Jobs Data Engineer

Equals5 helps pharmaceutical companies run precisely targeted ad campaigns on social platforms by identifying healthcare professionals and the consumer signals that reach them. The Identity team builds the data, scoring, and targeting systems that make this possible.

We are looking for a Senior Data Analyst to join the Identity team at Equals5. This is not a standard analyst role. We are building a dynamic identity resolution system where AI is deeply integrated — both as a productivity multiplier and as a core component of our data processing logic for identity resolution and LLM-based scoring.

We run enrichment against 70+ TB of data, apply AI and LLM-based scoring on top, and process around 20 million enrichment operations per day across hundreds of thousands of records.

The analytical challenges ahead are substantial: how to measure the quality of AI-driven scoring, how to validate that a change makes the system better, how to know where our money and time deliver the most value, and how to turn the questions our internal teams bring in into fast data-backed answers. You will own this side of the business, working daily alongside engineers and the product lead to turn these challenges into decisions that ship.

The main part of the role is not building dashboards — it is the data work that makes a meaningful dashboard possible in the first place. Concretely, you will be:

• Looking at data from multiple vendors side by side and deciding what to trust.
• Reconciling entities across sources that have different shapes and quality.
• Proposing and validating the logic that matches and scores them.
• Defining metrics and ground truth for questions nobody has asked before.
• Tracing why numbers don't line up across partial and sometimes contradictory sources.

Dashboards and visualizations are part of how findings get communicated, but they come at the end — the surface of the work, not its core. Most of your time is spent on what sits underneath: methodology, judgment calls on data quality, and shaping how the domain understands its own numbers.

Responsibilities

• Measurement & Evaluation Foundations: Define how we measure what matters — data quality, the accuracy of our AI scoring, how many records actually get matched to usable signals, cost per outcome. Build the feedback loops that tell us whether a change makes the system better or worse.

• Scoring Intelligence (co-owned with engineers): Partner with the engineering team on the LLM-based scoring system. You will build the evaluation framework for AI scoring, run experiments comparing prompts, models, and approaches against a baseline, and make data-backed calls on where we invest next. Our AI scoring system is actively evolving — you will shape how we measure and improve it.

• Client-related Analysis: Own the analytical side of the work that internal sales and media-buying teams bring in from pharma clients — how reachable a target audience is, how good the data looks, why a campaign performed the way it did. You turn their questions into data-backed answers they can use. Identity is a product core; the analyst works with internal teams, not with clients directly.

• Cost and Value Analysis: Turn cost and value into product decisions. Which data sources and enrichment scenarios pay off, where we overspend, what to cache, what to cut. We operate a mix of free owned data and paid external providers — the decisions have real dollar impact.

• Active AI Usage: Use Claude Code and modern AI engineering tools to multiply your own output. Automate the repetitive parts of analysis so you can focus on the decisions. We provide Claude Code licenses and expect active daily use.

• Data Quality Response: When pipeline output drifts, a provider degrades, or upstream data shifts, you notice first, diagnose the root cause, and drive the fix. You treat data quality as a product, not a ticket queue.

Requirements

• 5+ years as a Data Analyst, Analytics Engineer, or Data Scientist in a product team (not consultancy, not BI-only roles).
• Advanced SQL at TB scale — BigQuery, Snowflake, or equivalent warehouse. You can read and write complex queries on tens of terabytes without someone pre-modelling the data for you.
• Python for analysis at a working level — pandas, Jupyter, or modern equivalents. Comfortable putting together a small script or helper when an existing tool doesn't cover your case.
• Built measurement or evaluation frameworks from scratch for systems that had no baseline. You are comfortable defining what and how to measure, not consuming someone else's KPI.
• Comfort with probabilistic systems. You understand that noise is inherent and 100% accuracy is not the goal — scoring, matching, ranking.
• AI-native workflow. You already use Claude Code, ChatGPT, Copilot, or similar AI tools daily and integrate them into your analytical process.
• English: B2+ (Upper-Intermediate) or higher.

Strong plus 

• LLM evaluation experience — A/B testing AI-powered features, output scoring, prompt iteration with measurable outcomes.
• Identity resolution / identity graph experience — adtech, martech, or customer data platform context (LiveIntent, LiveRamp, Epsilon, Experian Marketing, Acxiom, Merkle, or similar).
• Healthcare or pharma data — working with NPI, HCP-level data, healthcare taxonomies, pharma targeting.

Nice to have

• Experience running controlled experiments on data pipelines.
• Prompt engineering or structured LLM prompt design.
• Prior work in AI-first product companies.

What We Offer

• Fully remote with flexible hours, with working overlap in CET ±2 hours for syncs.
• AI-Native Environment: We provide licenses for Claude Code and encourage using the bleeding edge of AI tech — both for daily work and as part of product logic.
• High-Impact Role: You will directly shape how we identify, score, and reach healthcare professionals — the core business of our domain.
• Small team, direct impact: You will work directly with Product and Engineering leads — no layers between you and the people making decisions.
• No Bureaucracy: Fast decisions, no legacy processes, focus on results.

Equals5 is a leading Healthcare Marketing SaaS for Pharma and Life Sciences. Our platform leverages exclusive NPI-level targeting technology to help brands reach healthcare professionals across 20+ channels with precise, user-level reporting.

The Role

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.

   

Description

The GlobalLogic technology team is focused on next-generation health capabilities that align with the client’s mission and vision to deliver Insight-Driven Care. This role operates within the Health Applications & Interoperability subgroup of our broader team, with a focus on patient engagement, care coordination, AI, healthcare analytics, and interoperability. These advanced technologies enhance our product portfolio with new services while improving clinical and patient experiences.

Requirements

An AWS Data Engineer designs, develops, and maintains scalable data solutions using AWS cloud services.
Key Responsibilities:
    • Design, build, and manage ETL (Extract, Transform, Load) pipelines using AWS services (e.g., Glue, Lambda, EMR, Redshift, S3).
    • Develop and maintain data architecture (data lakes, warehouses, databases) on AWS.
    • Implement data quality and governance solutions.
    • Automate data workflows and monitor pipeline health.
    • Ensure data security and compliance with company policies.
Required Skills:
    • Proficiency with AWS cloud services, especially data-related offerings (S3, Glue, Redshift, Athena, EMR, Kinesis, Lambda).
    • Strong SQL and Python skills.
    • Experience with ETL tools and frameworks.
    • Familiarity with data modelling and warehousing concepts.
    • Knowledge of data security, access management, and best practices in AWS.
Preferred Qualifications:
    • AWS certifications (e.g., AWS Certified Data Analytics – Speciality, AWS Certified Solutions Architect).
    • Background in software engineering or data science.

• Hands-on experience with Oracle Database and log-based Change Data Capture (CDC) replication using AWS Database Migration Service (DMS) for near real-time data ingestion.

Middle+ Backend Engineer (Cloudflare),

English B1+

Project: A B2B layer for LLM token usage compression, designed as a cost optimization product for businesses utilizing large language models. The platform relies heavily on edge computing to deliver fast, scalable, and cost-effective proxy services.

Requirements:

- 4+ years of professional development experience.

- Strong hands-on experience building and running web services on Cloudflare Workers.

- Expertise in utilizing Cloudflare D1 (Serverless SQL database).

- Experience with Cloudflare Hyperdrive for optimizing regional database connections.

Nice to have:

- Experience working with LLM APIs (OpenAI, Anthropic, etc.) and understanding token economics.

- Background in building B2B SaaS platforms, API gateways, or developer tools.

Full-time, 10-12 months, start in 3-4 weeks

We are a technology consultancy working with enterprise B2B clients across the US and Europe — manufacturing, distribution, high-tech. Our teams build and integrate complex digital commerce solutions on platforms like SAP, Salesforce, and Shopify. The project is long-term and actively growing.

What You’ll Do

• Design and develop ETL/ELT pipelines across multiple enterprise platforms
• Build and maintain data warehouses and data lakes
• Ensure data quality, reliability, and security
• Prepare clean, structured datasets to support AI/ML initiatives
• Work closely with architects, developers, and business analysts
• Monitor and optimize data infrastructure for performance

What We’re Looking For

• 5+ years of experience as a Data Engineer
• Strong SQL and Python skills
• Hands-on experience with AWS, GCP, or Azure
• Experience with Airflow, dbt, or Spark
• Familiarity with Snowflake, BigQuery, or Redshift
• REST API and enterprise integration experience is a plus
• English B2+ – you’ll communicate directly with the team and stakeholders

Nice-to-Have Skills

• Familiarity with AI development tools (Claude Code, Gemini CLI)
• Experience with containerization (Docker) and orchestration platforms
• Knowledge of cloud data platforms (AWS, GCP, Azure)
• Leadership experience

What We Offer

• Fully remote work
• International team with clear processes
• Paid vacation, holidays, and sick leave

CrunchCode — міжнародна сервісна ІТ-компанія з досвідом близько 7 років у розробці вебсервісів і вебзастосунків. Ми працюємо у форматах staff augmentation (outstaff) та outsourcing і підключаємо спеціалістів до проєктів клієнтів у довгостроковій моделі співпраці.

Ми працюємо переважно з проєктами в доменах логістики (включно з last mile),e-commerce, fintech та банкінгу, а також enterprise-рішеннями.
Для нас важливо, щоб проєкт був “чистим” і зрозумілим з точки зору етики та цінності для користувачів.

Ми принципово не беремо проєкти, пов’язані з:
● gamblng / гемблінгом,
● adult-контентом та порнографією,
● шахрайством або будь-якою розробкою, що спрямована на обман чи маніпуляції.

What We Offer:
● Fully remote work
● Long-term, stable project
● High level of autonomy and trust
● Minimal bureaucracy
● Direct impact on business-critical logistics systems
● Long-term engagement, not a short-term contract.

Project Overview
Enterprise-grade data engineering role within a Pan-Baltic banking environment. The engineer will work on large-scale data platforms, building and maintaining production-ready pipelines and modern data lakehouse architectures across the organization.

Tech Stack
Python, Apache Spark, AWS (EMR, Glue, Athena, S3), SQL, Data Lakehouse, ETL/ELT

Requirements (Must-have):
- Strong hands-on enterprise data engineering experience
- Advanced SQL skills and solid understanding of analytical and dimensional data modeling
- Proven experience with Data Lakehouse / modern data platform concepts (cloud object storage, open table formats, distributed processing)
- Strong hands-on experience with AWS data services: EMR, Glue, Athena, S3-based data lakes
- Strong hands-on experience with Apache Spark for large-scale data processing
- Strong Python skills for ETL development, data processing, and automation
- Very strong analytical, problem-solving, and system-level thinking skills
- Fluent English B2+ — required for Pan-Baltic communication (spoken and written)

Responsibilities:
- Design, implement, and maintain robust production data pipelines
- Build and optimize Data Lakehouse and modern data platform solutions
- Work with AWS data services across the full data engineering stack
- Process large-scale data using Apache Spark
- Develop ETL workflows and automation scripts in Python
- Apply advanced SQL and dimensional/analytical data modeling
- Contribute to system-level thinking and data architecture decisions

Nice to Have:
- Experience in banking or financial services
- Familiarity with data governance and compliance practices

Hiring Process:
Intro call
Technical discussion
Offer
Start: ASAP

Project Description

We are a global audience and location intelligence company that helps marketers connect the digital and physical world. We provide data-driven solutions to enhance marketing campaigns by leveraging location and audience data to reveal consumer behavior and enable more precise targeting and measurement. We work on high-end / high-performance / high-throughput systems for in-time analysis of data for autonomous driving and other big data applications e.g. for E-commerce.

Job Responsibilities

Work in a self-organised agile team with a high level of autonomy, and you will actively shape your team's culture.

Design, build, and standardise privacy-first big data architectures, large-scale data pipelines, and advanced analytics solutions in AWS.

Develop complex integrations with third-party partners, transferring terabytes of data.

Align with other Data experts on data (analytics) engineering best practices and standards, and introduce those standards and data engineering expertise to the team in order to enhance existing data pipelines and build new ones.

Successfully partner up with the Product team to constantly develop further and improve our platform features.

Requirements:

• 4+ years in a Data Engineering or similar high-scale role.
• Expert-level Python skills. Familiarity with Java or Scala is a major plus.
• Proven hands-on experience building scalable solutions directly within AWS.
• Deep proficiency in high-throughput architectures using Kafka, Spark, Hadoop, MongoDB, AWS Batch, AWS Glue, Athena, Airflow, and dbt.
• Exceptional SQL and data transformation skills, with an eye for optimizing NoSQL and SQL databases.
• Ability to simplify complex technical concepts and a passion for mentoring junior engineers in a collaborative environment.

About the project

US-founded media company operating email newsletters at scale – millions of subscribers across finance, health, and business verticals. Small engineering team, flat structure, direct ownership, fast iteration. No layers of approval, no large org to navigate.

You'll own the integration and infrastructure layer alongside a counterpart engineer who handles the AI and automation side. The AI systems depend on what you build staying reliable.
 

What you'll work on

• Custom CRMs and operational tools tailored to internal workflows
• Browser automation pipelines with Playwright for interacting with and validating UI workflows
• Distributed automation infrastructure: proxy management, session handling, request routing
• PostgreSQL data models and pipelines that AI systems and operational teams depend on
• Integrations with third-party APIs and platforms – including ones with inconsistent or undocumented APIs
   

Requirements

• 6+ years of backend development
• 4+ years of production Python
• Strong PostgreSQL: schema design, indexing, query optimization – not just ORM usage
• Hands-on Playwright or equivalent (Selenium, Puppeteer) for real browser automation
• Experience with proxy infrastructure: rotation, health checking, geographic routing
   

Tech stack

Python · FastAPI · PostgreSQL · Playwright · Docker · proxy infrastructure · REST APIs and webhooks · third-party platform integrations
 

Conditions

• B2B contract, full-time
• Warsaw office (onsite preferred, remote considered)
• Direct collaboration with technical PM and small senior team
• Fast-moving environment: ambiguity, shifting priorities, growing scope

We build and operate AI-enabled systems that create measurable operational impact across the organization. Our primary output is working software in production.

Anchors the data platform architecture and owns enterprise data extraction end-to-end.

Ideal Candidate

Has designed and built a data platform from scratch in an enterprise environment — not inherited a running system, built one. Has pulled data from SAP or comparable ERP into a warehouse and survived upstream failures without silent data loss. Sets standards that other engineers can follow without three clarification meetings. Can make architecture calls quickly and correct them later. Has strong opinions about pipeline observability and data quality.

Skills Required

• SAP data extraction: OData services, RFC/BAPI, SAP Data Services, or CDS views — hands-on experience pulling data from SAP FI/CO modules
• Python — async data pipelines, background jobs, scheduled tasks
• PostgreSQL — schema design, migrations (Alembic), query optimization, partitioning
• Azure Data Lake Storage + Synapse Analytics
• Microsoft Graph API — SharePoint, M365, organizational data
• Apache Airflow or Azure Data Factory
• dbt or equivalent for transformation and quality testing
• Redis — queue management, TTL, cache invalidation
• Observability — structured logging, Azure Monitor or Prometheus/Grafana
• Docker — containerized pipeline jobs
• Infrastructure-as-code (Terraform or equivalent)

Skills Required

• SAP data extraction: OData services, RFC/BAPI, SAP Data Services, or CDS views — hands-on experience pulling data from SAP FI/CO modules
• Python — async data pipelines, background jobs, scheduled tasks
• PostgreSQL — schema design, migrations (Alembic), query optimization, partitioning
• Azure Data Lake Storage + Synapse Analytics
• Microsoft Graph API — SharePoint, M365, organizational data
• Apache Airflow or Azure Data Factory
• dbt or equivalent for transformation and quality testing
• Redis — queue management, TTL, cache invalidation
• Observability — structured logging, Azure Monitor or Prometheus/Grafana
• Docker — containerized pipeline jobs
• Infrastructure-as-code (Terraform or equivalent)
  
  Has designed and built a data platform from scratch in an enterprise environment — not inherited a running system, built one. Has pulled data from SAP or comparable ERP into a warehouse and survived upstream failures without silent data loss. Sets standards that other engineers can follow without three clarification meetings. Can make architecture calls quickly and correct them later. Has strong opinions about pipeline observability and data quality.

LITSLINK is looking for a Senior Azure Data Engineer to join an enterprise client project. We are looking for a proactive engineer with strong experience in the Azure data ecosystem who can quickly take ownership of tasks and deliver high-quality solutions.

Responsibilities

• Migrate data processing logic from SQL Server stored procedures to Azure Databricks
• Build and maintain ETL/ELT pipelines using Azure Data Factory
• Replace and integrate new data sources in Power BI
• Optimize data models and reporting performance
• Work with large datasets and optimize SQL queries
• Collaborate with data, BI, and engineering teams
   

Requirements

• 7+ years of experience in Data Engineering
• Strong hands-on experience with the Azure data ecosystem
• Experience with:
  • Azure Data Factory
  • Azure Databricks
  • SQL
  • Power BI
• Experience building and optimizing data pipelines
• Experience migrating data workloads to cloud environments
• Python for data processing
• Proactive mindset and strong ownership of tasks
   

Engagement Details

• Full-time
• Remote
• 3-month contract (renewable)
• Start ASAP

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.

Description

The GlobalLogic technology team is focused on next-generation health capabilities that align with the client’s mission and vision to deliver Insight-Driven Care. This role operates within the Health Applications & Interoperability subgroup of our broader team, with a focus on patient engagement, care coordination, AI, healthcare analytics, and interoperability. These advanced technologies enhance our product portfolio with new services while improving clinical and patient

experiences.

Requirements

An AWS Data Engineer designs, develops, and maintains scalable data solutions using AWS cloud services.

Key Responsibilities:
    • Design, build, and manage ETL (Extract, Transform, Load) pipelines using AWS services (e.g., Glue, Lambda, EMR, Redshift, S3).
    • Develop and maintain data architecture (data lakes, warehouses, databases) on AWS.
    • Implement data quality and governance solutions.
    • Automate data workflows and monitor pipeline health.
    • Ensure data security and compliance with company policies.
Required Skills:
    • Proficiency with AWS cloud services, especially data-related offerings (S3, Glue, Redshift, Athena, EMR, Kinesis, Lambda).
    • Strong SQL and Python skills.
    • Experience with ETL tools and frameworks.
    • Familiarity with data modelling and warehousing concepts.
    • Knowledge of data security, access management, and best practices in AWS.
Preferred Qualifications:
    • AWS certifications (e.g., AWS Certified Data Analytics – Speciality, AWS Certified Solutions Architect).
    • Background in software engineering or data science.

• Hands-on experience with Oracle Database and log-based Change Data Capture (CDC) replication using AWS Database Migration Service (DMS) for near real-time data ingestion.

Job responsibilities

– Develops, documents, and configures systems specifications that conform to defined architecture standards, address business requirements, and processes in the cloud development & engineering.

– Involved in planning of system and development deployment, as well as responsible for meeting compliance and security standards.

– API development using AWS services in a scalable, microservices-based architecture

– Actively identifies system functionality or performance deficiencies, executes changes to existing systems, and tests functionality of the system to correct deficiencies and maintain more effective data handling, data integrity, conversion, input/output requirements, and storage.

– May document testing and maintenance of system updates, modifications, and configurations.

– May act as a liaison with key technology vendor technologists or other business functions.

– Function Specific: Strategically design technology solutions that meet the needs and goals of the company and its customers/users.

– Leverages platform process expertise to assess if existing standard platform functionality will solve a business problem or if a customisation solution would be required.

– Test the quality of a product and its ability to perform a task or solve a problem.

– Perform basic maintenance and performance optimisation procedures in each of the primary operating systems.

– Ability to document detailed technical system specifications based on business system requirements

– Ensures system implementation compliance with global & local regulatory and security standards (i.e. HIPAA, SOCII, ISO27001, etc.)

What we offer

Culture of caring. At GlobalLogic, we prioritize a culture of caring. Across every region and department, at every level, we consistently put people first. From day one, you’ll experience an inclusive culture of acceptance and belonging, where you’ll have the chance to build meaningful connections with collaborative teammates, supportive managers, and compassionate leaders. 

Learning and development. We are committed to your continuous learning and development. You’ll learn and grow daily in an environment with many opportunities to try new things, sharpen your skills, and advance your career at GlobalLogic. With our Career Navigator tool as just one example, GlobalLogic offers a rich array of programs, training curricula, and hands-on opportunities to grow personally and professionally.

Interesting & meaningful work. GlobalLogic is known for engineering impact for and with clients around the world. As part of our team, you’ll have the chance to work on projects that matter. Each is a unique opportunity to engage your curiosity and creative problem-solving skills as you help clients reimagine what’s possible and bring new solutions to market. In the process, you’ll have the privilege of working on some of the most cutting-edge and impactful solutions shaping the world today.

Balance and flexibility. We believe in the importance of balance and flexibility. With many functional career areas, roles, and work arrangements, you can explore ways of achieving the perfect balance between your work and life. Your life extends beyond the office, and we always do our best to help you integrate and balance the best of work and life, having fun along the way!

High-trust organization. We are a high-trust organization where integrity is key. By joining GlobalLogic, you’re placing your trust in a safe, reliable, and ethical global company. Integrity and trust are a cornerstone of our value proposition to our employees and clients. You will find truthfulness, candor, and integrity in everything we do.

Laba Group is one of the largest international EdTech companies in Eastern Europe. Currently, our team consists of over 800 colleagues united by a single mission: to improve people's lives through relevant and systematic knowledge.

In 10 years, we have launched over 1,400 courses and educated more than 200,000 students globally. We have also created 5 online education brands:

• Laba – an online business school
• Skvot – a school of popular culture
• robot_dreams – a platform for growth in IT
• Vocabulaba – a school of English for professionals
• elvtr – an online school in the US and the UK

We are seeking a Middle  Data Engineer.  The primary purpose or objective of this role is to be responsible for designing, building, and maintaining a scalable data infrastructure that supports analytics, reporting, and business decision-making within the organization. 

The role focuses on developing robust data pipelines, integrating multiple data sources, ensuring data quality, and delivering business-driven data solutions that align with the company's goals.

What will be the main responsibilities ?

• Design, build, and maintain scalable ETL/ELT pipelines.
• Integrate data from internal and external systems (CRMs, LMS, marketing platforms, databases, etc.).
• Develop and maintain API integrations (REST/JSON, OAuth, etc.).
• Automate recurring data processes using Python (or similar scripting languages).
• Design and maintain data models optimized for analytics and operational reporting.
• Work with cloud data warehouses (e.g., BigQuery, Snowflake) to ensure efficient storage and retrieval.
• Implement data validation and monitoring mechanisms to ensure accuracy and reliability.
• Proactively monitor and resolve data pipeline failures.
• Create dashboards and data applications using low-code/no-code platforms (e.g., Power BI, Retool, Coda, Tableau, Google Sheets).
• Translate complex datasets into clear, actionable insights for business stakeholders.
• Collaborate with analysts and business teams to define KPIs and reporting requirements.
• Suggest improvements to existing data flows and business processes.
• Maintain structured and comprehensive technical documentation (pipelines, integrations, data definitions, architecture).
• Participate in cross-functional discussions to align technical implementation with business needs

What skills and experience are considered necessary?

• Strong proficiency in Python (or similar scripting language) for data manipulation and automation.
• Advanced SQL knowledge and experience in data modeling.
• Hands-on experience with API integrations (REST, JSON, OAuth) and related tools (e.g., Postman).
• Experience working with cloud platforms (GCP, AWS) and cloud data warehouses.
• Experience with orchestration tools (e.g., Airflow, dbt, or similar frameworks).
• Familiarity with Git and CI/CD processes.
• Experience with low-code/no-code platforms for data visualization or workflow automation.
• Solid understanding of business processes and KPI-driven decision-making.
• 2–4 years of experience in a data engineering or data-focused role.

Skills that would be "nice to have":

• Experience developing and customizing internal tools using Retool, with working knowledge of JavaScript.
• Experience optimizing query performance and cost efficiency in cloud environments.
• Exposure to real-time data streaming solutions.
• Experience supporting AI/ML data pipelines.
• Strong data storytelling and stakeholder communication skills

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Why Laba Group is the Place to Be🔥:

• Flexible full-time. We focus on results, not hours worked: manage your own time, stay connected with the team, and meet deadlines.
•  Remote, onsite, or hybrid — it’s up to you! Our modern workspace in Kyiv is fully equipped with everything you need.

As part of our team, you’ll get:

• Access to all Laba Group courses for you and your family.
• Compensation for external training, sports, and mental and physical health, helping you stay balanced and prioritize your well-being.
• Unlimited vacation after 6 months of working with us. Plan according to your needs and adjust based on workload intensity because rest is essential for your health. 
• We create a supportive environment where facing challenges and making mistakes isn’t scary. A place to find like-minded people and become part of a larger community. A service that truly puts the client first.
• No micromanagement or bureaucracy — only automated processes. Feel free to experiment, propose, and implement your ideas.
• We champion a proactive mindset, bold ideas, and a willingness to embrace change. Laba isn’t about going with the flow — it’s about pushing the world forward.
• We provide only up-to-date insights from market experts—knowledge that can be immediately applied in practice, transforming workflows even during the learning process. Our products are designed for decisive action in business and careers.
• A socially responsible environment: we regularly launch charity projects and fundraisers to support Ukraine and its defense forces.
• Vertical and horizontal growth: 83% of our Heads of Departments and Team Leaders have been promoted internally.

Our recruitment process is transparent and straightforward. 

Three stages: an interview with the Rectuiter→ Test Task→ an interview with the HM’s team 

After that, the job offer will be in your  inbox.🙌

We’re not looking for perfect candidates. We’re looking for bold and “one of us” people. 💛

Join the team. It’s going to be an amazing journey.

Join the Data Engineering team to contribute to the ongoing maintenance and improvement of an internal LLM-powered assistant that uses hosted LLM APIs and internal knowledge sources, with a focus on reliability, retrieval quality, and operational excellence.

Responsibilities

Maintain and enhance ingestion/enrichment pipelines for internal content (parsing/extraction, normalization, metadata enrichment, deduplication, and quality monitoring)

Improve indexing and retrieval performance and quality (chunking/segmentation refinements, embedding/index update workflows, metadata filtering, caching) and support hybrid retrieval capabilities (vector + keyword/BM25 + metadata)

Implement and maintain access-aware retrieval by propagating/enforcing document permissions through indexing and query-time filters, including audit logs and validation tests

Improve source attribution so responses reliably point to the correct documents and sections in a consistent format.

Extend and harden tool/workflow execution and automations (scheduled/trigger-based), including retries, timeouts, idempotency, concurrency controls, and run history

Develop and maintain evaluation and regression testing (golden sets, automated scoring) and support structured comparisons across LLM providers/models as required

Operate the platform in production: observability (logs/metrics/tracing), alerting, incident support, performance tuning, and cost controls, plus runbooks and handover documentation

Skills

Must have

8+ years of hands-on experience in Data Science and 5+ years in Machine Learning, with a proven track record, demonstrated through a robust portfolio of projects.

Strong programming skills in languages such as Python and familiarity building ETL pipelines.

Expertise in SQL and experience with both relational (preferably Postgres) and NoSQL databases (Open Search or Elastic Search)

Familiarity with cloud platforms (e.g., AWS) and their services.

Experience with version control systems (e.g., Git) and CI/CD pipelines.

Ability to build scalable infrastructure to embed and search very large number of documents.

Ability to move fast in an environment where things are sometimes loosely defined and may have competing priorities or deadlines.

Expertise in ML inference optimizations

Solid experience with Hybrid RAG, chunking/segmentation refinements, embedding/index update workflows, metadata filtering, caching, etc.

Knowledge of network optimization for distributed ML training and inference.

Understanding of distributed training patterns and checkpointing strategies.

Strong English skills (B2 and higher)

Strong verbal and written communication skills.

Ability to work independently and collaborate in a group.

Nice to have

Agile certification

AWS/Oracle/Microsoft attestations and certifications

Domain knowledge

Trading and Capital Markets