Jobs Data Engineer

Are you a Senior Backend Engineer passionate about building scalable AI-driven systems? Join us at Sigma Software to work on a cutting-edge platform that transforms how large-scale engineering organizations manage and analyze complex technical data.
This is a remote position with flexible locations across Europe, Ukraine, and LATAM. You will be part of an innovative team leveraging AI, semantic graphs, and distributed processing to deliver impactful solutions.
At Sigma Software, we value expertise, creativity, and collaboration. Why join us? You will work with advanced technologies, contribute to mission-critical projects, and be part of a company recognized for excellence and innovation.

CUSTOMER
Our customer operates in the AdTech industry, delivering advanced technology solutions that optimize advertising performance and audience targeting. While the name is confidential, the organization is known for leveraging cutting-edge AI and data-driven strategies to enhance campaign effectiveness and deliver measurable business impact.

PROJECT
We are developing a next-generation AI-powered Knowledge Base and Gap Analysis platform for SysML-based engineering environments. The system enables large-scale engineering organizations to ingest, structure, analyze, and reason over complex MBSE artifacts and technical documentation. It supports both cloud and secure classified environments, improving traceability, identifying gaps, and enhancing decision-making in mission-critical projects.

Responsibilities

• Design and develop scalable AI-powered backend systems for SysML-based engineering environments
• Build and maintain distributed data ingestion and ETL pipelines for large-scale engineering artifacts and technical documentation
• Develop and optimize LLM-powered workflows for metadata extraction, semantic analysis, and entity resolution
• Implement AI agents and multi-agent orchestration workflows
• Design and improve RAG-based architectures and semantic retrieval pipelines
• Develop graph-based knowledge representation and traceability analysis solutions
• Work with graph databases, graph processing libraries, and semantic relationship modeling
• Build and optimize distributed data processing workflows using Apache Spark
• Collaborate with cross-functional engineering teams to integrate AI capabilities into platform services
• Design scalable and high-performance APIs and backend services
• Improve system reliability, scalability, observability, and performance across distributed environments
• Participate in architecture discussions and technical decision-making processes
• Contribute to cloud-native infrastructure and deployment workflows
• Support deployments in secure, air-gapped, or classified environments when required
• Create and maintain technical documentation and engineering best practices

Qualifications

• At least 5 years of commercial experience in software engineering, Data Engineering, or AI systems development
• Experience with at least one JVM language
• Hands-on experience building distributed and scalable systems
• Practical experience with LLM-based applications and AI integrations
• Experience building AI agents and multi-agent systems
• Strong understanding of RAG architectures and semantic retrieval workflows
• Hands-on experience with graph technologies, graph libraries, or graph databases
• Experience with Apache Spark and distributed data processing
• Strong understanding of ETL pipelines and large-scale data ingestion workflows
• Experience with cloud-native infrastructure and distributed environments
• Practical experience with backend platform development and API integrations
• Good understanding of semantic search, entity resolution, and metadata extraction
• Experience working with highly scalable and high-performance systems
• Strong problem-solving and communication skills
• Upper-Intermediate level of English

WILL BE A PLUS

• Background in Data Engineering
• Experience with  distributed data processing, Apache Spark, or Apache Beam
• Experience with Knowledge Graphs and graph-based semantic modeling
• Familiarity with MBSE or SysML environments
• Experience supporting air-gapped or classified environments
• Experience with vector databases and embedding pipelines
• Experience with Kubernetes and cloud platforms such as AWS, GCP, or Azure

Additional information

PERSONAL PROFILE

• Analytical mindset with strong problem-solving skills
• Ability to work independently and in a distributed team
• Adaptability to secure and classified environments
• Strong communication and collaboration abilities
• Passion for AI-driven engineering solutions

Are you a Senior Backend Engineer passionate about building scalable AI-driven systems? 

Join us at Sigma Software to work on a cutting-edge platform that transforms how large-scale engineering organizations manage and analyze complex technical data.
This is a remote position with flexible locations across Europe, Ukraine, and LATAM. You will be part of an innovative team leveraging AI, semantic graphs, and distributed processing to deliver impactful solutions.
At Sigma Software, we value expertise, creativity, and collaboration. Why join us? You will work with advanced technologies, contribute to mission-critical projects, and be part of a company recognized for excellence and innovation.

CUSTOMER
Our customer operates in the AdTech industry, delivering advanced technology solutions that optimize advertising performance and audience targeting. While the name is confidential, the organization is known for leveraging cutting-edge AI and data-driven strategies to enhance campaign effectiveness and deliver measurable business impact.

PROJECT
We are developing a next-generation AI-powered Knowledge Base and Gap Analysis platform for SysML-based engineering environments. The system enables large-scale engineering organizations to ingest, structure, analyze, and reason over complex MBSE artifacts and technical documentation. It supports both cloud and secure classified environments, improving traceability, identifying gaps, and enhancing decision-making in mission-critical projects.

Responsibilities

• Design and develop scalable AI-powered backend systems for SysML-based engineering environments
• Build and maintain distributed data ingestion and ETL pipelines for large-scale engineering artifacts and technical documentation
• Develop and optimize LLM-powered workflows for metadata extraction, semantic analysis, and entity resolution
• Implement AI agents and multi-agent orchestration workflows
• Design and improve RAG-based architectures and semantic retrieval pipelines
• Develop graph-based knowledge representation and traceability analysis solutions
• Work with graph databases, graph processing libraries, and semantic relationship modeling
• Build and optimize distributed data processing workflows using Apache Spark
• Collaborate with cross-functional engineering teams to integrate AI capabilities into platform services
• Design scalable and high-performance APIs and backend services
• Improve system reliability, scalability, observability, and performance across distributed environments
• Participate in architecture discussions and technical decision-making processes
• Contribute to cloud-native infrastructure and deployment workflows
• Support deployments in secure, air-gapped, or classified environments when required
• Create and maintain technical documentation and engineering best practices

Qualifications

• At least 5 years of commercial experience in software engineering, Data Engineering, or AI systems development
• Experience with Python
• Hands-on experience building distributed and scalable systems
• Practical experience with LLM-based applications and AI integrations
• Experience building AI agents and multi-agent systems
• Strong understanding of RAG architectures and semantic retrieval workflows
• Hands-on experience with graph technologies, graph libraries, or graph databases
• Experience with Apache Spark and distributed data processing
• Strong understanding of ETL pipelines and large-scale data ingestion workflows
• Experience with cloud-native infrastructure and distributed environments
• Practical experience with backend platform development and API integrations
• Good understanding of semantic search, entity resolution, and metadata extraction
• Experience working with highly scalable and high-performance systems
• Strong problem-solving and communication skills
• Upper-Intermediate level of English

WILL BE A PLUS

• Background in Data Engineering
• Experience with  distributed data processing, Apache Spark, or Apache Beam
• Experience with Knowledge Graphs and graph-based semantic modeling
• Familiarity with MBSE or SysML environments
• Experience supporting air-gapped or classified environments
• Experience with vector databases and embedding pipelines
• Experience with Kubernetes and cloud platforms such as AWS, GCP, or Azure

Additional information

PERSONAL PROFILE

• Analytical mindset with strong problem-solving skills
• Ability to work independently and in a distributed team
• Adaptability to secure and classified environments
• Strong communication and collaboration abilities
• Passion for AI-driven engineering solutions

Are you passionate about building scalable, reliable data systems that power real-world solutions? We are looking for a Senior Data Engineer to join our team and work remotely from Europe, Ukraine, or LATAM.

At Sigma Software, we partner with innovative companies to deliver cutting-edge technology solutions. This role offers the opportunity to design and operate a canonical data platform that integrates diverse external data sources, ensuring high quality and flexibility.

Why join us? You’ll work with modern technologies, collaborate with talented professionals across multiple regions, and have the freedom to experiment and innovate while contributing to impactful projects in the AdTech domain.

Customer

Our client is a fast-growing AdTech company focused on solving real-world challenges in digital advertising and data-driven marketing. They specialize in building highly resilient and scalable systems that encourage experimentation and innovation. Their data platform is designed to be both powerful and flexible, enabling engineers to introduce new ideas and leverage the latest technologies to optimize advertising performance and audience insights.

Project

The project involves developing and maintaining a canonical data platform that integrates multiple external data sources. It supports both full data loads and incremental updates, ensures high data quality, and leverages AI-assisted tools for monitoring and issue detection.

Key Technologies: Java, Scala, Apache Beam/Apache Spark, SQL, GCP Dataflow, REST APIs, AI-assisted tools, event-driven architectures

Responsibilities

• Design, build, and maintain reliable data pipelines to ingest and process data from external systems
• Implement integrations using Java or Scala, ensuring scalability and resilience
• Handle both full data loads and incremental updates efficiently
• Collaborate with engineering and product teams to align on integration and data needs
• Develop and maintain a unified internal data model
• Ensure data quality, detect and resolve incorrect or incomplete data
• Utilize AI-assisted tools to improve data quality and operational efficiency
• Monitor and optimize data pipelines for production readiness

Requirements

• At least 5 years of experience as a Data Engineer or Backend/Data Engineer
• Strong production experience with Java or Scala
• Experience with Apache Beam or Apache Spark
• Proven experience integrating external systems via REST APIs (pagination, rate limiting, token-based authentication)
• Strong data modelling skills with structured, relational data
• Solid SQL knowledge
• Experience with GCP Dataflow
• Experience operating data pipelines in production environments
• Strong communication skills and ability to collaborate across teams
• At least an Upper Intermediate level of English

WILL BE A PLUS:

• Experience with event-driven architectures or messaging systems
• Designing canonical schemas across multiple data sources
• Experience with LLM (Large Language Models)

Personal Profile

• Proactive and detail-oriented
• Thrives in collaborative environments
• Enjoys solving complex integration challenges
• Comfortable experimenting with new technologies
• Committed to improving data systems

About the Client

Our client is a leading global healthcare organization, driving innovation in pharmaceuticals, biotechnology, and patient-centric solutions.

We develop advanced data and analytics solutions that help global organizations turn complex data into intuitive digital tools, enabling teams to make informed decisions in their daily operations and long-term strategy. Our projects span modern operational applications, interactive dashboards, and advanced analytics platforms designed to deliver actionable insights across multiple business domains.
 

About the Role

We are seeking a Power Platform Engineer to lead the implementation of an automated reporting and presentation-generation solution for a global pharmaceutical organization.

The primary objective is to automate the creation of PowerPoint presentations based on data and visualizations from Power BI, leveraging Power Automate, Power BI APIs, Microsoft 365 services, and Copilot capabilities. The solution will enable business users to generate standardized executive reports with minimal manual effort.

The successful candidate will work directly with business stakeholders and client team, taking ownership of solution design, implementation, and ongoing enhancements.
 

Responsibilities:

• Design and implement an automated reporting solution using Power Automate and Power BI APIs.
• Develop workflows that export Power BI report pages and populate PowerPoint templates automatically.
• Integrate Microsoft Copilot capabilities to generate AI-assisted slide commentary.
• Build user-friendly automation triggers through Teams, SharePoint, or scheduled execution.
• Configure and manage connections between Power Platform components and reporting systems.
• Ensure solution reliability, maintainability, and scalability.
• Create technical documentation and support handover activities.
• Evaluate opportunities for future integrations with SAP Analytics, financial systems, and external web-based data sources.
   

Requirements:

• 4+ years of experience working with Microsoft Power Platform.
• Strong hands-on experience with Power Automate.
• Experience integrating and working with Power BI, including Power BI Service and Power BI APIs.
• Experience building business process automation solutions within Microsoft 365.
• Solid understanding of SharePoint Online and Teams integrations.
• Experience working with REST APIs and authentication mechanisms.
• Understanding of Microsoft Copilot capabilities and AI-assisted workflow automation.
• Strong stakeholder communication and requirements clarification skills.
• Experience working in international and cross-functional teams.
• Ability to work independently and drive technical decisions.
• English level - Upper-Intermediate or higher.

Backend / Data Engineer (Ad Fraud Platform)
Про компанію
Ми розробляємо платформу для виявлення рекламного фроду та підвищення точності маркетингової атрибуції.
________________________________________
Основні задачі
•        Архітектура anti-fraud системи 
•        Real-time event processing 
•        Data pipelines та стрімінг 
•        Rule engine (GIVT / SIVT) 
•        Server-side tracking (Meta / Google) 
•        Deduplication та атрибуція 
•        Телеметрія та сигнали якості 
•        Моніторинг та алерти 
•        Співпраця з продуктом 
________________________________________
Вимоги
•        2+ роки backend / data engineering 
•        Python + SQL 
•        Kafka / streaming 
•        ClickHouse / BigQuery 
•        Event-based системи 
•        CI/CD, Git 
________________________________________
Буде плюсом
•        Ad fraud / IVT 
•        Meta CAPI / Google tracking 
•        Bot detection / WAF 
•        Rule engines / DSL 
________________________________________
Ми пропонуємо
•        Вплив на продукт 
•        Full-time remote формат роботи 
•        Бонуси за результат 
•        Гнучкий графік 
•        Бюджети на інфраструктуру 
•        Швидкі ітерації

About PredictSpring

PredictSpring is a market-leading company shaping the future of omni-channel retail and modern POS technology. We help global retail and lifestyle brands deliver seamless, modern, and data-driven customer experiences across digital and in-store channels.

We are looking for a highly skilled Senior AI/ML Engineer – GenAI to design, develop, and deploy enterprise-grade AI solutions with a strong focus on Generative AI, Large Language Models, Retrieval-Augmented Generation, and Agentic AI systems.

In this role, you will build production AI applications, multi-agent workflows, scalable ML pipelines, and cloud-native AI solutions that create business value across our platform and operations.
 

Responsibilities

As a Senior AI/ML Engineer – GenAI, you will:

• Design, develop, and deploy enterprise Generative AI applications using foundation models such as GPT, Claude, Gemini, Llama, Mistral, and other open-source LLMs.
• Build advanced RAG solutions using vector databases, embeddings, reranking techniques, and hybrid search architectures.
• Develop prompt engineering strategies, evaluation frameworks, guardrails, and hallucination mitigation techniques.
• Fine-tune and optimize LLMs using techniques such as LoRA, QLoRA, PEFT, and reinforcement learning approaches.
• Integrate LLMs with enterprise applications, APIs, databases, and business workflows.
• Design and implement autonomous and semi-autonomous AI agents capable of reasoning, planning, memory management, tool usage, and workflow orchestration.
• Build multi-agent systems using frameworks such as LangGraph, LangChain, AutoGen, CrewAI, Semantic Kernel, MCP, A2A, or similar technologies.
• Build and maintain end-to-end machine learning pipelines, including data ingestion, feature engineering, model training, evaluation, deployment, and monitoring.
• Develop predictive models, recommendation systems, anomaly detection solutions, NLP applications, and deep learning models.
• Design CI/CD pipelines for machine learning and AI applications.
• Deploy and manage AI workloads using Docker, Kubernetes, and cloud-native services.
• Monitor model drift, performance degradation, latency, and data quality.
• Architect cloud-native AI solutions on AWS, Azure, or Google Cloud Platform.
• Partner with product managers, software engineers, data engineers, and business stakeholders to translate business requirements into AI solutions.
• Mentor junior engineers and contribute to architecture reviews, technical strategy, and AI best practices.

Requirements

We are looking for someone with:

• Upper C1 or higher English proficiency, with fluent spoken and written English.
• Ability to confidently participate in client-facing discussions, technical workshops, architecture reviews, stakeholder presentations, and cross-functional collaboration.
• Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Data Science, Machine Learning, Engineering, or a related field.
• 7+ years of software engineering, machine learning, or AI experience.
• Minimum 3+ years of hands-on experience developing and deploying Generative AI applications in production environments.
• Strong Python programming skills with experience building scalable backend systems.
• Extensive experience with machine learning frameworks including PyTorch, TensorFlow, scikit-learn, and Hugging Face.
• Proven experience developing RAG architectures and knowledge retrieval systems.
• Experience building Agentic AI solutions and multi-agent workflows.
• Strong understanding of vector databases, embeddings, semantic search, and retrieval optimization.
• Experience with cloud platforms including AWS, Azure, or GCP.
• Strong understanding of MLOps principles, CI/CD, containerization, and model lifecycle management.

Preferred Qualifications

Nice to have:

• Experience with managed AI services such as AWS SageMaker, AWS Bedrock, Azure OpenAI, Azure ML, or Vertex AI.
• Experience with distributed computing platforms such as Databricks, Spark, or Ray.
• Experience with AI governance, responsible AI practices, model monitoring, and production AI observability.
• Experience with secure AI architectures, role-based permissions, auditability, and compliance controls.
• Experience in retail, e-commerce, omni-channel commerce, or POS technology is a strong plus.

Why PredictSpring?

• Join a market-leading company shaping the future of omni-channel retail and modern POS.
• Work on high-impact challenges at the intersection of commerce, data, AI, and customer experience.
• Collaborate with a talented global team in a flexible remote work environment.
• Enjoy opportunities for growth, learning, and professional development.
• Contribute to products used by some of the world’s most recognized retail and lifestyle brands.
• Be part of an innovative, collaborative, and data-driven culture focused on delivering measurable business value.

Intetics Inc., a global technology company providing custom software application development, distributed professional teams, software product quality assessment, and “all-things-digital” solutions, is seeking a highly skilled and experienced Senior Python Engineer with Apache Airflow experience to join our dynamic team on a full-time basis.

Responsibilities

• Own and support critical backend services, ensuring their stability and performance
• Implement new features and improvements in existing systems
• Investigate issues related to data pipelines, DAGs, indexing, and web applications
• Perform root cause analysis and propose effective solutions
• Suggest and implement improvements across different layers of the system
• Actively collaborate with the team and communicate with the client

Requirements

• 5+ years of experience with Python, including development of Airflow DAGs and Flask applications
• 3+ years of experience with Apache Airflow (DAG development and orchestration)
• 3+ years of experience with Elasticsearch (data indexing and optimization)
• 3+ years of experience with GitLab, including CI/CD pipeline design
• 3+ years of experience with Oracle or PostgreSQL (ideally both)
• 3+ years of experience working with Unix/Linux systems
• 5+ years of experience working in Agile environments
• Strong experience in data pipelines, distributed systems, and backend development
• Ability to perform root cause analysis and work with complex systems
• Advanced English
• Technical degree

Soft Skills

• Proactive and self-driven approach to work
• Strong communication skills, both written and verbal
• Ability to clearly express ideas and collaborate with team members and stakeholders
• Attention to detail and commitment to high-quality delivery
• Strong listening skills and openness to feedback

About the Role

We're looking for a sharp, analytically mindedcontractor to support our accounting team with workpaper modernization and dataquery work. This is a hands-on, execution-focused engagement suited for someonewho moves fast, works independently, and takes ownership.

Technical Requirements

 *   Advanced Excel proficiency — pivot tables, dynamic arrays, Power Query, and building structured reporting tools for high-volume datasets
 *   Advanced SQL skills — complex queries, stored procedures, window/analytical functions, and query optimization
 *   Hands-on experience with dbt, Google BigQuery, and Airflow
 *   4–6 years of hands-on experience analyzing and engineering large datasets in a business or finance context
 *   Demonstrated ability to pick up unfamiliar tools and systems quickly

Soft Skills & Work Style

 *   Highly organized with the ability to juggle multiple deliverables
 *   Strong attention to detail without losing sight of the bigger picture
 *   Self-starter who operates well with minimal oversight
 *   Collaborative — comfortable interfacing with accounting and operations teammates
 *   Professional proficiency in English (written and verbal)

We are looking for a Senior Data Engineer to support a wealth/asset management client with data integration, data platform modernization, reporting, and analytics enablement.
The ideal candidate should have strong experience building reliable data pipelines, integrating enterprise and financial systems, preparing data for BI/analytics, and working with business-critical datasets where accuracy, governance, and data quality are essential.
This role may involve working with data from portfolio management systems, CRM / ERP platforms, SAP, finance systems, reporting tools, and cloud-based data platforms.
 

Responsibilities:

Design, build, and maintain scalable data pipelines from enterprise systems into analytics/reporting environments
Integrate data from systems such as SAP, CRM, portfolio/wealth management platforms, APIs, flat files, and databases
Build and optimize data models for BI, reporting, dashboards, and business analytics
Support Tableau / Power BI reporting by preparing clean, reliable, well-structured datasets
Develop ETL / ELT workflows for ingestion, transformation, validation, and reconciliation
Implement data quality checks, monitoring, logging, and issue resolution processes
Work with business stakeholders to understand reporting requirements and translate them into data models
Collaborate with analysts, BI developers, application teams, and business users
Support migration or modernization of legacy reporting/data workflows into a more scalable architecture
Ensure data security, access control, governance, and compliance with financial-industry expectations

Requirements

5+ years of experience in data engineering, data warehousing, or analytics engineering
Strong SQL skills and experience designing analytical data models
Experience building ETL / ELT pipelines and working with structured business data
Hands-on experience with cloud data platforms or warehouses such as Snowflake, Databricks, Redshift, BigQuery, Azure Synapse, or similar
Experience integrating data from ERP / enterprise systems; SAP experience is a strong plus
Experience supporting BI tools such as Tableau, Power BI, Looker, or similar
Strong understanding of data quality, reconciliation, lineage, governance, and access control
Experience working with APIs, batch data loads, scheduled jobs, and file-based integrations
Ability to work with stakeholders to clarify reporting needs and data definitions
Strong communication skills and ability to work in a client-facing environment

Nice to Have

Experience in wealth management, asset management, private banking, investment management, family office, or financial services
Experience working with portfolio, holdings, transactions, performance, client, or advisor data
Experience with SAP data extraction/integration, SAP BW, SAP HANA, or SAP Datasphere
Experience with Tableau and Power BI semantic models/datasets
Experience with Python for data processing and automation
Experience with dbt, Airflow, Fivetran, Matillion, Informatica, Azure Data Factory, AWS Glue, or similar tools
Experience with master data management, data catalogues, data lineage, or data governance platforms
Understanding of financial reporting, regulatory reporting, or client reporting workflows

Tech Stack / Tools
Relevant experience may include:

Data platforms: Snowflake, Databricks, Redshift, BigQuery, Azure Synapse
ETL / orchestration: Airflow, dbt, Azure Data Factory, AWS Glue, Fivetran, Matillion, Informatica
BI / reporting: Tableau, Power BI, Looker
Enterprise systems: SAP, SAP BW, SAP HANA, SAP Datasphere, CRM, portfolio management platforms
Languages: SQL, Python
Cloud: AWS, Azure, GCP
Data governance: data quality checks, lineage, access control, reconciliation

Responsibilities
Design, build, and maintain end-to-end data pipelines using Palantir Foundry

Develop and manage data models, transformations, and workflows within Foundry

Integrate data from multiple sources (APIs, databases, files, event streams)

Ensure data quality, reliability, security, and governance across data products

Optimize performance and scalability of data pipelines and analytics workloads

Collaborate with product managers, analysts, and stakeholders to translate business needs into data solutions

Support analytics, reporting, and advanced use cases (including ML/AI where applicable)

Contribute to best practices, documentation, and data platform standards

Requirements (Must-Have)
Senior-level experience as a Data Engineer (5+ years)

Palantir certification (Foundry)

Strong hands-on experience working with Palantir Foundry in production

Excellent proficiency in Python and SQL

Experience building and operating cloud-based data platforms

Solid understanding of data modeling, ETL/ELT, and data warehousing concepts

Strong focus on data quality, governance, and security

Experience working in Agile, cross-functional teams

Professional working proficiency in English

Must be located in Europe

Nice to Have
Experience with cloud platforms (AWS, Azure, or GCP)

Exposure to analytics engineering or data product development

Experience working in regulated or enterprise environments

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.

We are looking for a Senior Data Engineer to join the Identity team at Equals5. This is not a standard ETL role. We are building a dynamic data ecosystem where AI is deeply integrated—both as a productivity multiplier and as a core component of our data processing logic for identity data enrichment and data scoring.

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

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

Responsibilities

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

Requirements

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

Culture & Mindset

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

What We Offer

• Fully remote with flexible hours (aligned with EU timezones for syncs).
• AI-Native Environment: We provide licenses for Claude Code and encourage using the bleeding edge of AI tech for both daily coding and product features.
• High-Impact Role: You will directly influence how we identify and score users, impacting the core business logic.
• Cross-functional visibility: Work closely with Product and Tech Leads to shape the future of Identity.
• No Bureaucracy: Fast decisions, no legacy processes, focus on results.

We are looking for a Data / Backend Engineer to architect and scale the core data infrastructure behind our healthcare marketing platform. In this role, you will design high-throughput data systems that process millions of behavioral events, power real-time attribution and user scoring, and enable precise targeting of healthcare professionals across 20+ channels.

You will work at the intersection of data engineering, backend systems, and marketing infrastructure, building scalable pipelines, tracking systems, and APIs that support analytics, segmentation, and campaign activation. The role also involves experimenting with AI-powered automation and agent-based workflows to improve internal operations and product capabilities.

This is a high-ownership position where you will shape architecture decisions, build critical platform components from the ground up, and help evolve our data platform as the company scales.

Responsibilities

- Architect and own data-heavy backend systems powering real-time attribution, user modeling, and scoring

- Build and evolve client-side tracking pixels (like FB pixel / Amplitude snippet / Heap autocapture) from scratch

- Set up and manage scalable ETL workflows: cleaning, merging, enriching, splitting, transforming across millions of behavioral events
Lead the build of CDP / CDXP-style data layers to support segmentation, scoring, and activation across channels

- Connect and compose systems using modern low-code / no-code tools (n8n) to accelerate ops

- Implement and maintain high-availability APIs for analytics, scoring, and campaign delivery

- Drive experimentation around AI-powered agents and automation tools that can boost internal workflows

Requirements

- System Design & Data Architecture:
Designs scalable, event-driven data platforms with strong decoupling, fault tolerance, and horizontal scalability. Builds real-time and batch pipelines using lakehouse architectures and streaming systems (Kafka / PubSub).

- Distributed Data Processing (Spark / BigQuery / Iceberg):
Expert in large-scale data processing, query optimization, and cost-efficient analytics. Deep understanding of Spark execution, partitioning, and modern table formats (Iceberg / Delta).

- Cloud & Infrastructure (GCP / Kubernetes):
Builds resilient cloud-native data platforms on GCP and Kubernetes using IaC, autoscaling, and secure access (IAM, Workload Identity).

- Python Engineering:
Develops high-performance Python services for data and ML workloads with focus on concurrency, clean architecture, and production-grade quality.

- Databases & Performance (PostgreSQL / OLTP):
Optimizes high-throughput OLTP systems through indexing, partitioning, and query analysis (EXPLAIN ANALYZE, MVCC).

- Reliability & Observability (SRE):
Implements resilient data systems with idempotency, retries, observability, SLOs, and incident management.

- AI / LLM Integration:
Integrates LLMs into production pipelines with structured outputs, caching, batching, prompt versioning, and evaluation.

- Workflow Orchestration (Airflow / Dagster):
Designs scalable DAG-based workflows with dependency management, retries, and reproducible backfills.

- CI/CD & DevOps for Data:
Implements safe deployments for data systems including schema migrations, canary releases, and data contracts.

- Ownership & Engineering Maturity:
Owns end-to-end production systems and architecture decisions while balancing delivery speed, quality, and technical debt.

Nice-to-have: 

- Experience in MarTech / AdTech platforms (e.g., DSPs, attribution systems, DMP/CDP tools)

- Deep knowledge of data matching/fingerprinting techniques (identity graphs, IP + UA resolution, hashed PII workflows)

- Strong prompt engineering skills — not just ChatGPT 101, but chaining, system prompting, tooling integration

What We Offer
- Fully remote with flexible hours (aligned with EU timezones for syncs).
- Influence on quality strategy across the entire engineering organization.
- A cross-team role with visibility into every part of the product.
- AI-first tooling.
- Claude Code licenses and cutting-edge AI development workflows. 
- A team with no bureaucracy, decisions are made fast.

We are an international product company, we provide e-learning and self-development services to a wide audience. 

And we are looking for a Junior BI Engineer to join our team.

Stack of our BI Tool:

• SQL (SQL server, MySQL, Postgres);
• Cloud services (Amazon S3, Redshift, Google BigQuery, Amazon Athena);
• Power BI;
• Python.

Your future tasks:

• Development and optimization of reports and dashboards in Power BI.
• Hands on with Power BI Desktop (dashboard creation, reports, troubleshooting, data source management).
• Create and edit SQL queries within Power BI to build calculated fields.
• Optimizing routine tasks by creating automated reports and data extractors.
• Changing developed reports on request from the team.
• Support in data analysis and decision-making process.

About you:

• 0.5+ years of experience.
• Experience with SQL databases.
• Experience with PowerBI.
• MS Office Suite (Excel, Sp lists, Sharepoint).
• Python (pandas, numpy, json, BS, sqlalchemy, smtp).

Nice to have:

• Bachelor degree in computer-science or economics.
• Understanding of Google’s BigQuery, Data Studio or AWS’s Athena, Redshift.
• Using Python for data transformation and preparation, building data extractors.
• Knowledge of HTML, CSS, JavaScript.

We offer:

- 100% remote within international product team.

- Paid vacation, sick leaves, and additional day off.

We are looking for a senior GCP Data Engineer / Data Architect to lead and execute an on-premise to GCP data migration project.
This is a hands-on data-focused role, not a classic DevOps/Kubernetes role.

Main responsibilities:
- Lead and implement the migration of data workloads from on-premise infrastructure to GCP
- Design and build GCP data lake / lakehouse architecture
- Work hands-on with GCP data services such as BigQuery, Dataproc, Cloud Storage, Spark, and related tools
- Design and implement scalable data pipelines and data processing flows
- Handle data ingestion, storage, security, reliability, and cost optimization
- Work independently with the existing technical team and drive technical decisions

Required experience:
- Strong hands-on GCP data engineering experience
- BigQuery, Dataproc, Spark, and Cloud Storage
- Data lake / lakehouse architecture
- On-premise to cloud migration experience
- Ability to lead technical decisions and work independently

Nice to have:
- Dataflow, Pub/Sub, Cloud Composer / Airflow
Full-time availability is preferred. Please apply only if you have real hands-on experience with GCP data platforms and data migration projects.