Jobs Data Engineer

• Project Description:

  Join the Data Engineering team to contribute to the ongoing maintenance and improvement of an internal assistant that uses hosted 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)
  • 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
  • Operate the platform in production: observability (logs/metrics/tracing), alerting, incident support, performance tuning, and cost controls, plus runbooks and handover documentation

   

• Mandatory Skills Description:

  8+ years of hands-on experience in Data Science and 2+ 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
  Solid experience with OpenSearch
  Familiarity with AWS cloud platform and its 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
  Strong English skills (B2 and higher)
  Strong verbal and written communication skills.
  Ability to work independently and collaborate in a group.

   

• Nice-to-Have Skills Description:

  Agile certification
  Oracle/Microsoft attestations and certifications
  Domain knowledge - Trading and Capital Markets

   

• Languages:
  • English: C1 Advanced

We are seeking a Principal-level Cloud Integration Engineer to architect and own the middleware layer connecting our CRM (Salesforce) with the wider enterprise ecosystem. You will spearhead the transition toward highly scalable, event-driven microservices within an AWS environment, ensuring seamless data synchronization, system security, and robust API lifecycle management.

This is a high-impact, individual contributor role requiring deep technical maturity, architectural foresight, and an uncompromising standard for code quality.

Core Responsibilities

• Architectural Ownership: Design and evolve cloud-native integration patterns between Salesforce and core internal systems.
• System Integration: Develop, deploy, and maintain high-performance microservices using Kotlin/Java.
• Scalability: Implement event-driven architectures and API gateways to ensure system reliability and low-latency data sync.
• Infrastructure Excellence: Maintain CI/CD pipelines, IaC, and Kubernetes-based deployments in AWS.
• Quality Assurance: Drive test-automation initiatives and enforce API security best practices across the integration layer

Requirements 

• Technical Core: Extensive production experience with Kotlin or Java (Quarkus/Spring Boot).
• Integration Expertise: Advanced understanding of RESTful API design, messaging queues, and event-driven patterns.
• Cloud & Infrastructure: Hands-on command of AWS, Kubernetes, and Docker.
• DevOps Culture: Strong background in CI/CD, Infrastructure as Code, and production-grade monitoring.
• Communication: Exceptional English proficiency, capable of leading technical discussions with stakeholders.

Preferred ("Top-Tier") Qualifications

• Production experience with Kafka / AWS MSK.
• Experience with GitOps workflows (ArgoCD, Kargo).
• Domain familiarity with the Salesforce API ecosystem.

About the role and client:
We are looking for an Scraping Engineer who will design, build, and operate large-scale, resilient web scraping systems, with a focus on Google and Google-like search environments. This role sits at the intersection of data engineering, reverse engineering, and systems reliability, and is critical to delivering accurate, timely, and trustworthy data at scale. Our client is a leader in adopting coding with AI tools. The role is ideal for someone who believes in agentic coding and would like to improve their skills.

Responsibilities:
- Design and maintain large-scale Python scraping systems that operate reliably against Google and other highly defended websites
- Build scrapers for dynamic, JavaScript-heavy pages using browser automation and hybrid approaches
- Continuously adapt to changes in page structure, request flows, and anti-automation mechanisms
- Engineer robust extraction pipelines that prioritise data accuracy, consistency, and observability
- Implement proxy, fingerprinting, and request-routing strategies to maximise stability and throughput
- Monitor scrape health, detect failures early, and rapidly debug production issues
- Optimise performance, cost, and latency across scraping infrastructure
- Work closely with data engineers, data scientists, and product teams to ensure scraped data is usable and trusted
- Document scraping logic and operational runbooks for long-term maintainability

Requirements:
- Professional experience with Python (or another main language, i.e. GoLang, Rust, JavaScript) including production-grade scraping systems
- Experience scraping Google or similarly protected platforms
- Understanding of HTTP, TLS, cookies, headers, redirects, and browser networking behaviour
- Experience with tools such as Playwright, Selenium, Puppeteer, or equivalent browser automation frameworks
- Knowledge of HTML parsing, DOM traversal, and data extraction techniques
- Experience handling rate limiting, CAPTCHA, IP rotation, and bot detection systems
- Comfortable working with asynchronous and concurrent scraping architectures
- Experience running scrapers at scale in cloud environments
- Debugging skills and ability to reason about complex failure modes
- Experience with headless browser fingerprinting and anti-bot evasion techniques

Nice-To-Have:
- Familiarity with containerisation and orchestration, such as Docker and Kubernetes
- Experience with distributed task systems and job queues
- Background in data quality monitoring and anomaly detection
- Experience working with search, advertising, or competitive intelligence data

What the client offers:
- Startup Engineering culture
- Remote working
- Strong Culture
- Award-Winning Product
- Stock Options
- Trust-Based Vacation
- Flexible Work
- Career Growth
- Monthly Hackdays & Training Days
- Family Care Package
- Home Office Stipend
- Swag Welcome Gift
- Birthday Day Off
- Regular Socials
- Volunteer Days

Description

The Digital Health organization is technology team which focused on next generation Digital Health capabilities which deliver on the Medicine mission and vision to deliver Insight Driven Care. This role will operate within the Digital Health Applications & Interoperability subgroup of the broader Digital Health team, focused on patient engagement, care coordination, AI, healthcare analytics & interoperability amongst other advanced technologies which enhance our product portfolio with new services, while improving clinical & patient experiences.

The project is a cloud-based PaaS Ecosystem built with a privacy by design centric approach to provide a centralized cloud-based platform to store, classify, and control access to federated datasets in a scalable, secure, and efficient manner.

The ecosystem will allow Customer Operating Units (medical device departments) to store federated data sets of varying sizes and formats and control access to those data sets through Data steward(s). Source data sets can be exposed to qualified use cases and workflows through different project types.

The Healthcare Data Platform ecosystem will provide ML/AI project capabilities for streamlined development processes and a ML/AI workbench to enhance data exploration, wrangling, and model training.

In queue: 15+ OU’s. At this moment focused on – Nuero, Cardio, Diabetes is the OU that data platform is working with, but there could be more OU’s coming up with requirements in future.

GL Role: is to work on the enhancement of current capabilities, including taking over the work that AWS proserve team is doing, and develop new requirements that will keep coming from different OU’s in the future.

Requirements

• AWS Platform: Working experience with AWS data technologies, including S3, AWS RDS, and Lake Formation
• Programming Languages: Strong programming skills in Python
• Data Formats: Experience with JSON, XML, and other relevant data formats
• CI/CD Tools: Ability to deploy using established CI/CD pipelines using GitLab CI, Jenkins, Terraform or similar tools
• Scripting and automation: experience in scripting languages such as Python, PowerShell, etc.
• Monitoring and Logging: Familiarity with monitoring & logging tools like CloudWatch, Splunk, ELK, Dynatrace, Prometheus
• Source Code Management: Expertise with GitLab
• Documentation: Experience with markdown and in particula,r Antora for creating technical documentation
• Previous Healthcare or Medical Device experience
• Experience implementing enterprise grade cyber security & privacy by design into software products
• Experience working in Digital Health software
• Experience developing global applications
• Strong understanding of SDLC;
• Experience with Agile methodologies
• Software estimation
• Experience leading software development teams onshore and offshore

Job responsibilities

• Implement data pipelines using AWS services such as AWS Glue, Lambda, Kinesis, etc
• Implement integrations between the data platform and systems such as Atlan, Trino/Starburst, etc
• Complete logging and monitoring tasks through AWS and Splunk toolsets
• Develop and maintain ETL processes to ingest, clean, transform and store healthcare data from various sources
• Optimize data storage solutions using Amazon S3, AWS RDS, Lake Formation and other AWS technologies.
• Document, configure, and maintain systems specifications that conform to defined architecture standards, address business requirements, and processes in the cloud development & engineering.
• Participate in planning of system and development deployment as well as responsible for meeting compliance and security standards.
• Actively identify system functionality or performance deficiencies, execute changes to existing systems, and test functionality of the system to correct deficiencies and maintain more effective data handling, data integrity, conversion, input/output requirements, and storage.
• Document testing and maintenance of system updates, modifications, and configurations.
• Leverage platform process expertise to assess if existing standard platform functionality will solve a business problem or customization solution would be required.
• Test the quality of a product and its ability to perform a task or solve a problems.
• Perform basic maintenance and performance optimization procedures in each of the primary operating systems.
• Ensure system implementation compliance with global & local regulatory and security standards (i.e. HIPAA, SOCII, ISO27001, etc…)

Description

The Digital Health organization is technology team which focused on next generation Digital Health capabilities which deliver on the Medicine mission and vision to deliver Insight Driven Care. This role will operate within the Digital Health Applications & Interoperability subgroup of the broader Digital Health team, focused on patient engagement, care coordination, AI, healthcare analytics & interoperability amongst other advanced technologies which enhance our product portfolio with new services, while improving clinical & patient experiences.

The project is a cloud-based PaaS Ecosystem built with a privacy by design centric approach to provide a centralized cloud-based platform to store, classify, and control access to federated datasets in a scalable, secure, and efficient manner.

The ecosystem will allow Customer Operating Units (medical device departments) to store federated data sets of varying sizes and formats and control access to those data sets through Data steward(s). Source data sets can be exposed to qualified use cases and workflows through different project types.

The Healthcare Data Platform ecosystem will provide ML/AI project capabilities for streamlined development processes and a ML/AI workbench to enhance data exploration, wrangling, and model training.

In queue: 15+ OU’s. At this moment focused on – Nuero, Cardio, Diabetes is the OU that data platform is working with, but there could be more OU’s coming up with requirements in future.

GL Role: is to work on the enhancement of current capabilities, including taking over the work that AWS proserve team is doing, and develop new requirements that will keep coming from different OU’s in the future.

Requirements

MUST HAVE

• AWS Platform: Working experience with AWS data technologies, including S3, AWS RDS, Lake Formation
• Programming Languages: Strong programming skills in Python
• Data Formats: Experience with JSON, XML and other relevant data formats
• CI/CD Tools: Ability to deploy using established CI/CD pipelines using GitLab CI, Jenkins, Terraform or similar tools
• Scripting and automation: experience in scripting language such as Python, PowerShell, etc…
• Monitoring and Logging: Familiarity with monitoring & logging tools like CloudWatch, Splunk, ELK, Dynatrace, Prometheus
• Source Code Management: Expertise with GitLab
• Documentation: Experience with markdown and in particular Antora for creating technical documentation 

NICE TO HAVE

• Previous Healthcare or Medical Device experience
• Experience implementating enterprise grade cyber security & privacy by design into software products
• Experience working in Digital Health software
• Experience developing global applications
• Strong understanding of SDLC; experience with Agile methodologiesSoftware estimation
• Experience leading software development teams onshore and offshore
• Experience with FHIR

Job responsibilities

• Implement data pipelines using AWS services such as AWS Glue, Lambda, Kinesis, etc
• Implement integrations between the data platform and systems such as Atlan, Trino/Starburst, etc
• Complete logging and monitoring tasks through AWS and Splunk toolsets
• Develop and maintain ETL processes to ingest, clean, transform and store healthcare data from various sources
• Optimize data storage solutions using Amazon S3, AWS RDS, Lake Formation and other AWS technologies.
• Document, configure, and maintain systems specifications that conform to defined architecture standards, address business requirements, and processes in the cloud development & engineering.
• Participate in planning of system and development deployment as well as responsible for meeting compliance and security standards.
• Actively identify system functionality or performance deficiencies, execute changes to existing systems, and test functionality of the system to correct deficiencies and maintain more effective data handling, data integrity, conversion, input/output requirements, and storage.
• Document testing and maintenance of system updates, modifications, and configurations.
• Leverage platform process expertise to assess if existing standard platform functionality will solve a business problem or customization solution would be required.
• Test the quality of a product and its ability to perform a task or solve a problems.
• Perform basic maintenance and performance optimization procedures in each of the primary operating systems.
• Ensure system implementation compliance with global & local regulatory and security standards (i.e. HIPAA, SOCII, ISO27001, etc…)

Join the Data Engineering team to contribute to the ongoing maintenance and improvement of an internal assistant that uses hosted 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)
• 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
• Operate the platform in production: observability (logs/metrics/tracing), alerting, incident support, performance tuning, and cost controls, plus runbooks and handover documentation

Mandatory Skills:

8+ years of hands-on experience in Data Science and 2+ 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
Solid experience with OpenSearch
Familiarity with AWS cloud platform and its 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
Strong English skills (B2 and higher)
Strong verbal and written communication skills.
Ability to work independently and collaborate in a group.

Nice-to-Have Skills:

Agile certification
Oracle/Microsoft attestations and certifications
Domain knowledge - Trading and Capital Markets

Join the Data Engineering team to contribute to the ongoing maintenance and improvement of an internal assistant that uses hosted 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)
  • 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
  • Operate the platform in production: observability (logs/metrics/tracing), alerting, incident support, performance tuning, and cost controls, plus runbooks and handover documentation

• Mandatory Skills Description:

  8+ years of hands-on experience in Data Science and 2+ 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
  Solid experience with OpenSearch
  Familiarity with AWS cloud platform and its 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
  Strong English skills (B2 and higher)
  Strong verbal and written communication skills.
  Ability to work independently and collaborate in a group.

• Nice-to-Have Skills Description:

  Agile certification
  Oracle/Microsoft attestations and certifications
  Domain knowledge - Trading and Capital Markets

The DataOS team at AppsFlyer is building and operating a reliable, high-scale data platform that powers analytics and product capabilities across the company.
We process more than 150 billion events per day and manage petabyte-scale historical data. Our team owns much more than a traditional “data lake” — including schema management, ETL pipelines, and interfaces to and from storage.

If you’re excited by scale, ownership, and building production-grade data systems, we’d love to meet you.

Tech stack highlights

Key technologies include:

• Processing and streaming: Spark, Kafka
• Data lake and formats: S3, Parquet, Delta Lake, Iceberg, Hadoop, Hive
• Cloud and compute: AWS, EMR/EMR Serverless, Athena
• Analytics and data platforms: BigQuery, BigLake, Aerospike, AWS Glue, Databricks Delta Engine
• Languages: Scala, Python (team focus), plus a broader polyglot engineering environment across AppsFlyer

What you’ll do:

• Design, build, and evolve large-scale data pipelines from raw ingestion to production-ready datasets.
• Develop and maintain Spark/Scala-based data processing workflows for both batch and streaming use cases.
• Own data platform reliability, quality, and performance in production environments.
• Collaborate with engineers, product owners, and stakeholders to define and deliver robust data solutions.
• Help shape engineering standards and operational practices as the DataOS team grows.

What You Bring:

• 3+ years of software engineering experience, with strong hands-on Scala and/or Java development.
• Strong Java core fundamentals.
• Proven experience with Spark and Kafka in production environments.
• Experience with the Hadoop ecosystem and distributed data processing platforms (AWS, GCP, Azure, CDP, MapR, or similar).
• Hands-on AWS experience, especially with S3 and EMR/EMR Serverless (Athena is a strong advantage).
• Experience building and operating cloud-based, high-scale distributed systems.
• Strong analytical and interpersonal skills, with the ability to work effectively across engineering and business teams.
• Professional spoken and written English.

Bonus Points:

• Knowledge of Scala is a plus.
• Experience with AWS authentication/authorization and cloud security fundamentals.
• Experience with CI/CD pipelines and tooling.
• Experience with DevOps and infrastructure-as-code tools (e.g., Terraform).
• Experience in SaaS product companies.
• Referred by an AppsFlyer employee.

Benefits:

• Health Insurance
• Paid Unlimited Vacation Days + all national holidays + additional recharge days
• Meals Reimbursement
• Sport Reimbursement
• Breakfast in the office
• Mental health program
• Team building, happy hours, and other team activities
• Paid sick days
• Snacks, fruits & ice cold beer
• All new team members are provided with a brand-new Mac laptop with 2 monitors and a Starter package

About the project

Our client is a global company with a platform managing over 700,000 hotel rooms across 124 countries, helping clients generate billions in revenue.

Why join

— Stable long-term cooperation: already 5 engineers are working on the project
— Technical freedom: ability to propose architecture decisions and improvements without heavy bureaucracy
— End-to-end ownership: work with the full data pipeline from raw data to production-ready solutions
— Direct business impact: your work helps increase hotel revenues
— Collaboration with major global hotel brands
— Fast and measurable results with clear business value

Requirements

Must have

— 5+ years of experience in Data Engineering
— 3+ years of commercial experience with AWS (including at least 1 year on the latest project)
— 2+ years of experience with Spark/PySpark (including at least 1 year on the latest project)
— Strong experience with:

• Spark / PySpark
• AWS S3
• Kafka or Kinesis
• DynamoDB
• PostgreSQL or MySQL
• AWS ECS Fargate

Nice to have

• AWS Glue
• EMR
• AWS Batch
• Flink
• Apache Beam
• Cassandra / ScyllaDB
• AWS Step Functions

Responsibilities

• Implement scaling of the case detection process (scanner)
• Split monolithic API into multiple services
• Emulate Pub/Sub and Cloud Run locally
• Extract and process data using PySpark + S3
• Work with Kafka/Kinesis pipelines (as a plus)
• Write and optimize SQL queries in PostgreSQL/Redshift
• Use DynamoDB as a data source and sink
• Run and debug ETL jobs on AWS Glue or EMR
• Monitor jobs via AWS Console and Spark UI

We are looking for an experienced Data Engineer to design and maintain robust data infrastructure across our systems. In this role, you will be responsible for building scalable data pipelines, ensuring data integrity, and integrating third-party data sources. Your primary focus will be to enable efficient data flow and support analytical capabilities across the organization. You will also contribute to the development of our data architecture, implement best engineering practices, and collaborate closely with cross-functional teams to turn raw data into actionable insights.

Requirements

• 3+ years of commercial experience in Data Engineering
• Experience gathering business requirements and communicating with stakeholders
• Strong knowledge of Data Warehouse (DWH) architecture and principles
• Hands-on experience designing data warehouses and building ETL pipelines
• Deep practical experience with Python
• Hands-on experience in one or more of the following areas: data processing using PySpark, Apache Spark, Pandas, or similar frameworks; data scraping; integration of third-party data sources and APIs
• Proficiency in SQL and relational databases such as PostgreSQL and MySQL
• Hands-on experience with column-oriented databases such ClickHouse, Snowflake, Cassandra, BigQuery (many tables with millions of records and above each)
• Solid understanding of software design patterns, algorithms, and data structures
• Intermediate English proficiency

Will be a plus

• Experience with messaging platforms such as RabbitMQ or Kafka
• Familiarity with DataOps practices and data pipeline automation
• Familiarity with CI/CD pipelines and Kubernetes environments
• Background in FinTech or Trading domains

Responsibilities

• Communicate with technical and non-technical stakeholders to gather and clarify business requirements
• Review and analyze data and business logic to ensure consistency, accuracy, and reliability
• Design, implement, and maintain data pipelines for efficient and scalable data processing
• Integrate, maintain, and support data solutions and third-party data sources
• Research and evaluate third-party tools, services, and components for potential use
• Follow engineering best practices, including code reviews, testing, refactoring, and continuous delivery
• Design, optimize, and maintain data storage solutions

What we offer:

• Tax expenses coverage for private entrepreneurs in Ukraine
• Expert support and guidance for Ukrainian private entrepreneurs
• 20 paid vacation days per year
• 10 paid sick leave days per year
• Public holidays as per the company’s approved Public holiday list
• Medical insurance
• Opportunity to work remotely
• Professional education budget
• Language learning budget
• Wellness budget (gym membership, sports gear and related expenses)

The company helps hotel chains like Hilton and Marriott transform front-desk staff into revenue generators through upselling training and analytics. Their IN-Gauge SaaS platform empowers frontline teams across 2,000+ properties in over 100 countries.

- Implement scaling of the case detection process (scanner)
- Split API into multiple API services
- Emulate pubsub/cloud run locally
- Implement scaling of the case detection process (scanner)
- Split API into multiple API services
- Emulate pubsub/cloud run locally
- Extract & process data using PySpark + S3 (Kafka/Kinesis — bonus)
- Write & optimize SQL on PostgreSQL/Redshift; use DynamoDB as data source/sink
- Run and debug ETL jobs on Glue or EMR; monitor via console/Spark UI

Must-have skills:
- Data engineering - 5 years, 
- AWS - 3 years (1 year latest project), 
- Spark/PySpark - 2 years (1 year latest project)
- English B2+

About Traffic Label

Traffic Label is a fast-growing, data-driven technology company operating in the iGaming and affiliate marketing space, building scalable products focused on performance, analytics, and automation across global markets.

Role Overview

We are looking for a Data Engineer (integration) to join our Data Platform team to help build, maintain, and scale integrations between external platforms and internal systems. Reporting directly to the Data Engineering Lead, you will focus on reliable backend services, AWS server-less infrastructure, and external API integrations that support critical business operations.
This role is fully remote across Europe and sits within the Development Department - in the Data Platform team/squad.
We are open to Seniority level here from Mid level and above.

Key Responsibilities

• Design, develop, and maintain integrations between third-party platforms and internal systems.
• Build scalable backend services and API-based integration solutions using Python.
• Manage integrations across AWS server-less infrastructure including Lambda, S3, DynamoDB, EventBridge, and related services.
• Implement and maintain authentication flows, token refresh handling, retries, pagination, polling, and async job processing.
• Monitor, troubleshoot, and resolve integration issues in production environments.
• Own integrations end-to-end, including implementation, deployment, operations, and incident handling.
• Write and maintain automated tests to ensure reliability and stability of integration services.
• Collaborate closely with Engineering, Product, and Data teams to support platform scalability and operational efficiency.
• Contribute to infrastructure improvements and Infrastructure-as-Code initiatives.

Skills & Experience

• 4+ years of backend or integration engineering experience in production environments.
• Strong Python development skills with experience building and maintaining external API integrations.
• Hands-on AWS experience including Lambda, S3, DynamoDB, EventBridge, Secrets Manager, SSM Parameter Store, and CloudWatch.
• Experience with Infrastructure-as-Code for provisioning and maintaining cloud infrastructure.
• Strong understanding of REST APIs and integration patterns.
• Experience handling authentication flows, retries, pagination, polling, and asynchronous processing.
• Strong debugging and troubleshooting skills, particularly with third-party integrations.
• Experience writing and maintaining automated tests for backend or integration services.
• Ability to work independently and take ownership of technical deliverables.
• At least 6 months of hands-on experience using AI coding agents in day-to-day development workflows.
• Experience with Airflow or similar workflow orchestration tools is considered a plus.
• Experience working with ESP or CRM platforms is considered an advantage.
• Familiarity with affiliate marketing or iGaming environments is a plus.
• Understanding of marketing data structures and identifiers is considered beneficial.

What We Offer

• Competitive salary.
• Fully remote work across Europe.
• Flexible collaboration hours and strong work-life balance.
• The opportunity to work on scalable, business-critical systems and integrations.
• A collaborative culture focused on ownership, innovation, and continuous improvement.