:

Data Engineer is responsible for helping select, deploy, and manage the systems and infrastructure required of a data processing pipeline to support customer requirements.

You will work on cutting-edge cloud technologies, including Microsoft Fabric, Azure Synapse Analytics, Apache Spark, Data Lake, Data Bricks, Data Factory, Cosmos DB, HD Insights, Stream Analytics, Event Grid in the implementation projects for corporate clients all over EU, CIS, United Kingdom, Middle East.

Our ideal candidate is a professional passionated with technologies, a curious and self-motivated person.

Responsibilities revolve around DevOps and include implementing ETL pipelines, monitoring/maintaining data pipeline performance, model optimization

Mandatory Requirements:

– 3+ years of experience, ideally within a Data Engineer role.

– understanding of data modeling, data warehousing concepts, and ETL processes

– 2+ years of experience with Azure Cloud technologies

– experience in distributed computing principles and familiarity with key architectures, broad experience across a set of data stores (Azure Data Lake Store, Azure Synapse Analytics, Apache Spark, Azure Data Factory)

– Understanding of landing, staging area, data cleansing, data profiling, data security and data architecture concepts (DWH, Data Lake, Delta Lake/Lakehouse, Datamart)

– SQL-skills

– communication and interpersonal skills

– English —В2

Will be beneficial if a candidate has experience in SQL migration from on-premises to cloud, data modernization and migration, advanced analytics projects, and/or professional certification in data&analytics.

We offer:

– professional growth and international certification

– free of charge technical and business trainings and the best bootcamps (worldwide, including HQ Microsoft- Redmond courses)

– innovative data & analytics projects, practical experience with cutting-edge Azure data&analytics technologies at various customers’ projects

– great compensation and individual bonus remuneration

– medical insurance

– long-term employment

– ondividual development plan