Jobs Data Engineer

Join an exciting journey to create a cutting-edge Consumer Data Lake for a leading global organization based in Europe. This platform will unify, process, and leverage consumer data from various systems, unlocking advanced analytics, insights, and personalization opportunities. As a Senior Data Engineer, you will play a pivotal role in shaping and implementing the platform's architecture, focusing on hands-on technical execution and collaboration with cross-functional teams.

Your work will transform consumer data into actionable insights and personalization on a global scale. Using advanced tools to tackle complex challenges, you’ll innovate within a collaborative environment alongside skilled architects, engineers, and leaders.

Key Responsibilities:

• Hands-On Development: Build, maintain, and optimize data pipelines for ingestion, transformation, and activation.
• Create and implement scalable solutions to handle diverse data sources and high volumes of information
• Data Modeling & Warehousing: Design and maintain efficient data models and schemas for a cloud-based data platform.
• Develop pipelines to ensure data accuracy, integrity, and accessibility for downstream analytics.
• Collaboration: Partner with Solution Architects to translate high-level designs into detailed implementation plans.
• Work closely with Technical Product Owners to align data solutions with business needs.
• Collaborate with global teams to integrate data from diverse platforms, ensuring scalability, security, and accuracy.
• Platform Development: Enable data readiness for advanced analytics, reporting, and segmentation.
• Implement robust frameworks to monitor data quality, accuracy, and performance.
• Testing & Quality Assurance: Implement robust security measures to protect sensitive consumer data at every stage of the pipeline
• Ensure compliance with data privacy regulations (e.g., GDPR, CCPA ..) and internal policies.
• Monitor and address potential vulnerabilities, ensuring the platform adheres to security best practices.

Requirements:

• Over 4+ years of experience showcasing technical expertise and critical thinking in data engineering.
• Hands-on experience with DBT and strong Python programming skills.
• Proficiency in Snowflake and expertise in data modeling are essential.
• Demonstrated experience in building consumer data lakes and developing consumer analytics capabilities is required.
• In-depth understanding of privacy and security engineering within Snowflake, including concepts like RBAC, dynamic/tag-based data masking, row-level security/access policies, and secure views.
• Ability to design, implement, and promote advanced solution patterns and standards for solving complex challenges.
• Familiarity with multiple cloud platforms (Azure or GCP preferred, with a focus on Azure).
• Practical experience with Big Data batch and streaming tools.
• Competence in SQL, NoSQL, relational database design (SAP HANA experience is a bonus), and efficient methods for data retrieval and preparation at scale.
• Proven ability to collect and process raw data at scale, including scripting, web scraping, API integration, and SQL querying.
• Experience working in global environments and collaborating with virtual teams.
• A Bachelor’s or Master’s degree in Data Science, Computer Science, Economics, or a related discipline.

We are looking for a Lead Data Engineer to drive the design and implementation of scalable data solutions, pipelines, and analytics-ready datasets. 

What You’ll Do 

• Lead design and implementation of data pipelines, transformations, and curated datasets 
• Translate business requirements into structured data solutions and models 
• Guide and execute development of reusable, analytics-ready data assets 
• Ensure consistency in how key data elements are defined and used across systems 
• Collaborate with stakeholders to define and refine data requirements and logic 
• Review and guide engineering work to ensure quality, performance, and scalability 
• Establish best practices for data engineering, transformation, and data quality 
• Support integration of data across multiple domains and systems 
• Contribute to architecture decisions across data platforms and tooling 
• Mentor and support other engineers on the team 

What You Bring 

Must-Haves 

• 5+ years of experience in data engineering, analytics engineering, or related fields 
• Strong SQL expertise and experience designing complex data transformations 
• Hands-on experience with modern data platforms (e.g., GCP BigQuery, Databricks, Snowflake) 
• Data platforms experience. ELT or ETL, orchestration such as Airflow or dbt, Spark, data warehouses and lakehouses such as Snowflake, BigQuery, or Databricks, streaming such as Kafka or Kinesis, metadata and data quality 
• Proficiency in Python 
• Strong understanding of data modeling concepts and data structuring for analytics 
• Experience working with stakeholders to define requirements and deliver data solutions 
• Ability to balance hands-on delivery with technical guidance 

Nice-to-Haves 

• Familiarity with data governance, lineage, or metadata management concepts 
• Experience working with cross-domain data (e.g., customer, product, transactions) 
• Exposure to financial services or other data-intensive industries 
• Experience supporting migration or evolution of data platforms (e.g., toward Databricks) 
• Experience with orchestration tools (e.g., Airflow, Cloud Composer) 
• Exposure to data modeling concepts (e.g., dimensional models, data marts, reusable datasets) 

What’s in It for You 

• Impact at scale. Help shape enterprise AI, software, and data programs across industries. 
• Growth and mastery. Work with a seasoned team from leading consulting and technology backgrounds. 
• Build real products. Work on production ready assets with autonomy over key technical decisions. 

🚀 Senior Data Engineer (EU)

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 looking for a Senior Data Engineer with specialized domain expertise in fraud detection, Anti-Money Laundering (AML), or transaction-monitoring systems to establish data-quality foundations for decision engines.

Our client is a fast-growing European FinTech company in the Business Spend Management space - providing corporate cards and related financial products to SME and mid-sized businesses across the EU and UK in a regulated environment.
You will embed directly into a product squad as a hands-on Individual Contributor (IC). 

Key Responsibilities:

• Architect and build robust data-quality frameworks specifically designed to power decision engines.
• Design, scale, and maintain reliable, high-throughput production data pipelines.
• Build infrastructure and workflows that enable fast, seamless deployment of fraud and transaction-monitoring rules.
• Bring deep domain knowledge in Fraud, AML, and Transaction Monitoring to production data engineering workflows.
• Multiply the output and quality of your squad while sharing data engineering patterns and best practices across the organization.

Requirements:

• Strong, senior-level 5+ years expertise in Python for data engineering and production pipeline development.
• Experience/background in Fraud, AML, or Transaction-Monitoring systems.
• Proven track record of establishing data-quality foundations for automated decisioning systems.
• Extensive experience building production data pipelines and supporting rapid rule deployment workflows.

Nice-to-Have Skills:

• Hands-on experience with Airflow, SQL, PostgreSQL, and Google BigQuery (standard stack for data/analytics workloads).
• Experience working in hybrid cloud environments (AWS primary + GCP analytics).
• Familiarity with modern engineering workflows (Linear, GitHub, Notion, Slack) and AI-assisted development (Claude Code, GitHub Copilot).

Client

Our client is the UK’s leading development finance institution, dedicated to supporting companies in developing countries and driving sustainable growth.

Position overview

We are looking for a Senior/Lead Data Engineer to join a distributed team working on modern cloud-based data solutions within the Azure ecosystem. The role involves designing, developing, and maintaining scalable data pipelines and integrations that support business-critical reporting, analytics, and operational processes.

You will work closely with cross-functional teams, contributing to architecture decisions, delivery processes, and continuous platform improvements while ensuring high standards of quality and reliability.

Responsibilities

• Design, develop, and maintain data pipelines and ETL/ELT processes using Azure technologies
• Build and support scalable solutions using Azure Data Factory (ADF), Azure SQL, and other Azure services
• Develop backend logic and automation using Python, Azure Functions, and Logic Apps
• Collaborate with stakeholders, analysts, and engineering teams to gather requirements and deliver data solutions
• Monitor, troubleshoot, and optimize data workflows and integrations
• Participate in code reviews, technical discussions, and solution design activities
• Contribute to CI/CD and deployment processes within the Azure environment
• Ensure data quality, security, and performance best practices are followed
   

Requirements

• Strong hands-on experience with Azure Data Factory (ADF)
• Solid experience with Azure SQL and the Azure Data Stack
• Strong Python development skills
• Experience working with Azure Logic Apps and Azure Function Apps
• Good understanding of cloud-based data architecture and integration patterns
• Experience building and maintaining scalable data pipelines
• Familiarity with Azure DevOps, Git, and CI/CD pipelines
• Experience working in Agile development environments
• Strong communication and collaboration skills
• Upper-Intermediate or higher English level

Nice to have

• Experience leading technical initiatives or mentoring engineers
• Knowledge of data governance and security best practices
• Experience with infrastructure automation or monitoring tools
• Exposure to financial services or development finance domains

Main requirements

Snowflake Experience

The person should be proactive, well-organized, and an effective communicator, able to independently drive tasks forward, keep processes under control, and communicate clearly with the team and stakeholders.

Requirements

Senior Data Enginer

Snowflake — core development

• Writing and maintaining production views, secured views and stored logic in Snowflake
• Understanding of role-based access control: users, roles, GRANTs, warehouse and database entitlement models
• Enough query-tuning instinct to build views over large fact tables without wrecking performance — partition pruning, clustering awareness, avoiding SELECT *

Microsoft SQL Server

• T-SQL development
• Migrating legacy tables, views and stored procedures to Snowflake

Previous ETL Tooling Experience

Bonus Points

BI and semantic layer

• Sigma Computing — connection setup, workbooks, embedding, AI/Cortex configuration. We are rolling Sigma out now and retiring Tableau Desktop.
• Tableau — data source management, extract vs live strategy, extract scheduling and dependency mapping

Documentation and code review

• Producing data-flow and architecture diagrams
• Reviewing SQL/pipeline code to a standard — we have a code review backlog in other areas because there aren’t enough qualified SQL reviewers. A contractor who can act as a second reviewer is disproportionately valuable.

Azure DevOps (aka ADF Pipelines sync’d with Github)

• CI/CD pipelines for database and ADF artefacts, service principal / client secret configuration, release troubleshooting

External API ingestion

• Consuming and loading third-party APIs into the warehouse (e.g. FX/exchange rate feeds), including auth and error handling
• Snowflake Git integration — connecting a Git repository to Snowflake, versioning database objects and deploying from a branch, plus general source-control discipline for SQL and pipeline code
• Snowflake Streamlit — building lightweight in-warehouse data apps as an alternative to a full BI workbook where the audience is small or the use case is operational
• Python for data engineering and Snowpark
• Snowflake Cortex / LLM-in-warehouse features
• dbt or equivalent transformation tooling (not in use today, but relevant if we modernise)

Working attributes we need

• Comfortable being the second pair of hands on a one-person team — takes a ticket end-to-end without daily direction
• Documents as they go; we are explicitly trying to reduce single-person key-man risk
• Cost-aware: several of our decisions are spend-driven, not purely technical

English - Andvanced

About the role

We're looking for a middle DevOps / SysOps engineer to take care of the infrastructure our product runs on: on-prem virtualization, network and VPN connectivity between sites, and the delivery pipelines on top of it. The team is small, so you get real ownership from the start — and room to grow into your own areas of responsibility.

Responsibilities

* Operate and develop on-prem virtualization: VMware ESXi + vCenter (clusters, resource pools, storage, patching and version upgrades)

* Administer network infrastructure: MikroTik, Cisco, pfSense — VLANs, routing, NAT, firewall policies

* Build and maintain WireGuard site-to-site and client VPN topologies between offices, labs and cloud

* Maintain Ubuntu servers: systemd, journald, configuration management, hardening, monitoring and alerting

* Support Docker-based build and deployment workflows

* Develop and maintain CI/CD pipelines in GitHub Actions

* Manage S3-compatible object storage for backups and build artifacts

* Own backup and restore procedures, including regular recovery testing

* Write technical documentation and runbooks for what you build

* Participate in incident response and on-call rotation

Requirements

* 2+ years of commercial experience in DevOps / system administration / infrastructure

* Production experience with VMware ESXi and vCenter

* Hands-on experience with at least two of: MikroTik RouterOS, Cisco, pfSense / OPNsense

* Networking fundamentals: L2/L3, VLAN, static and dynamic routing, NAT, firewall policies, DNS, DHCP, TLS, SSH

* WireGuard (or IPsec / OpenVPN): configuring tunnels and routing between sites, troubleshooting asymmetric routing

* Docker and Docker Compose: builds, registries, networking, volumes

* CI/CD with GitHub Actions (or GitLab CI with readiness to move to GHA)

* Linux (Ubuntu): confident CLI, systemd, journald, bash scripting

* Basic experience with S3-compatible storage or a public cloud provider (AWS / Azure / GCP / Hetzner)

* Monitoring and logging basics: Zabbix, Prometheus + Grafana, or ELK

* English for technical communication (reading docs, written async communication)

Nice to have

* Cisco FTD / FMC, Cisco ISE (802.1X, NAC, posture)

* Certifications: VCP-DCV, CCNA / CCNP Security, MTCNA / MTCRE / MTCINE, LFCS / RHCSA, AWS SAA

* Other VMware products: vSAN, NSX, Horizon (VDI), VCF, Site Recovery Manager, Veeam Backup & Replication

* Automation and IaC: Ansible, Terraform, Python

* Information security fundamentals: PKI, secrets management, hardening baselines (CIS), secure boot

* Bare-metal / Raspberry Pi / embedded Linux

* Experience with isolated or air-gapped environments

What we offer

* Competitive salary

* Reservation from mobilization

* Office in Kyiv with shelter access, generator and Starlink

* Possibility of hybrid work format

* Impact on improving our country's defense capabilities

* 21 days of vacation + public holidays, sick leaves

We are looking for a Senior DevOps Engineer to build and evolve the infrastructure behind Kyivstar's Big Data products. You will own the full lifecycle of our cloud and on-premises environments - from architecture and provisioning to CI/CD, observability and incident response 

Requirements

- 3+ years of experience as a DevOps Engineer.

- Practical experience with cloud providers (AWS preferred).

- Experience building CI/CD pipelines (preferably GitLab).

- Strong hands-on experience with Docker and Kubernetes.

- Practical experience with Infrastructure as Code (IaC) (preferably Terraform).

- Solid understanding of Unix/Linux operating systems and networking fundamentals.

- Strong hands-on experience with scripting languages (Bash and/or Python).

- Experience with relational and non-relational databases (e.g., PostgreSQL or similar).

- Experience with monitoring and alerting tools (e.g., Prometheus, Grafana).

- Proven experience working with remote/distributed teams.

- Experience with AI agents or AI-driven tooling is a plus.

Responsibilities

- Implement solutions for Big Data and AI products.

- Design and implement CI/CD pipelines tailored for Big Data solutions.

- Manage and maintain AWS and on-premises infrastructure.

- Monitor, troubleshoot, and continuously improve system observability.

- Automate software deployment, monitoring, and routine operational tasks.

- Support staging/production environments, manage release cycles, and assist customers.

We offer

•            A unique opportunity to shape the future of Big Data products at Ukraine's leading telecom operator

•            Work on high-impact initiatives that create value across multiple business functions

•            Collaboration with experienced business, data and technology professionals

•            Remote work with the possibility to visit the office

•            Competitive salary and annual bonus

•            Paid vacation and sick leave

•            Flexible working hours

•            Medical and life insurance

•            Professional development and career growth opportunities

•            A friendly, collaborative and innovation-driven working environment

ABOUT US

ODDITY is a consumer-tech company which builds and scales digital-first brands to disrupt offline-dominated categories.

With HQ in New York City and an R&D center in Tel Aviv, we built one of the industry’s most advanced technology platforms, which leverages data science, machine learning and computer vision capabilities to deliver an unparalleled online experience for consumers. We are using cutting-edge data science to identify consumer needs and develop solutions in the form of tech and wellness products.

In less than 5 years since launch, we have built two of the fastest-growing online beauty brands in the US-IL MAKIAGE and SpoiledChild. Our first brand IL MAKIAGE has since grown to unprecedented scale online, reaching over $300 million in revenue and 40 million users in only 4 years. ODDITY New Ventures built and launched our second brand SpoiledChild in early 2022, and it is already scaling even faster than IL MAKIAGE. As of 2023, ODDITY is officially a publicly traded company valued at >$2B and we were named a TIME100 Most Influential Company.

Our continued success is a result of our winning mindset combined with unparalleled physical & tech products. We have made significant investments in data science, AI, computer vision, and biotechnology to identify consumer needs and develop solutions designed for consumers. Our proprietary computer vision technology allows smartphone cameras to capture hyperspectral wavelengths of light beyond the capability of the human eye. In 2023, ODDITY acquired Revela - a biotech start-up that uses AI-based molecule discovery to bring next-generation, proprietary ingredients to the beauty & wellness market.

ABOUT THE ROLE

We are seeking bright and curious data-minded individuals to join our Data team. Data is a core to our growing business and our Data team is the engine that powers our data-driven culture. As a Data Engineer, you will play a vital role in designing & building solutions for our most challenging business problems.

KEY RESPONSIBILITIES

• Help design and implement data collection strategy to ensure we know as much as possible about user experience and needs
• Design, build, and maintain ETL and ELT pipelines
• Develop and optimize data processing pipelines using AWS Glue
• Build robust data transformations using Python and SQL
• Support BI use cases and verify data availability for reporting in Looker
• Work hand-in-hand with engineers and product leaders to implement your solutions quickly and effectively
• Constantly measure, analyze, and produce insights and visibility on performance to keep improving user satisfaction with our products and store
• Work with growth, marketing, product, support, and management to better understand where data can be useful and ‘move the needle’
• Support upper management in tasks that will bolster user satisfaction, product recommendations, or strategy.

REQUIRED SKILLS & EXPERIENCE

• B.S.c in a highly quantitative field such as Computer Science/Mathematics / Physics/Industrial Engineering or equivalent academic knowledge
• 1+ years of programming experience
• High proficiency in Python and SQL
• Strong outstanding analytical & technical skills
• Able to quickly learn new tools and data analysis methods
• A self-learner, not afraid to explore new areas of research
• A team player and a can-do attitude, delivery oriented
• Excellent spoken and written English.

NICE TO HAVE (BIG ADVANTAGE)

• Experience working directly with marketing / product analytics teams
• Experience with AWS data services, especially AWS Glue, AWS MWAA (Airflow) or Amazon Redshift
• Familiarity with BI tools, preferably Looker
• Experience working in agile environments using Jira

Шукаємо у команду Senior DevOps / SRE Engineer (Remote).

Якщо ви маєте бажання працювати в невеликому колективі разом із сильною командою, радо розглянемо ваш відгук! Ми шукаємо не лише сильного DevOps Engineer, а й інженера із досвідом Site Reliability Engineering (SRE), який готовий брати на себе технічне лідерство, ділитися знаннями та допомагати розвиватися іншим членам команди. Націлені на довгострокову співпрацю з компенсацією, що базуватиметься на вашому досвіді роботи.
 

Завантаженість: повна зайнятість — 40 год/тиждень. Робота віддалена. Оплата погодинна.
 

Стек технологій:

- Scripting: Bash | Python | Makefile

- Containers and Orchestration: Kubernetes | Docker | GKE

- Infrastructure as Code (IaC): Terraform | Ansible

- CI/CD & Automation: GitHub Actions | CircleCI | TravisCI

- Cloud Providers & IaaS: AWS | GCP | Azure | Hetzner

- Databases: SQL | NoSQL (PostgreSQL, Redis…)

- Authorization and Security: OpenSSL

- Observability and Monitoring: Prometheus | Grafana | ELK Stack (Elasticsearch, Logstash, Kibana)

- Operating Systems: Linux
 

Site Reliability Engineering (SRE):
- SLI / SLO / SLA | Incident Response | Root Cause Analysis (RCA) | - High Availability | Capacity Planning | Disaster Recovery | 
- Performance Optimization | Reliability Engineering | 
 

Буде плюсом:

- Infrastructure Management: Developing and implementing infrastructure, configuration, and code branching strategies.

- Quality Assurance & Testing: Conducting integration, regression, UI/UX, API, load/stress, and other types of testing.

- Bug Tracking & Issue Management: Identifying, documenting, and tracking software defects and bugs.

- Performance & Optimization: Monitoring and analyzing quality metrics to identify areas for improvement.

- Automated Testing: Experience with automated testing frameworks such as Selenium, Appium, JMeter, etc.

Mentoring & Leadership:
- Досвід менторингу Junior/Middle інженерів, проведення code review, технічних обговорень, knowledge sharing та допомоги команді у професійному розвитку.
 

Вимоги до кандидата:

- Досвід роботи DevOps Engineer та практичний досвід Site Reliability Engineering (SRE)
- Досвід побудови та підтримки високодоступних production-систем із високими вимогами до reliability.

- Досвід роботи з Kubernetes у production-середовищі

- Розуміння принципів високої доступності, масштабування та відмовостійкості систем

- Досвід побудови та підтримки CI/CD процесів

- Англійська мова — Intermediate+

- Уміння слідувати code conventions

- Здатність навчатися

- Здатність наполегливо працювати

- Критичне мислення

- Витривалість

- Спроможність лаконічно та чітко пояснювати свою думку

- Бажання ділитися знаннями, проводити менторинг та допомагати розвиватися іншим членам команди

- Відданість нашим проєктам

- Прозорість
 

Що отримаєте:

- Віддалені умови роботи

- Удосконалення навичок планування та продуктивності

- Робота у вимогливому, але дружньому середовищі серед A-гравців

- Регулярний зворотний зв'язок і допомога в плануванні вашого навчального процесу та кар'єрного зростання

- Незалежність від місцевого ринку та долучення до глобальної економіки

- Підвищення рівня володіння англійською мовою

- Корпоративні навчання, технічні воркшопи та тренінги для постійного підвищення кваліфікації

Important: after confirming your application on this platform, you’ll receive an email with the next step: completing your application on our internal site, LaunchPod. So keep an eye on your inbox and don’t miss this step — without it, the process can’t move forward.

Why join us

If you're looking for a place to grow, make an impact, and work with people who care, we'd love to meet you! :)

About the role

We are looking for a Senior Application Security Engineer to architect and build automated security layers within the SDLC, engineering AI-enabled secure code scanning, hardened baseline automation, and CI/CD security tooling integration within a large-scale financial services program. You will work primarily in Python to build automated security runbooks, deploy and tune scanning tools, and provide code-level remediation guidance to development teams — operating with full autonomy and no daily supervision. AppSec and DevSecOps experience is strongly preferred; SAST/DAST/SCA and Java expertise are a plus.

What you will do

• Engineer and deploy AI-enabled secure code scanning capabilities and "Golden Images" to drive secure-from-the-start adoption;
• Automate the development of secure coding patterns and integrate them with traditional and Agentic SDLC workflows;
• Architect the integration of continuous security scanning tools (SAST, DAST, SCA) into enterprise CI/CD pipelines, tuning them to eliminate noise;
• Act as a senior technical SME, reading and reviewing complex application code (Java/Python) to provide software engineers with highly specific, code-level remediation guidance.

Must haves

• 5+ years of software engineering experience, ideally with a focus on Application Security and DevSecOps;
• Strong coding and architectural proficiency in Python for security automation and scripting;
• Fully autonomous execution capability, requiring no daily supervision to map out and build automated security runbooks;
• Upper-intermediate English level.

Nice to haves

• Deep, hands-on expertise deploying and tuning modern application security testing tools, including SAST, DAST, and SCA, and integrating them into complex CI/CD orchestration ecosystems;
• Experience integrating LLMs, AI agents, or automated coding assistants to streamline vulnerability triaging or secure code generation;
• Advanced application threat modeling experience;
• Ability to confidently read, review, and secure enterprise source Java code.

The benefits of joining us

• Professional growth

Accelerate your professional journey with mentorship, TechTalks, and personalized growth roadmaps

• Competitive compensation

We match your ever-growing skills, talent, and contributions with competitive USD-based compensation and budgets for education, fitness, and team activities

• A selection of exciting projects

Join projects with modern solutions development and top-tier clients that include Fortune 500 enterprises and leading product brands

• Flextime

Tailor your schedule for an optimal work-life balance, by having the options of working from home and going to the office – whatever makes you the happiest and most productive.

Meet Our Recruitment Process

Asynchronous stage – An automated, self-paced track that helps us move faster and give you quicker feedback:

• Short online form to confirm basic requirements
• 30–60 minute skills assessment via Codility – a platform founded in Poland that helps us provide quicker feedback and streamline this stage of the process.
• 5-minute introduction video

Synchronous stage – Live interviews

• Technical interview with our engineering team (scheduled at your convenience)
• Final interview with your future teammates

If it’s a match — you’ll get an offer!

🚀 We are looking for a Middle+/Senior Data Engineer to join a long-term data platform project.

 

The role is focused on designing, building, and maintaining reliable data pipelines and cloud-based data platforms for high-load business environments. The ideal candidate has strong hands-on experience with Python, SQL, ETL/ELT processes, and AWS data services.

🎯 Responsibilities

 

- Design, build, and maintain scalable batch and near-real-time data pipelines.

- Develop ETL/ELT workflows using Python, SQL, and modern data engineering tools.

- Integrate data from APIs, databases, files, SaaS platforms, and event-based sources.

- Build and support data lakes, data warehouses, and analytics-ready datasets.

- Improve pipeline performance, reliability, scalability, and cost efficiency.

- Implement data quality checks, monitoring, logging, validation, and alerting.

- Troubleshoot production data issues and identify root causes.

- Collaborate with data analysts, BI engineers, data scientists, software engineers, and business stakeholders.

- Maintain technical documentation, data models, and pipeline specifications.

- Contribute to CI/CD, infrastructure automation, and cloud platform improvements.

 

🧩 Requirements

 

- 3+ years of commercial experience in Data Engineering or a closely related role.

- Strong hands-on experience with Python.

- Strong SQL skills, including complex transformations and query optimisation.

- Practical experience building and maintaining production-grade ETL/ELT pipelines.- Experience working with AWS data services, particularly S3 and at least one of the following:

  - AWS Glue;

  - Athena;

  - EMR;

  - Redshift;

  - Lambda.

- Experience with at least one orchestration or transformation tool such as Airflow, dbt, Prefect, Dagster, or similar.

- Experience working with at least one cloud data warehouse or data platform such as Snowflake, Databricks, BigQuery, or Redshift.

- Strong understanding of data warehousing, data lakes, data modelling, partitioning, and file formats.

- Experience implementing data quality checks, monitoring, and error handling.

- Experience with Git and CI/CD workflows.

- Ability to independently investigate issues, make technical decisions, and take ownership of delivery.

- English level: Upper-Intermediate or higher.

 

🧩 Nice to Have

 

- Experience with Spark or PySpark.

- Experience with Kafka, Kinesis, Pub/Sub, or other streaming technologies.

- Experience with Delta Lake, Apache Iceberg, or Apache Hudi.

- Experience with Terraform, AWS CDK, or another Infrastructure as Code tool.

- Experience with Docker or Kubernetes.

- Experience with high-load or analytics-heavy products.

- Experience with GCP or Azure data services.

- Experience supporting AI/ML or LLM-related data pipelines.

🧩You'll have an opportunity to:

Build scalable data platforms using modern cloud technologies.

Work with large datasets and production-grade data pipelines.

Collaborate with experienced international engineering teams.Solve complex data engineering challenges across different industries.

Continuously develop your technical expertise with modern data tools and cloud services.

Take ownership of features and contribute to high-quality engineering practices.

We are looking for a hands-on Senior Computer Vision Engineer to join a long-term product engineering team. The client builds hardware and software platforms for real-world outdoor mapping, inventory, and environmental analysis. This is not a standard image classification task on clean laboratory datasets. Our models process visual and sensor data captured on the go in dynamic, unpredictable outdoor environments (varying lighting, motion blur, complex natural backgrounds, changing distances). Your main focus won't be just reading R&D papers, but diagnosing where existing models fail, running experiments, and turning those experiments into robust production improvements.

Key Responsibilities:

• Analyze, improve, and optimize production CV models for object detection, segmentation, and depth analysis.
• Diagnose model errors.
• Build evaluation and experimentation pipelines for real-world, noisy data.
• Work with data captured from moving camera systems / wearables.
• Optimize inference pipelines for production integration.
   

Requirements:

• 3+ years of commercial experience in Computer Vision & ML (Python, PyTorch).
• Proven experience taking CV models into production.
• Strong expertise in Object Detection, Instance/Semantic Segmentation, or Depth Estimation.
• Solid understanding of training pipelines, dataset quality, data augmentation, and inference optimization.

• Ability to work independently on applied ML problems.

  
   

Nice to Have:

• 3D & Spatial CV: Monocular/stereo depth estimation, RGB-D, Point Clouds, Camera Geometry.

• Sensor & Navigation: SLAM, Visual-Inertial Odometry (VIO), Sensor Fusion, LiDAR.

   

• We offer:
• Flexible working schedule
• Fully remote work
• Compensation for medical, educational and sports activities
• Professional growth opportunities
• Internal knowledge-sharing talks
• Awesome team events and activities
• Paid vacation and sick leave
   

Description

We are seeking a highly skilled Сonsultant Data Engineer to be the driving force behind this massive architectural shift. You will be hands-on in moving a highly complex, highly regulated data ecosystem from an on-premise Teradata environment to a cutting-edge AWS “Lakehouse” architecture.
In this role, you will focus on building robust data pipelines, modernizing legacy code, and ensuring flawless data delivery. You will work closely with System Analysts, Automation Engineers, and Data Architects to convert hundreds of legacy scripts into modern dbt models, orchestrate them via Astronomer (Airflow), and establish governed warehousing in Databricks.

Requirements

• Cloud Platforms: Hands-on engineering experience within the AWS ecosystem (S3, IAM, Glue) and deep expertise in Databricks (SparkSQL, PySpark, governed cataloging).
• Modern Data Stack: Strong proficiency in dbt (Core or Cloud) for data transformation and understanding of modern table formats, specifically Apache Iceberg.
• Orchestration: Experience building and maintaining data pipelines using Apache Airflow (Astronomer experience is a strong plus).
• Languages: Expert-level SQL (ability to read Teradata SQL/BTEQ and write highly optimized Spark/Databricks SQL) and strong Python skills for pipeline development and Airflow DAGs.
• Legacy Systems: Familiarity with Teradata architecture and utilities (FastExport, BTEQ) to effectively understand the source systems being decommissioned.

Experience & Qualifications

• Experience: 7+ years of dedicated Data Engineering experience, with a proven track record in complex data migration projects (On-Premise to Cloud).
• Financial Services Background: Experience working in a highly regulated banking or financial services environment is strongly preferred, particularly within Risk or Finance domains.
• Engineering Best Practices: Strong grasp of CI/CD for data pipelines, Git version control, data modeling (Kimball/Inmon), and infrastructure as code (Terraform).
• Communication: Ability to work collaboratively in a fast-paced, cross-functional agile team, effectively communicating technical blockers to technical leads and project managers.

Job responsibilities

• Lakehouse Engineering: Build and maintain scalable data pipelines to migrate Consumer Risk datasets from Teradata to Amazon S3, utilizing Apache Iceberg for the lakehouse layer and Databricks for governed warehousing.
• Code Modernization (BTEQ to dbt): Perform complex code conversions, transforming up to 500 legacy Teradata BTEQ scripts into modular, version-controlled, and highly performant dbt (data build tool) models.
• Pipeline Orchestration: Design, develop, and monitor complex Directed Acyclic Graphs (DAGs) using Astronomer (Apache Airflow) to orchestrate end-to-end data workflows.
• Data Lineage & Transparency: Integrate pipelines with OpenLineage to ensure complete, end-to-end data traceability, providing the transparency required for regulatory compliance.
• Reconciliation & Parity: Work alongside the QA/Automation team to execute automated reconciliation frameworks, debugging and resolving data discrepancies to ensure strict attribute-level parity and timing equivalence during governed parallel runs

What we offer

Our goal is to build an inclusive positive culture where everyone can feel comfortable being themselves, empowering people to create their own high standards and therefore more value. We work together to promote fairness while recognising, valuing and embracing differences – providing a transparent support structure and generous training budget to help our people develop skills to progress their career. Our region supports a hybrid model that can flex across a wide spectrum of working options determined by business, customer and individual needs.

You'll benefit from a comprehensive health and wellness plan, private healthcare (clinical and mental wellbeing), discounted gym memberships, and in office yoga sessions and massages. We offer a fantastic benefits package including a competitive pension scheme and recognition schemes through bonus/reward initiatives. Colleagues are entitled to an annual volunteering day – so you can take time to support a cause close to your heart. We also love to stay social with trips to the zoo, quiz nights, sports events, theatre trips and much more.

We are an equal opportunities employer. It is our policy to promote an environment free from discrimination, harassment and victimisation, and we actively welcome applications from people with a disability or long-term health condition. As users of the Disability Confident scheme, we guarantee to interview all disabled applicants who meet the minimum essential criteria for this vacancy.

The company is a healthcare data analytics provider offering modern data infrastructure, reporting, and AI‑driven insights. Their technology focuses on improving how healthcare organizations manage, analyze, and use clinical data.

Core Solutions

•  Healthcare data platform: Consolidates structured and unstructured patient data in near real time to create a unified data foundation.

•  Longitudinal clinical data ecosystem: Enables comprehensive management and analysis of patient information.

•  Patient engagement platform: Integrates data from multiple sources to support secure communication and holistic patient care.

•  Population health management suite: Aggregates clinical and claims data, identifies at‑risk groups, and supports interventions to improve outcomes and reduce costs.

•  Care coordination and analytics tools: Provide a complete view of patient data to enhance quality, reduce costs, and support risk stratification.

•  AI and analytics services: Transform healthcare data into actionable insights for better care and operational efficiency.

Main expectations:
1.  Strong Python 3.x backend development (Flask + multithreading)
2.  Solid SQL skills and hands‑on experience with PostgreSQL
3.  Practical experience with BigQuery and Google Cloud services
4.  Containerization skills (Docker/Podman) and basic Kubernetes knowledge
5.  ETL/ELT pipeline experience and large‑scale data processing

Conditions:

• Compensation: 5500–6500 USD/month

• Contract: B2B

• Remote‑friendly