Jobs Data Engineer

About the role and product:
We are looking for an experienced Data Engineer to join the Data &AI team delivering enterprise-grade data platform capabilities. The role centres on building Python-based ETL pipelines across a Medallion architecture, developing and operationalising data quality rules using both Python and the Informatica platform (IDQ, EDC, Axon), and ensuring robust governance integration. 

Responsibilities:
- Design, build, and maintain Python-based ETL pipelines across Bronze, Silver, and Gold layers following the Medallion architecture pattern.
- Develop and operationalise data quality (DQ) rules in Python, covering validity, completeness, consistency, uniqueness, accuracy, and timeliness dimensions.
- Build and maintain DQ rules using Informatica IDQ 10.5 on-premises, including mapplet design, profile configuration, and scorecard setup.
- Support data cataloguing and lineage activities using Informatica EDC, including schema scanning, data classification, and lineage mapping.
- Configure and maintain Informatica Axon for governance workflows, business glossary management, policy enforcement, and surfacing DQ scores to stakeholders.
- Develop cross-system DQ checks including referential integrity, reconciliation, and entity deduplication as scheduled Python jobs.
- Integrate DQ outputs into Power BI dashboards, contributing to the DQ Index Aggregation layer that unifies IDQ scorecard and Python-based scores.
- Support the IDQ–Axon integration, including Axon Agent configuration and DQ metric propagation into Axon dashboards.
- Contribute to the Python DQ framework package, maintaining modular, testable, and well-documented code with comprehensive unit test coverage.
- Support Talend-based ingestion processes at the Bronze layer, ensuring schema conformance and completeness checks.
- Participate in root-cause analysis of DQ failures using the programme’s three-tier classification taxonomy.

Requirements:
- Strong Python development skills, including experience with data processing libraries (pandas, PySpark) and testing frameworks (pytest).
- Hands-on experience with Informatica IDQ 10.5 on-premises: Developer Tool, mapplet design, profiles, scorecards, and expression-based DQ rules.
- Working knowledge of Informatica EDC for schema scanning, data lineage, and data classification.
- Experience with Informatica Axon for governance, business glossary management, HITL steward workflows, and DQ score surfacing.
- Solid understanding of the Medallion architecture (Bronze / Silver / Gold) and data lake design patterns.
- Working knowledge of SQL and relational databases for data validation and reconciliation.
- Experience building production-grade Python ETL pipelines with appropriate logging, error handling, and modular design.
- Experience with CI/CD practices for data pipelines and version control (Git).

Nice to have:
- Familiarity with Talend for data ingestion workflows.
- Exposure to AI/ML techniques for data quality: anomaly detection, entity resolution, DQ score aggregation.
- Experience generating or consuming Informatica IMX-format XML programmatically.
- Knowledge of Power BI for building or maintaining DQ score dashboards.
- Understanding of data governance frameworks, stewardship models, and regulatory reporting requirements.
- Experience with the Informatica IDQ–Axon integration bridge (Axon Agent setup and configuration).

The client offers:
- 24 working days of annual leave.

- 10 sick days.

- All official Ukrainian public holidays are days off.

- All necessary equipment for work is provided by the company.

- Medical insurance after the probationary period (3 months).

- Monthly budget to cover English classes, sports, and psychological support.

- All accounting and payroll administration are handled by the company; salary is paid net in UAH

Description

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.

OU’s: Currently, Nuero, Cardio, Diabetes is the OU that HDP 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

As a System Engineer within the Company Research & Systems Engineering team, you will have the opportunity to work on cloud-based solutions with a strong focus on AWS, Data Engineering, and scalable data platforms. You will collaborate with cross-functional engineering teams to design, develop, integrate, and maintain reliable cloud-native systems and data workflows.

In this role, you will contribute to building and evolving AWS-based architectures, data processing pipelines, and integrations across distributed systems. You will develop a strong understanding of end-to-end system architecture, data flows, infrastructure, and operational requirements, helping to drive technical implementation and delivery throughout the software development lifecycle.

You will work closely with software engineers, data engineers, architects, and other stakeholders to ensure that solutions are scalable, secure, maintainable, and aligned with both technical and business requirements.

• 3+ years of experience in System Engineering, Software Engineering, Cloud Engineering, Data Engineering, or a related technical role.
• Strong software development experience with Python.
• Hands-on experience designing, developing, or supporting solutions on AWS.
• Experience with data engineering concepts and technologies, including data ingestion, ETL/ELT, transformation, validation, and data processing pipelines.
• Strong SQL skills and experience working with relational and/or NoSQL databases.
• Experience with REST APIs, service integrations, and distributed application architectures.
• Understanding of cloud-native architecture principles and modern software development practices.
• Experience troubleshooting applications and distributed cloud systems and performing root cause analysis.
• Experience with Git and modern CI/CD development workflows.
• Strong analytical and problem-solving skills with the ability to understand complex systems and data flows.
• Ability to work effectively with software, data, cloud, and machine learning engineering teams.
• BA/BS in Computer Science, Software Engineering, Information Technology, or a related technical field, or equivalent practical experience.

Preferred Qualifications

• Experience with AWS data services such as S3, Glue, Athena, EMR, or similar technologies.
• Experience with Amazon SageMaker and machine learning development or deployment workflows.
• Experience with Infrastructure as Code using AWS CloudFormation, Terraform, or AWS CDK.
• Experience with AWS monitoring and observability services such as CloudWatch and CloudTrail.
• Experience working in Agile/Scrum development environments.

Job responsibilities

• Work with engineering and cross-functional stakeholders to gather, analyze, clarify, and document business, functional, and non-functional requirements, translating them into clear system and technical requirements.
• Define system requirements, interfaces, data flows, integration requirements, acceptance criteria, and technical constraints for cloud-based software components, data platforms, and integrations.
• Maintain requirements throughout the development lifecycle, ensuring traceability between business needs, system requirements, technical design, implementation, and validation.
• Identify gaps, dependencies, assumptions, and potential technical risks in requirements and work with stakeholders to resolve them before and during implementation.
• Design and contribute to scalable AWS-based architectures supporting data ingestion, processing, transformation, storage, and distribution.
• Analyze data and system behavior to support architecture, implementation, performance, and product decisions.
• Collaborate with Data Engineering, Software Engineering, Cloud Engineering, DevOps, and Architecture teams to design and integrate end-to-end cloud solutions.
• Support operational monitoring, logging, alerting, and troubleshooting of cloud applications and data processing workflows.
• Contribute to system architecture and technical design discussions, including scalability, reliability, security, performance, and cost considerations.
• Participate in technical and requirements reviews to ensure solutions meet defined requirements, engineering standards, cloud best practices, and established software development processes.
• Support continuous improvement of cloud infrastructure, data pipelines, deployment processes, requirements management, and engineering practices throughout the software development lifecycle.

Remote | Full-time | $3,000–4,000/month

We are looking for an experienced DevOps Engineer (Middle+/Senior) to take ownership of the infrastructure behind multiple production environments.

This is a hands-on position with responsibility for production stability, deployments, servers, backups, infrastructure security, troubleshooting, and incident response.

Our infrastructure currently includes approximately 20 separate production broker environments plus core/database infrastructure.

We are looking for someone who can first learn the existing infrastructure and deployment processes and then gradually take full ownership of them.

Environment

Our current environment includes technologies and infrastructure such as:

• Linux / AlmaLinux
• Nginx
• Docker
• GitHub
• CI/CD
• Cloudflare
• Multiple production servers
• Central/core database infrastructure
• CRM applications
• Web-based trading platforms
• REST APIs
• WebSockets / real-time services
• Third-party data/API providers

The exact existing infrastructure will be reviewed during onboarding.

Responsibilities

You will be responsible for the reliability and operation of production infrastructure.

This includes:

• Maintain approximately 20 production environments
• Maintain core/database infrastructure
• Provision new production servers from scratch
• Configure environments for new brands/sub-brands
• Deploy applications and infrastructure changes
• Maintain and improve CI/CD processes
• Manage application and infrastructure configuration
• Configure and maintain Nginx/reverse proxy infrastructure
• Work with Docker/containerized services
• Manage GitHub-related deployment infrastructure, access, keys, and secrets
• Maintain SSL certificates, domains, DNS, and Cloudflare-related infrastructure when required
• Perform server and application migrations
• Move environments between servers when required
• Maintain database infrastructure
• Manage database backups and restoration procedures
• Implement and verify automated backups
• Ensure that backups can actually be restored when needed
• Maintain disaster-recovery procedures
• Monitor server health, CPU, RAM, disk usage, services, and application availability
• Maintain and improve existing monitoring and alerts
• Troubleshoot production incidents
• Investigate infrastructure, network, API, service, and real-time data issues
• Investigate cases where external/internal APIs or data sources stop functioning correctly
• Work with external hosting and infrastructure providers when required
• Maintain infrastructure security
• Manage SSH access, permissions, firewall rules, secrets, and production access
• Perform safe production restarts and updates
• Maintain rollback procedures
• Minimize downtime during deployments and infrastructure changes
• Document servers, services, environments, domains, dependencies, deployment processes, backup procedures, and recovery procedures
• Work closely with Full-Stack Developers and QA

Production ownership

This position requires real ownership of production infrastructure.

We are not looking for someone who only executes predefined commands.

During the onboarding period, you will receive information about the existing environments and infrastructure.

As you become familiar with the system, we expect you to independently:

• Diagnose infrastructure problems
• Determine root causes
• Decide on appropriate technical actions
• Restore affected services
• Coordinate with developers when the issue is application-related
• Verify production health after changes
• Document important incidents and infrastructure changes
• Identify potential infrastructure risks before they become production incidents

Requirements

• 4+ years of commercial DevOps/System Engineering experience or equivalent strong hands-on experience
• Strong Linux administration skills
• Production experience with Linux-based environments
• Strong Nginx knowledge
• Docker experience
• CI/CD experience
• Git/GitHub experience
• Experience managing multiple production environments
• Experience provisioning production servers
• Experience with database infrastructure, backups, and recovery
• Understanding of networking, DNS, SSL/TLS, HTTP/HTTPS, reverse proxies, and firewalls
• Experience troubleshooting production systems
• Experience with monitoring and alerting
• Understanding of infrastructure and application security
• Experience managing SSH access, secrets, permissions, and deployment credentials
• Ability to analyze logs and diagnose application/infrastructure failures
• Experience working with third-party infrastructure/API providers
• Ability to create clear infrastructure documentation
• Ability to work independently after onboarding
• English — Intermediate or higher

Experience with AlmaLinux/RHEL-compatible environments is a strong plus.

Experience with trading or FinTech infrastructure is not required.

Backup and recovery

We expect the DevOps Engineer to maintain a reliable backup and recovery process.

This means not only creating backups but also knowing:

• What is backed up
• How frequently backups are created
• Where they are stored
• How they can be restored
• How a failed production environment can be rebuilt
• How production can be recovered if a server becomes unavailable

Incident response

This is the only position in the team that includes responsibility for urgent production incidents outside standard working hours.

Production incidents outside working hours are not expected to be routine, but when a critical production service becomes unavailable, the DevOps Engineer must be reachable and able to respond.

We expect:

• Reliable availability during normal working hours
• Reasonable emergency availability outside working hours
• Fast acknowledgement of critical production incidents
• Ability to access and investigate production remotely when necessary
• Clear communication during an incident
• Notification to the team if you will be unavailable for a known period

The exact incident-response/on-call process will be agreed with the successful candidate.

First 1–3 months

We understand that the infrastructure contains multiple environments and cannot be fully learned in several days.

The initial period will focus on:

• Understanding existing infrastructure
• Mapping production environments
• Understanding deployments
• Understanding database and service dependencies
• Reviewing access and security
• Reviewing monitoring
• Reviewing backup processes
• Creating/updating infrastructure documentation
• Identifying infrastructure risks and areas for improvement

After the onboarding period, we expect you to be able to manage standard infrastructure operations and troubleshoot most production issues independently.

Working conditions

• Fully remote
• Full-time
• Monday–Friday
• Standard working hours: 09:00–18:00 GMT+3 / 10:00–19:00 GMT+4
• Emergency production availability outside working hours
• Probation/onboarding period: 1–3 months
• Compensation: $3,000–4,000/month, depending on experience and technical level
• Higher compensation may be considered for an exceptionally strong candidate with significant production ownership experience
• Long-term cooperation
• English: Intermediate or higher

What is important to us

Reliability and communication are critical for this role.

We expect the DevOps Engineer to:

• Be reachable during agreed working hours
• Respond to critical infrastructure incidents
• Notify the team about planned periods of unavailability
• Take ownership of production problems
• Investigate root causes rather than only restart services
• Communicate clearly with developers, QA, and the Project Manager
• Document important infrastructure knowledge
• Proactively identify risks
• Gradually reduce dependency on undocumented knowledge held by individual team members

Our goal is to build an infrastructure process where production knowledge, access, deployments, backups, and recovery procedures are documented and are not dependent on one person's memory.

Data Engineer / Migration Specialist (SAP BW to Databricks) 📊🚀
 

ZentixSoft is looking for a Senior Data Engineer! 🚀
 

Format: Full-Time Outstaffing, long-term engagement starting Dec 2026 / Jan 2027 through Q1 2028 (EU-based candidates).
 

💡 Why ZentixSoft? 
💸 Salary Review: A structured system of compensation reviews aligned with your engineering growth. 
⚖️ Work-Life Balance: Sustainable workflows with no senseless overtime, helping you keep your resource fully charged.
 🦾 Trust and Transparency: Zero micromanagement and no invasive time-trackers—we fully trust your professional autonomy. 
🎁 Gifts & Culture: Corporate gifts for holidays, birthdays, and a true team atmosphere where your voice always matters.
 

Our Perfect Match: 
1️⃣ Databricks Expertise: Strong hands-on experience with Databricks, general BI, data platform architecture, and advanced data modeling.
 2️⃣ SAP BW Context: solid background in SAP BW sufficient to analyze existing BW structures, models, and business logic for migration. 
3️⃣ Enterprise Migration: Proven track record in large-scale data migration/modernization projects (ideally leveraging LLM-powered code translation or migration tools). 
4️⃣ Cloud & Domain: Cloud experience with AWS (or comparable platforms); exposure to enterprise Finance domain processes is a big plus. 
5️⃣ Location & Communication: Based in EU countries with English proficiency at B2/C1 level for smooth enterprise stakeholder communication.
 

Project Details: 
⏳ Duration: Dec/Jan start until end of Q1 2028 (Full-time). 

Lead Data Engineer 

Requirements:

- 5+ years of experience in Data Engineering, Analytics Engineering, or a related field

- Strong SQL skills and experience with complex data transformations

- Hands-on experience with modern data platforms such as BigQuery, Databricks, or Snowflake

- Strong experience with ETL/ELT, data orchestration, and data warehousing/lakehouse solutions

- Experience with Airflow, dbt, Spark, and streaming technologies such as Kafka or Kinesis

- Proficiency in Python

- Strong understanding of data modeling and analytics-ready datasets

- Experience working with stakeholders to define requirements and deliver data solutions

- Experience with data quality, metadata, and scalable data pipelines

- Strong English communication skills

- Ability to work with US overlap

Nice to have:

- Data governance, lineage, or metadata management

- Experience with cross-domain data such as customer, product, or transaction data

- Financial services or other data-intensive industry experience

- Experience with data platform migration or evolution toward Databricks

- Dimensional modeling, data marts, and reusable datasets

- Airflow / Cloud Composer

Company offers:

- Long-term employment with possibilities for professional growth

- Fully remote work

- Reasonably flexible schedule

- 15 days of paid vacation

- Regular performance reviews

Join the Dataforest Team!

We are actively expanding our team and looking for strong new talent to join our ranks. If you are a Data Engineer seeking a friendly team, a healthy working environment, and a flexible schedule — you have found the right place to send your CV!

You'll be a great fit if you have:

- 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;
- Experience with Kafka;
- Knowledge of data algorithms and data structures is a MUST;
- Working with high volume tables 10m+.

What you'll do:

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

Would be a plus:

- Experience with Spark (pyspark);
- Experience with Airflow;
- Experience in statistics;
- Knowledge of DS and Machine learning algorithms.

We ensure your growth with:

- 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.

Level: Senior Engagement: Long-term contract Location: Europe (EU / EEA / UK), remote Working hours: EU business hours, shifted 2–3 hours later to ensure daily overlap with US West Coast (PST/PDT) mornings

About the Client

Our client is a leading enterprise data platform company building an open, high-performance data lakehouse for AI and analytical workloads. The platform combines an intelligent SQL query engine, an AI-ready semantic layer, and an open catalog built on Apache Iceberg — enabling Fortune 500 companies across finance, energy, manufacturing, and logistics to unify, query, and govern data at massive scale across cloud and on-premise sources.

About the Role

We are looking for a Senior SDET to lead the design of automated test frameworks and testing strategy for a large-scale distributed data platform. You will own the quality of the query engine, connectivity layer, and backend services end-to-end — from framework architecture through CI/CD infrastructure across all major clouds — and mentor middle engineers on the team.

This is a data-heavy, backend-focused role. We are not looking for web/UI QA engineers — the work centers on validating distributed query execution, data correctness at scale, connectivity drivers, and backend microservices.

Responsibilities

• Architect, design, and evolve automated test frameworks in Python / pytest for backend services, REST APIs, and distributed data components.
• Define testing strategy for new features and platform components — coverage, risk assessment, and quality gates.
• Own end-to-end, integration, performance, and regression testing covering SQL query execution, data correctness at scale, and platform APIs.
• Lead performance and load testing efforts with JMeter, including workloads over JDBC / ODBC / Arrow Flight drivers.
• Design and validate large-scale data testing scenarios — query plans, result correctness across heterogeneous data sources, metadata consistency, and behavior under high concurrency.
• Own CI/CD test pipelines in Jenkins — architect, maintain, and continuously improve.
• Provision and manage test environments in Kubernetes (GKE / EKS / AKS) across GCP, AWS, and Azure using Docker; drive automation and reproducibility.
• Investigate complex, cross-layer failures and drive root-cause analysis with engineering.
• Mentor middle SDETs, review test designs, and set quality standards across the team.
• Partner with US-based development leads on shift-left practices, testability, and release readiness.

Required Qualifications

• Education: B.S. or M.S. in Computer Science, Computer Engineering, or a related technical field.
• Programming: Strong proficiency in Python, including pytest, with deep understanding of OOP, software design principles, and test framework architecture.
• SQL & Data: Advanced SQL skills and strong understanding of relational and analytical data systems, including query execution internals.
• Data-intensive testing experience: Demonstrated experience testing data-intensive systems — query engines, ETL/ELT pipelines, streaming platforms, or analytical databases. Candidates with only web/UI QA backgrounds are not a fit.
• Testing experience: 5+ years in backend/system test automation, with demonstrated ownership of test strategy and infrastructure.
• CI/CD & DevOps: Solid experience architecting and maintaining Jenkins pipelines and test environments.
• Containers & Orchestration: Strong working knowledge of Docker and Kubernetes (running workloads, debugging pods, deploying complex environments).
• Cloud: Hands-on experience with at least one major cloud (GCP, AWS, or Azure); exposure to more than one is a strong plus.
• Version Control: Confident with Git / GitHub workflows and code review practices.
• English: Upper-Intermediate or higher (B2+) — daily written and verbal communication with a US-based engineering team.
• Availability: Able to work EU hours with a 2–3 hour shift toward US West Coast time to ensure daily overlap with the client team.
• Leadership: Prior experience mentoring engineers, defining test strategy, or leading a QA/SDET function.

Desired Skills

• Deep experience testing REST APIs and backend microservices at scale.
• Hands-on with distributed computing frameworks (e.g., Apache Spark, Kafka) and MPP SQL query engines (e.g., Presto, Trino, or similar).
• Strong understanding of modern data lakehouse concepts, open table formats (Apache Iceberg), and data warehousing.
• Experience with data connectivity drivers: JDBC, ODBC, Arrow Flight.
• Performance testing with JMeter or comparable load-testing tools at production scale.
• Kubernetes on managed services (GKE / EKS / AKS) and multi-cloud exposure.
• IaC tools such as Terraform.
• Deep understanding of query plan generation, query acceleration / materializations, and metadata integrity in distributed data systems.
• Prior experience leading a QA/SDET function in a data-platform or database engineering environment.
  Please note: We can consider only candidates currently residing in the EU, EEA, or the UK.

Level: Middle Engagement: Long-term contract Location: Europe (EU / EEA / UK), remote Working hours: EU business hours, shifted 2–3 hours later to ensure daily overlap with US West Coast (PST/PDT) mornings

About the Client

Our client is a leading enterprise data platform company building an open, high-performance data lakehouse for AI and analytical workloads. The platform combines an intelligent SQL query engine, an AI-ready semantic layer, and an open catalog built on Apache Iceberg — enabling Fortune 500 companies across finance, energy, manufacturing, and logistics to unify, query, and govern data at massive scale across cloud and on-premise sources.

About the Role

We are looking for a Middle-level SDET to design and maintain automated tests for a large-scale distributed data platform. You will validate the correctness, performance, and reliability of the query engine, connectivity layer, and backend services across all major clouds.

This is a data-heavy, backend-focused role. We are not looking for web/UI QA engineers — the work centers on validating distributed query execution, data correctness at scale, connectivity drivers, and backend microservices.

Responsibilities

• Develop and maintain automated tests in Python / pytest for backend services, REST APIs, and distributed data components.
• Write end-to-end, integration, and regression tests covering SQL query execution, data correctness, and platform APIs.
• Support performance and load testing with JMeter, including workloads over JDBC / ODBC / Arrow Flight drivers.
• Validate data-intensive scenarios — query plans, result correctness across data sources, metadata consistency, and behavior under concurrency.
• Contribute to CI/CD test pipelines in Jenkins — configure, maintain, and troubleshoot.
• Provision and manage test environments in Kubernetes (GKE / EKS / AKS) across GCP, AWS, and Azure using Docker.
• Investigate failures across the stack — query engine, distributed services, drivers, infrastructure — and drive them to resolution with engineering.
• Collaborate with US-based developers on testability and quality gates.

Required Qualifications

• Education: B.S. or M.S. in Computer Science, Computer Engineering, or a related technical field.
• Programming: Strong proficiency in Python, including pytest, with a solid grasp of OOP and software design principles.
• SQL & Data: Strong SQL skills and solid understanding of how relational and analytical data systems work.
• Data-intensive testing experience: Hands-on experience testing data-intensive systems — query engines, ETL/ELT pipelines, streaming platforms, or analytical databases. Candidates with only web/UI QA backgrounds are not a fit.
• Testing experience: 3+ years in backend/system test automation or SDET roles.
• CI/CD & DevOps basics: Practical experience with Jenkins pipelines and deploying/maintaining test environments.
• Containers: Working knowledge of Docker and basic Kubernetes (running workloads, debugging pods, kubectl fluency).
• Cloud: Comfortable operating in at least one major cloud (GCP, AWS, or Azure).
• Version Control: Confident with Git / GitHub workflows.
• English: Upper-Intermediate or higher (B2+) — daily written and verbal communication with a US-based engineering team.
• Availability: Able to work EU hours with a 2–3 hour shift toward US West Coast time to ensure daily overlap with the client team.

Desired Skills

• Experience testing REST APIs and backend microservices at scale.
• Familiarity with distributed computing frameworks (e.g., Apache Spark, Kafka) and MPP SQL query engines (e.g., Presto, Trino, or similar).
• Understanding of modern data lakehouse concepts, open table formats (Apache Iceberg), and data warehousing.
• Experience with data connectivity drivers: JDBC, ODBC, Arrow Flight.
• Performance testing with JMeter or comparable load-testing tools.
• Kubernetes on managed services (GKE / EKS / AKS) and multi-cloud exposure.
• IaC tools such as Terraform.
• Understanding of query plan generation, query acceleration / materializations, and metadata integrity in distributed data systems.
  Please note: We can consider only candidates currently residing in the EU, EEA, or the UK

Level: Senior Engagement: Long-term contract Location: Europe (EU / EEA / UK), remote Working hours: EU business hours, shifted 2–3 hours later to ensure daily overlap with US West Coast (PST/PDT) mornings

About the Client

Our client is a leading enterprise data platform company building an open, high-performance data lakehouse for AI and analytical workloads. The platform combines an intelligent SQL query engine, an AI-ready semantic layer, and an open catalog built on Apache Iceberg — enabling Fortune 500 companies across finance, energy, manufacturing, and logistics to unify, query, and govern data at massive scale across cloud and on-premise sources.

About the Role

We are looking for a Senior Software Engineer to design, build, and own significant components of the core query engine of a large-scale distributed data platform. You will lead work across query planning, optimization, and execution — driving architectural decisions, mentoring middle engineers, and pushing the platform's performance and scalability boundaries across all major clouds.

This is a systems-level, backend engineering role focused on distributed data processing internals — not application development or CRUD services.

Responsibilities

• Architect, design, and implement significant components of the query engine — planner, optimizer, execution operators, memory management, and data access layers.
• Write and review high-quality, performance-critical code in Java and/or C++.
• Own end-to-end delivery of features from technical design through production rollout.
• Drive performance optimization work — profiling, benchmarking, and eliminating bottlenecks in latency- and throughput-sensitive paths.
• Integrate deeply with columnar formats, open table formats, and connectivity drivers.
• Mentor middle engineers, lead code reviews, and set technical standards for the team.
• Contribute to CI/CD architecture and quality processes across Jenkins, containerization, and multi-cloud deployment (GCP, AWS, Azure via Kubernetes / Docker).
• Debug complex, cross-layer issues spanning query planning, distributed execution, memory management, and I/O.
• Partner with US-based engineering leads on design reviews, architectural decisions, and roadmap execution.

Required Qualifications

• Education: B.S. or M.S. in Computer Science, Computer Engineering, or a related technical field.
• Programming: Strong proficiency in Java or C++, with deep understanding of OOP, systems design, memory management, and concurrency. Candidates strong in both are especially valued.
• SQL & Data: Advanced SQL skills and strong understanding of query execution internals — planning, optimization, and operator implementation.
• Data processing systems experience: Demonstrated experience building or extending data processing systems — query engines, distributed databases, ETL/ELT frameworks, or analytical platforms.
• Engineering experience: 5+ years in backend/systems software engineering, with a track record of owning significant components.
• CI/CD & DevOps: Solid experience with Jenkins and modern engineering workflows.
• Containers & Orchestration: Strong working knowledge of Docker and Kubernetes.
• Cloud: Hands-on experience with at least one major cloud (GCP, AWS, or Azure); exposure to more than one is a strong plus.
• Version Control: Confident with Git / GitHub workflows and rigorous code review practices.
• English: Upper-Intermediate or higher (B2+) — daily written and verbal communication with a US-based engineering team.
• Availability: Able to work EU hours with a 2–3 hour shift toward US West Coast time to ensure daily overlap with the client team.
• Leadership: Prior experience mentoring engineers, leading technical designs, or owning components end-to-end.

Desired Skills

• Deep experience with Apache Arrow (columnar in-memory format).
• Hands-on experience with Apache Calcite (SQL parsing, planning, optimization framework).
• Experience with Gandiva or LLVM-based expression compilation and code generation.
• Experience with open table formats — Apache Iceberg, Delta Lake, or Hudi.
• Deep familiarity with distributed computing frameworks (e.g., Apache Spark, Kafka) and MPP SQL query engines (e.g., Presto, Trino, or similar).
• Deep understanding of query planning, optimization (cost-based, rule-based), and execution internals.
• Experience with data connectivity drivers: JDBC, ODBC, Arrow Flight.
• Kubernetes on managed services (GKE / EKS / AKS) and multi-cloud exposure.
• IaC tools such as Terraform.
• Track record of performance optimization at the systems level — profiling, vectorization, cache/memory-conscious design.
• Prior experience contributing to open-source data infrastructure projects.
  Please note: We can consider only candidates currently residing in the EU, EEA, or the UK

Level: Middle Engagement: Long-term contract Location: Europe (EU / EEA / UK), remote Working hours: EU business hours, shifted 2–3 hours later to ensure daily overlap with US West Coast (PST/PDT) mornings

About the Client

Our client is a leading enterprise data platform company building an open, high-performance data lakehouse for AI and analytical workloads. The platform combines an intelligent SQL query engine, an AI-ready semantic layer, and an open catalog built on Apache Iceberg — enabling Fortune 500 companies across finance, energy, manufacturing, and logistics to unify, query, and govern data at massive scale across cloud and on-premise sources.

About the Role

We are looking for a Middle-level Software Engineer to work on the core query engine of a large-scale distributed data platform. You will develop features across query planning, optimization, and execution, contribute to performance-critical components, and help evolve the platform's ability to process massive analytical workloads across heterogeneous data sources.

This is a systems-level, backend engineering role focused on distributed data processing internals — not application development or CRUD services.

Responsibilities

• Develop and maintain features across the query engine — planning, optimization, execution, and data access layers.
• Write high-quality, performance-conscious code in Java and/or C++.
• Work with SQL semantics, query plans, and execution operators over large-scale distributed data.
• Integrate with columnar formats, open table formats, and connectivity drivers used across the platform.
• Contribute to CI/CD pipelines and automated testing — participate in build, test, and release workflows in Jenkins.
• Deploy and validate work in Kubernetes (GKE / EKS / AKS) across GCP, AWS, and Azure using Docker.
• Debug complex issues spanning query planning, distributed execution, memory management, and I/O.
• Collaborate closely with US-based engineering teams on design reviews, code reviews, and technical decisions.

Required Qualifications

• Education: B.S. or M.S. in Computer Science, Computer Engineering, or a related technical field.
• Programming: Strong proficiency in Java or C++, with solid OOP and software design fundamentals. Candidates comfortable with both are especially valued.
• SQL & Data: Strong SQL skills and solid understanding of relational and analytical data systems, including query execution concepts.
• Data processing systems experience: Hands-on experience with data processing systems — query engines, distributed databases, ETL/ELT frameworks, or analytical platforms.
• Engineering experience: 3+ years in backend/systems software engineering.
• CI/CD & DevOps basics: Practical experience with Jenkins pipelines and modern development workflows.
• Containers: Working knowledge of Docker and basic Kubernetes (running workloads, debugging pods, kubectl fluency).
• Cloud: Comfortable operating in at least one major cloud (GCP, AWS, or Azure).
• Version Control: Confident with Git / GitHub workflows.
• English: Upper-Intermediate or higher (B2+) — daily written and verbal communication with a US-based engineering team.
• Availability: Able to work EU hours with a 2–3 hour shift toward US West Coast time to ensure daily overlap with the client team.

Desired Skills

• Experience with Apache Arrow (columnar in-memory format).
• Familiarity with Apache Calcite (SQL parsing, planning, optimization framework).
• Exposure to Gandiva or LLVM-based expression compilation.
• Experience with open table formats — Apache Iceberg, Delta Lake, or Hudi.
• Familiarity with distributed computing frameworks (e.g., Apache Spark, Kafka) and MPP SQL query engines (e.g., Presto, Trino, or similar).
• Understanding of query planning, optimization, and execution internals.
• Experience with data connectivity drivers: JDBC, ODBC, Arrow Flight.
• Kubernetes on managed services (GKE / EKS / AKS) and multi-cloud exposure.
• IaC tools such as Terraform.
• Experience with performance profiling and optimization of latency-sensitive systems.
  Please note: We can consider only candidates currently residing in the EU, EEA, or the UK.
  Please note: We can consider only candidates currently residing in the EU, EEA, or the UK

About the Role:

We are looking for an experienced Senior Data Engineer to join our team and help build scalable, secure, and high-performance data platforms. In this role, you will work closely with Data Architects, Engineers, Analysts, DevOps specialists, and Data Scientists to design, develop, and optimize modern cloud-based data ecosystems.

This is a full-time remote position for a senior-level professional who can commit 40 hours per week and take ownership of complex data engineering initiatives.

🔹 Responsibilities:

As a Senior Data Engineer, you will:

* Collaborate with Data Architects on designing and implementing data solutions across Azure, AWS, or IBM Cloud environments

* Build, maintain, and optimize modern data ecosystems and data pipelines

* Develop and support data ingestion, transformation, and processing solutions

* Work closely with cross-functional teams, including Data Engineers, Analysts, DevOps Engineers, and Data Scientists

* Implement security best practices to ensure the reliability and protection of cloud infrastructure and data processes

* Apply modern engineering principles and methodologies to support business growth and innovation

* Identify opportunities to improve data quality, reliability, scalability, efficiency, and overall platform performance

* Optimize data solutions to balance performance, maintainability, and cost-effectiveness

* Design and execute unit, system, and integration testing strategies

* Contribute to continuous improvement initiatives and engineering best practices

🔹 Requirements:

* Strong commercial experience as a Data Engineer

* Advanced proficiency in Python for data processing, transformation, and analysis

* Strong expertise in SQL, including query optimization and database performance tuning

* Hands-on experience with Azure and/or AWS data platforms and services

* Experience designing and maintaining scalable cloud-based data solutions

* Solid understanding of data engineering best practices, data modeling, and ETL/ELT processes

* Experience with software development lifecycle methodologies and Agile environments

Nice to Have:

* Experience with IBM Cloud data services

* Knowledge of data governance and cloud security practices

* Experience working in enterprise-scale data environments

🌍 What We Offer:

-Paid vacation and sick leave

-We provide the equipment you need to work comfortably (if required)

-We cover 50% of courses if you want to grow professionally

-Regular salary reviews based on your performance

-Competitive salary, depending on your experience

-Always on-time payments — no delays

-A normal, supportive team without unnecessary bureaucracy

We are seeking a skilled ML/AI Engineer to join our team and deliver cutting-edge ML/AI models in the ASR domain and legal insights more broadly. The core of this role is building, deploying, and serving ML models in production. 

A key part of this role is speech engineering — prior ASR/speech experience is not a must, but a willingness to learn and grow into this domain is essential. Experience with LLM-based solutions and agentic flows is an advantage, not a requirement. 

What you’ll do: 

• Build, deploy, and serve ML models in production — the core of the role — optimizing inference performance, latency, and efficient GPU utilization. 
• Support and extend our speech solutions, including 3rd-party ASR integrations and self-hosted ML models. 
• Evaluate and optimize key ASR/ML metrics such as WER, latency, F1 score, EER, and DER. 
• Secondary: Integrate LLMs and agentic flows into production solutions where they add value, including fine-tuning existing models. 

What you’ll bring: 

Core (required): 

• Solid background in machine/deep learning, with 4+ years of experience. 
• Strong Python skills and experience working in Linux environments. 
• Familiarity with deep learning libraries (e.g., PyTorch, TensorFlow) and training workflows. 
• Experience with MLOps pipelines and serving/deploying models in production. 
• Experience optimizing models for inference, including GPU acceleration. 
• Experience with Docker, gRPC, and serverless / micro-services architectures on cloud infrastructure (AWS/GCP/Azure). 
• Experience with real-time / streaming systems and low-latency processing (e.g. streaming pipelines, live sessions). 

Nice to have (secondary / optional): 

• Experience building and productizing agentic flows and AI-driven solutions (1+ year). 
• Familiarity with LLM / agent orchestration frameworks such as CrewAI, AWS Bedrock, Temporal, AgentCore, or LiteLLM. 
• Prior ASR / speech experience — not required; willingness to learn this domain is what matters most. 

📍 Location: Remote

🤝 Engagement: Full-time, long-term project for an international product client

💬 English: B2+

🎯 Level: Senior
 

About the Opportunity

We are looking for a Senior Web Scraping / Data Collection Engineer to join an international product project.

The project is already in development. The client is currently strengthening the data collection / web scraping direction and is looking for an engineer who can take ownership of the existing scraping work and continue developing it.

The main goal is to build a modern and scalable data collection system capable of extracting structured data from various community, hobbyist, and other public websites.

The system should primarily collect structured information about locations, including:

• Name
• Address
• Additional information available on the source
• Sentiment and user opinions

The client plans to use Crawl4AI together with LLMs to handle complex and dynamic content and enable intelligent data extraction.

What You'll Be Doing

• Develop custom scrapers using Crawl4AI.
• Extract structured data from various websites.
• Work with complex and dynamic web content.
• Implement advanced extraction strategies using Pydantic schemas, CSS selectors, and LLM-based parsing.
• Produce structured JSON / Markdown data optimized for further LLM processing.
• Extract basic location data such as names and addresses.
• Extract all available information about locations when additional data is provided by the source.
• Develop approaches for extracting sentiment from user opinions and discussions.
• Transform different opinions about a location into structured data that can be used for further processing and analytics.
• Work with different types of sources, including:
  • Community websites
  • Hobbyist websites
  • Blogs
  • Social media communities and groups
• Work with websites using sophisticated access restrictions, including age gates, CAPTCHAs, and IP rate limits.
• Use session persistence and browser fingerprinting to improve scraping success rates on challenging sources.
• Deliver clean and deduplicated data.
• Produce results in CSV or database-ready formats.
• Optionally contribute to a web interface that allows users to:
  • Enter URLs
  • Configure scraping settings
  • Adjust stealth mode
  • Set crawl depth
  • Add extraction instructions
  • Monitor scraping results

Data Structure

At a basic level, the system should be able to return location data in a simple structured format:

[

 {

   "name": "place1",

   "address": "address1"

 },

 {

   "name": "place2",

   "address": "address2"

 }

]

If a source contains more information, the system should be able to return additional fields in a consistent JSON format.

The system should also support extracting sentiment-related information.

For example, if 6 people mention that they loved a location, 2 consider it average, and 2 disliked it, this information should be structured in a way that can be used for further processing and analytics.

The exact sentiment format can be flexible, but consistent JSON is preferred.

What We're Looking For

• Commercial experience in Web Scraping / Web Crawling / Data Extraction.
• Strong Python skills.
• Hands-on experience working with dynamic and complex websites.
• Experience with browser automation.
• Good understanding of HTML / DOM and CSS selectors.
• Experience developing custom scrapers.
• Experience working with structured data and JSON.
• Experience with Pydantic or similar schema-based approaches.
• Understanding of LLM-based data extraction.
• Experience with session persistence and browser fingerprinting.
• Understanding of CAPTCHA, age gates, and IP rate limits.
• Ability to independently understand an existing scraping solution and continue developing it.
• English B2+.

Nice to Have

• Practical experience with Crawl4AI.
• Experience integrating Crawl4AI with LLMs.
• Experience with Playwright, Selenium, or similar tools.
• Experience with LLM-based parsing / information extraction.
• Experience with sentiment analysis / NLP.
• Experience collecting data from social media communities, blogs, and other user-generated sources.
• Experience building lightweight web interfaces for managing scraping jobs.

Who You Are

We are looking for an engineer who can independently take ownership of the scraping direction, understand the existing solution, and continue developing it.

It is important to be able not only to crawl pages, but to extract high-quality, structured, and usable data from them.

Strong practical experience with dynamic websites, browser automation, complex scraping scenarios, and structured data extraction is especially important.

What We Offer

• 🌍  Remote work.
• 📄  Full-time, long-term project.
• 🚀 Work on an existing international product.
• 🧠 Opportunity to take ownership of a dedicated technical direction.
• 💼 Work with Crawl4AI, LLMs, and modern data extraction approaches.
• 🤝 Direct collaboration with the client team.
• 📈 Opportunity to influence the technical solution and further development of the data collection system.

Hiring Process

1. Recruiter Screening

2. Client Interview (A technical interview with the client team focused on your practical experience, approach to complex scraping challenges, work with dynamic websites, and structured data extraction)

3. Offer 🎉

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.

Responsibility:

• Design and build data templates for integration workflows
• Optimize and improve existing data pipelines
• Ensure smooth and reliable integration across SaaS systems

Requements:

• Commercial experience as a Data Engineer
• Python skills for data engineering tasks
• 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

   

Required languages

EnglishB2 - Upper Intermediate

We are seeking a hands-on Senior DevSecOps Engineer with strong AWS and Azure experience to embed security directly into our engineering lifecycle. In this role, you will be the technical engine that automates compliance guardrails, integrates security tooling (SAST/DAST, EDR, Vulnerability Management) into CI/CD pipelines, and routes critical security telemetry to our SIEM. Your mission is to build the automated scaffolding that allows software delivery to move at high speed without compromising on enterprise security or governance.

Key Responsibilities

·  CI/CD Security Automation: Design, build, and maintain secure deployment pipelines (e.g., GitHub Actions, Azure DevOps, GitLab CI). Integrate automated vulnerability scanning, secret detection, and software supply chain security (SCA) seamlessly into the developer workflow.

·  Policy-as-Code & Guardrails: Write, test, and deploy automated policy guardrails using Infrastructure as Code (IaC) linting and scanning tools (e.g., Checkov, Tfsec, OPA/Rego) to catch misconfigurations before they reach production.

·  Security Product Deployment: Automate the baking of EDR agents, vulnerability scanners, and monitoring tools into base machine images (AMIs, Azure Golden Images) and containerized base environments.

·  Vulnerability & Remediation Pipelines: Operationalize vulnerability management by building automated workflows that ingest findings from cloud security tools, prioritize them based on risk, and route them to engineering backlogs (e.g., Jira tracking).

·  Logging & SIEM Integration: Configure and automate the pipeline delivery of application, container, and infrastructure logs to central logging repositories and SIEM systems for real-time threat hunting.

·  Developer Enablement: Serve as a bridge between Security and Engineering, providing developer-friendly remediation guidance and creating reusable, secure-by-default code templates (Terraform modules, Helm charts).

Required Skills & Qualifications

·  DevSecOps & CI/CD Pipelines: Deep, practical experience constructing and securing automated build/release pipelines at scale.

·  Multi-Cloud Platforms: Hands-on engineering experience configuring native security services and access controls in both AWS and Azure.

·  Infrastructure as Code (IaC): Advanced proficiency with Terraform or cloud-native tooling (Bicep, CloudFormation), focusing on modular design and immutable infrastructure.

·  Security Tooling Implementation: Direct experience implementing and maintaining security products across the lifecycle (e.g., SonarQube, Prisma Cloud, Wiz, Snyk, CrowdStrike, or Sentinel).

·  Container & Orchestration Security: Strong understanding of Kubernetes (EKS/AKS) security best practices, service meshes, and container runtime defense.

Preferred Certifications

·  Certified DevSecOps Professional (CDP) or Practical DevSecOps certification

·  AWS Certified Security – Specialty or Azure Security Engineer Associate

·  Certified Kubernetes Administrator (CKA) / Certified Kubernetes Security Specialist (CKS)...