Jobs Data Engineer

We're building a real-time startup & investor data platform — the data is the product, served to customers via API, a BigQuery feed, and MCP. 

The core challenge
Many of our pipeline processes are currently coupled and run sequentially not as parallelizable as we need. As we scale into millions of records and add tons of new data points, we want an architecture that lets us add sources and processes independently, run them in parallel, and scale cleanly. That's the heart of this role.

What you'll do

• Re-architect coupled, sequential pipelines into modular, parallelizable ones that scale to millions of records.
• Design scalable pipeline architecture on GCP-based services.
• Add new datasets end to end: structured extraction, LLM-based parsing, clean storage in Supabase / BigQuery with well-defined schemas.
• Build eval frameworks for our LLM calls so we can route the right model to the right use case mixing OpenAI with open-source models (e.g. Gemma) deliberately, not by default.
• Integrate scraping providers (Scrapfly, Bright Data) and handle the occasional hard source (Cloudflare, captchas) as we approach new datasets.

What we're looking for

• 4+ years building data pipelines, backend services, and automated data processing at scale.
• Strong track record designing scalable, parallelizable pipeline architecture — decoupling dependent processes, orchestration, throughput.
• Deep ETL and web-scraping experience (e.g. Scrapy, Playwright for dynamic sources); comfort working through providers like Scrapfly / Bright Data.
• Hands-on with GCP (BigQuery a plus), Airflow, PostgreSQL, FastAPI, and Docker.
• Practical LLM-pipeline experience building evals and choosing models for cost/quality per use case.
• Fluent English.

We care more about depth in scalable pipeline architecture, ETL, and scraping than about an exact stack match if you've built these systems well with adjacent tools, we want to talk.

Details

• Engagement: [contract / full-time]
• Location: [remote]

Adaptiq, on behalf of AppsFlyer, is looking for a Data Engineer

About AppsFlyer (Kyiv):

AppsFlyer provides a SaaS marketing analytics platform that measures and optimizes marketing activities across mobile, web, CTV, PC, and console applications. AppsFlyer is known for its massive backend production. At any given moment, thousands of servers are consuming 150+ billion mobile app events, crunching our users’ data, serving requests, and communicating on a massive scale.

To maintain the universe we call AppsFlyer, we practice modern production operations with a complete self-serve CI/CD platform, a highly integrated observability stack for our micro-services, backends, and infrastructure, a culture of ownership and eagerness for quality.

The Analytics group is responsible for showing our clients the stories their data is telling. Through complex aggregation, mission-tailored analytical databases, and carefully crafted APIs we are able to provide slice-and-dice analysis in our beautiful dashboards and through the use of external integrations.

About the Role:

As a Data Engineer in AppsFlyer’s Analytics group, you will be responsible for the full lifecycle of event data — from ingestion and processing to storage, modeling, and delivery through APIs.

You will build and maintain data pipelines with Apache Airflow and Spark, evaluate and optimize analytical databases, and integrate new components within a hybrid microservices architecture. You will work closely with product managers and cross-functional engineering teams, handle production issues, and take part in the company’s migration toward Google Cloud and BigQuery.

This role provides a high level of ownership over feature design, direct impact on a platform processing billions of events every day, and opportunities to contribute to open-source initiatives or share expertise at industry events.
 

Key Responsibilities:

• Develop and support data processing pipelines using Apache Airflow, Scala Spark, or PySpark.
• Select, design, and optimize analytical databases for high-volume, low-latency queries.
• Build backend services and APIs for data ingestion, aggregation, and customer-facing data consumption.
• Monitor system reliability and performance, investigate issues, and resolve production incidents.
• Partner with product managers and engineering teams to plan, design, and deliver complex features.
• Support migration initiatives to Google Cloud Platform, BigQuery, and modern data technologies.
• Participate in on-call rotations, PagerDuty alerts, and incident response processes.
• Document architecture, data flows, and technical decisions while maintaining high code quality and test coverage.
   

Required Competence and Skills:

• 3+ years of software development experience with a strong focus on data engineering.
• Hands-on experience with Apache Spark, using either Scala or PySpark.
• Practical experience with Apache Airflow.
• Background in building and maintaining distributed data systems with high throughput and low latency.
• Strong SQL knowledge and experience with data modeling for analytical use cases.
• Experience with JVM-based languages such as Scala, Java, or Clojure, or Python for backend development.
• Experience with cloud platforms, preferably GCP, and data warehouses such as BigQuery.
• Proven ownership of production systems, including on-call responsibilities and incident management.
• Strong English communication skills for working in a distributed environment.
• B.Sc. in Computer Science or equivalent practical experience.
   

Nice to Have:

• Production experience with large-scale databases and ETL tools.
• Hands-on experience with backend services written in Go or Clojure.
• Experience building production-grade BigQuery ETL processes and data pipelines.
• Contributions to open-source projects or experience speaking at meetups, conferences, or industry events.
• An AI-oriented mindset, including familiarity with tools such as GitHub Copilot and modern AI-assisted workflows.
  
  Benefits Package:
• Health insurance.
• Paid unlimited vacation days, national holidays, and additional recharge days.
• Meal reimbursement.
• Sport reimbursement.
• Breakfast in the office.
• Mental health program.
• Team buildings, happy hours, and other team activities.
• Paid sick leave.
• Snacks, fruits, and ice-cold beer in the office.
• Brand-new Mac laptop, two monitors, and a starter package for every new team member.

Project Description:

The primary goal of the project is the modernization, maintenance and development of an eCommerce platform for a big US-based retail company, serving millions of omnichannel customers each week.

Solutions are delivered by several Product Teams focused on different domains - Customer, Loyalty, Search and Browse, Data Integration, Cart.

Current overriding priorities are new brands onboarding, re-architecture, database migrations, migration of microservices to a unified cloud-native solution without any disruption to business.

Responsibilities:

We are looking for Data Engineer who will be responsible for designing a solution for a big retail company. The main focus is to support processing of big data volumes and integrate solution to current architecture.

Mandatory Skills Description:

• Readiness to work until 8.00 pm CET (no need to do overtimes)
• Overall years of experience required 8+ (at least 1+ year in a Lead/Architect position)
• Strong, recent hands-on expertise with Azure Data Factory and Synapse is a must (3+ years).
• Strong expertise in designing and implementing data models, including conceptual, logical, and physical data models, to support efficient data storage and retrieval.
• Strong knowledge of Microsoft Azure, including Azure Data Lake Storage, Azure Synapse Analytics, Azure Data Factory, and Azure Databricks, pySpark for building scalable and reliable data solutions.
• Extensive experience with building robust and scalable ETL/ELT pipelines to extract, transform, and load data from various sources into data lakes or data warehouses.
• Ability to integrate data from disparate sources, including databases, APIs, and external data providers, using appropriate techniques such as API integration or message queuing.
• Proficiency in designing and implementing data warehousing solutions (dimensional modeling, star schemas, Data Mesh, Data/Delta Lakehouse, Data Vault)
• Proficiency in SQL to perform complex queries, data transformations, and performance tuning on cloud-based data storages.
• Experience integrating metadata and governance processes into cloud-based data platforms
• Certification in Azure, Databricks, or other relevant technologies is an added advantage
• Experience with cloud-based analytical databases.
• Experience with Azure MI, Azure Database for Postgres, Azure Cosmos DB, Azure Analysis Services, and Informix.
• Experience with Python and Python-based ETL tools.
• Experience with shell scripting in Bash, Unix or windows shell is preferable.
• Demonstrated ability to lead cross-functional engineering teams, define technical strategy and architecture, drive delivery of complex data platforms, mentor engineers, and effectively communicate with stakeholders at all organizational levels.

Nice-to-Have Skills Description:

• Experience with Elasticsearch
• Familiarity with containerization and orchestration technologies (Docker, Kubernetes).
• Troubleshooting and Performance Tuning: Ability to identify and resolve performance bottlenecks in data processing workflows and optimize data pipelines for efficient data ingestion and analysis.
• Collaboration and Communication: Strong interpersonal skills to collaborate effectively with stakeholders, data engineers, data scientists, and other cross-functional teams.
• Ability to plan, estimate and track progress of implementing features
• Computer Science and data science academic and education credentials

Languages:

English: B2 Upper Intermediate

We are embarking on a critical initiative to achieve ISO 81001 compliance for our esteemed client. ISO 81001 is a pivotal standard for health informatics, specifically focusing on the management and security of health information systems. This project aims to ensure Client's digital infrastructure aligns with the stringent requirements set forth by ISO 81001, safeguarding sensitive healthcare data and bolstering cyber resilience.

Responsibilities:

Conduct a thorough assessment of Client's existing IT infrastructure, policies, and procedures against ISO 81001 requirements.
Identify gaps and vulnerabilities that need to be addressed to achieve compliance.
Collaborate with cross-functional teams to design and implement robust security controls aligned with ISO 81001 standards.
Deploy necessary security measures to protect Client's health information systems and data assets.
Draft and enhance security policies, procedures, and guidelines tailored to ISO 81001 specifications.
Ensure policies are communicated effectively and integrated into Client's operational framework.
Perform risk assessments and develop risk management strategies to mitigate cyber threats and vulnerabilities.
Implement proactive measures to enhance Client's cyber resilience in alignment with ISO 81001.
Conduct training sessions and workshops to enhance cyber security awareness among Client staff.
Foster a culture of security consciousness and best practices across the organization.
Establish monitoring mechanisms to track ongoing compliance with ISO 81001 requirements.
Conduct regular audits and assessments to ensure sustained adherence to security standards.
Develop incident response protocols and procedures to swiftly address and mitigate security incidents.
Continuously assess and refine security strategies based on emerging threats and industry developments.

Mandatory Skills:

Bachelor's degree in Cyber Security, Information Technology, or a related field.
Proven experience in cyber security, particularly in compliance initiatives (ISO standards preferred).
Strong understanding of health informatics and data security within healthcare environments.
Excellent analytical skills with the ability to assess complex systems and processes.
Effective communication skills to engage stakeholders and drive security initiatives forward.

Nice-to-Have Skills Description:

Agile

Project Description:

We are embarking on a critical initiative to achieve ISO 81001 compliance for our esteemed client. ISO 81001 is a pivotal standard for health informatics, specifically focusing on the management and security of health information systems. This project aims to ensure Client's digital infrastructure aligns with the stringent requirements set forth by ISO 81001, safeguarding sensitive healthcare data and bolstering cyber resilience.

Responsibilities:

Conduct a thorough assessment of Client's existing IT infrastructure, policies, and procedures against ISO 81001 requirements.
Identify gaps and vulnerabilities that need to be addressed to achieve compliance.
Collaborate with cross-functional teams to design and implement robust security controls aligned with ISO 81001 standards.
Deploy necessary security measures to protect Client's health information systems and data assets.
Draft and enhance security policies, procedures, and guidelines tailored to ISO 81001 specifications.
Ensure policies are communicated effectively and integrated into Client's operational framework.
Perform risk assessments and develop risk management strategies to mitigate cyber threats and vulnerabilities.
Implement proactive measures to enhance Client's cyber resilience in alignment with ISO 81001.
Conduct training sessions and workshops to enhance cyber security awareness among Client staff.
Foster a culture of security consciousness and best practices across the organization.
Establish monitoring mechanisms to track ongoing compliance with ISO 81001 requirements.
Conduct regular audits and assessments to ensure sustained adherence to security standards.
Develop incident response protocols and procedures to swiftly address and mitigate security incidents.
Continuously assess and refine security strategies based on emerging threats and industry developments.

Mandatory Skills Description:

Bachelor's degree in Cyber Security, Information Technology, or a related field.
Proven experience in cyber security, particularly in compliance initiatives (ISO standards preferred).
Strong understanding of health informatics and data security within healthcare environments.
Excellent analytical skills with the ability to assess complex systems and processes.
Effective communication skills to engage stakeholders and drive security initiatives forward.

Nice-to-Have Skills Description:

Agile

We are looking for a Data Engineer with 3+ years of commercial experience to help build and scale a modern data platform. In this role, you will work on developing and maintaining data pipelines, creating data models, and ensuring data quality and reliability.

Requirements:

• 3+ years of experience in data engineering or backend development.
• Experience with Java development
• Strong knowledge of SQL and database technologies.
• Hands-on experience with ETL/ELT processes and data modeling.
• Understanding of modern data architectures (data lakes, data warehouses).
• Experience with cloud platforms (AWS, GCP, or Azure) is a plus.
• Experience with big data technologies (e.g., Spark, Kafka, Hadoop) is a plus.
• Experience integrating AI/analytics solutions into data workflows is a plus.
• Understanding of software engineering best practices, including testing, CI/CD, and version control.
• Strong problem-solving and communication skills.
• Ability to collaborate effectively in a distributed team environment.
• Availability for 1–2 hours of overlap with U.S. Central Time business hours (9:00 AM — 5:00 PM CT).

• Experience working in an Agile environment.

   

Key Responsibilities

• Build and maintain scalable ETL/ELT pipelines and data architectures.
• Develop and optimize data models for analytics and reporting needs.
• Integrate data processing and analytics solutions to improve data workflows.
• Translate business and technical requirements into reliable data solutions.
• Implement data quality checks and monitor pipeline performance.
• Troubleshoot data issues and improve reliability and scalability.
• Participate in code reviews and follow data engineering best practices.
• Work with cloud services and data processing tools to optimize performance and costs

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 building a Customer Data Platform (CDP) that ingests data from 10+ casino partners, builds a unified player profile, and activates marketing campaigns through multiple ESPs (DotDigital, Adestra, FastTrack).

The platform is live: 5 sources in production, 30-40 dbt models in the silver layer, working email campaigns through DotDigital.

You’ll join a Data Platform team of 5-10 engineers (Senior DE, QA, DA, PM) reporting to the Data Engineering Lead. You will own the ingestion layer, source integrations, and platform tooling. Your job: make it so that connecting a new data source takes days, not months. You’ll design and build reusable pipeline templates and own integrations with external systems (both inbound and outbound).

This is not a “write one pipeline and move on” role. This is “build the system that generates pipelines” + own the integrations that feed and consume data.

Why this role

Connecting a new data source currently takes 2-3 months. Your job: make it 5 days. This is a data platform engineering challenge, not a pipeline writing task.

This is the group’s flagship project. The CDP improves how the company works with players across all brands and directly generates revenue through better marketing activation.

The platform is 4 months old, modern stack, zero legacy. But already in production with real traffic, real campaigns, real money. You’re scaling a working system, not prototyping in isolation.

The core challenge is designing a system where adding a new data partner is a configuration. You’ll solve problems across the full spectrum: API design, schema evolution, orchestration patterns, data quality, and delivery to downstream consumers.

Key Responsibilities

• Design and build ingestion pipelines for REST API, database sources, etc., using Python
• Own ETL and Reverse ETL end-to-end, including implementation, deployment, operations, and incident handling.
• Understand how external systems work (casino platforms, ESPs, affiliate tools) to build reliable integrations with them.
• Design DAG patterns: dependency management, partial retry, backfill procedures.
• Implement and maintain authentication flows, token refresh handling, and secrets management.
• Monitor, troubleshoot, and resolve integration issues in production environments.
• Write and maintain automated tests to ensure the 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.
• Write Architecture Decision Records (ADRs) for significant design choices.

Skills & Experience

Must have:

• 6+ years in data engineering.
• Advanced Python: API clients, file processing, schema validation, integration logic.
• Deep Airflow experience: DAG design, dynamic generation, sensors, retry patterns, backfill, pools, connections management.
• dbt (mid+): bronze/silver models, source freshness, tests, materialisation strategy.
• Snowflake (mid): external stages, COPY INTO, storage integration, basic optimisation.
• API integration experience: authentication (OAuth, API keys), pagination, rate limiting, retry with backoff, error classification.
• Proven experience building reusable pipeline frameworks/templates that others use daily.
• Reverse ETL or outbound integration experience: pushed data from the warehouse to external systems.
• Writes clear documentation: architecture decisions, pipeline templates, and onboarding guides for the team.
• CI/CD pipeline design (GitHub Actions).

Nice to have:

• Terraform basics.
• Metadata-driven / config-driven pipeline experience.
• Experience with ESP platforms (DotDigital, SendGrid, Braze, or similar).
• Gambling, marketing, or multi-tenant data platform experience.
• Comfortable using AI coding assistants.

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.

Be a Key Member of the GTM Team at a Video Marketing SaaS that is Powering 10,000s Entrepreneurs’ Businesses

This is not a typical product engineering role, rather you’re gonna be the key technical person, as a fullstack engineer who gets marketing, for the GTM teams @ Vidalytics. Reporting to the CEO who owns these functions. LFG! 

You’ll own tracking, attribution, and all things technical for the marketing and revenue teams.

You will get a crash in marketing, revenue generation, as we’re on the bleeding edge in these regards in many ways. 

These teams move fast, are very data driven and you’d be supported by the larger engineering team, the director of engineering, the director of business intelligence, and other folks from cross-departmental teams. 

We’re Vidalytics.com. A video marketing platform that helps entrepreneurs scale their businesses in the face of bigger, better-funded competitors. We do this with the advanced tools in our video marketing & hosting platform. We’re 9 years old and growing at a sustainable pace each year. And you’re going to be a part of the team that will add a few zeros to that growth rate. 

What You’ll Be Doing (Job Tasks) 

• Own, implement and deploy tracking and attribution across our customer journeys  (Webflow, Vercel, JS snippets), backend, and marketing automations  
• Help marketers get vibe coded projects over the finish line, such as landing pages and small apps creation through Claude Code, Codex, etc. 
• Work closely with the CEO (who doubles as our CMO and Chief Revenue Officer) and our Director of Business Intelligence to super charge GTM data insights 
• Translate vague or loosely defined ideas into concrete, scoped tracking implementations
• Build & deploy fullstack steaks to our web app for GTM tests and tweaks we’re testing. 
• Help the marketing team go AI Native, be more technical and self-sufficient. 
• Add backend hooks and logic to capture events and customer actions server-side. 
• Help maintain attribution integrity across touchpoints, including CRM and ad platforms
• Help deploy server side split tests.
• (Nice-to-have) Write SQL queries to explore data and build funnel or campaign dashboards

Requirements 

• Fullstack engineer who gets marketing 
• Experience with web attribution practices
• Professional experience with AI tools such as Claude Code, Codex, Loveable, Figma Weavy, etc.
• Know your way around page speed analysis tools to squeeze out every ms of latency
• Experience with n8n, Zapier or similar low-code automation tools
• Experience with marketing funnels, ideally Direct Response as well as Google Tag Manager, Meta CAPI, Google Ads, etc. 
• Solid JavaScript skills, especially in-browser tracking and event handling
• Backend fundamentals: you can hook into backend logic and write some code
• Ability to wrangle 3rd party tools like Typeform, Calendly, Webflow, etc.
• Excellent written and verbal English communication
• Strong sense of ownership and ability to work independently with vague or partial specs
• Comfortable aligning data between frontend, backend, and external systems like HubSpot and Intercom
• SQL experience for ad-hoc queries and funnel validation
• Your working hours need to have a strong overload w/ Eastern US time zone. Can discuss further. 

Nice-to-have 😃

• PostHoq & HogQL experience (this is the center of our attribution)
• Dashboarding/visualization experience with Grafana 
• Familiarity with MixPanel or similar product analytics tools
• Basic familiarity with GCP services
• Exposure to Video Marketing
• Experience with Meta's Conversion API Gateway and Signals Gateway
• Knowing your way around the odd reverse proxy setup (for maximizing accuracy through maintaining 1st party tracking infrastructure)
• GDPR, HIPPA and other regulation knowledge

Our Tech & Tooling Stack 🛠

• Frontend: Webflow, React SPA App, custom / Claude Code / Lovable 
• Backend: GCP, PHP 8, Go, Node.js
• Tracking & Attribution: Posthog, MixPanel, GTM, Meta Pixel/CAPI, Google Ads, custom 
• CRM & Automation: HubSpot, Intercom, Chargify, Stripe
• Data & Analytics: BigQuery, MySQL, Grafana, MixPanel, PostHog (for marketing analytics only)
• Widgets: Typeform, Calendly
• AI: Claude, Loveable, Figma Weavy, Midjourney, Perplexity, ChatGPT, Vercel…
  
   

Who You Are (Personality Type) 🦁

• You’re a translator between marketing and code: you ask the right questions, fill in gaps, and get things done.
• Biased toward shipping fast. You deliver in small, valuable chunks.
• Breaking down ambiguous requests? Easy. You enjoy untangling marketing noise into technical tasks.
• Self-organized and proactive. You don’t wait for instructions, you move.
• Clear communicator. You explain technical ideas well – written and verbal.
• You measure twice, cut once. Getting it First-Time-Right is your default.
• Direct and constructive. You give and receive honest feedback with care and clarity.
   

What You’ll Love About Us (Benefits and Perks) 😉

• High performance company culture. You won’t be a cog in a machine. Rather you’ll be a key member of a high performance team that is getting shit done. This is a place to grow and realize your potential, no matter what level you’re at in your career. 
• No office politics. We’re small and flat. There is no bullshit of trying to dance around sensitive topics. Divert resources from other division’s projects. We’re direct, we’re honest, we’re here to accomplish big audacious goals. 
• We value your ideas. At Vidalytics, my door is always open. Need help? Let’s talk! Have a vision for the future of the company? I want to hear it! Think I suck at my job? Help me grow! 
• Rest and relaxation. Employees get 20 days of PTO. 
• Professional development. Want to continue your education? Vidalytics pays for classes, conferences, and more.
• You’re more than an employee, you’re a person. Every co-worker you’ll meet is committed to treating you with respect and kindness. You won’t hear stuff like, “It’s just business.”
• This is a resume-making position, where you’ll learn a lot and have a lot of responsibility. You don’t have to wait for someone to die or retire to move up, like in a mega-corp. 
• Entrepreneurial to our core – Not only are we a startup, but we need intrapreneurs that will help us scale, and we’re looking to start other sister corps in time to form a portfolio of companies, which you could be a co-founder of.

Vidalytics’ Values 

(Yes, We’re Actually Serious About These) 😇

Play to Win – We’re competitors. We do what it takes to win. This means that we will fail, we will lose, but we want to do these things fast… because winning only comes after trial and error. Default paves the way to success. Or…  winning is on the other side of mistakes. 

Scrappy  – We’re a startup, it’s chaotic. This isn’t the government. You need to be able to learn fast, move fast and handle it. You need to be able to survive in a scrappy entrepreneur environment. This means often you need to figure it out but yet also not wander in the desert. We will be there with you, but if you want an easy job, go work at the government. 

Meritocracy – The best idea wins, not who it comes from… This means you can be direct & transparent with anyone. Test your ideas starting with analysis, form hypotheses, test small, measure results, iterate, and scale big with data. We can’t have perfect data. So when a decision is made, get on board. 

Own Yourself – We do what we say, and own what we’ve done. Mistakes happen. But the worst thing that can happen is when someone doesn’t own and learn from them. You trust us. We trust you. 

Self Actualization – This is a place for hyper learning. We want to scale. You need to scale with us, this doesn't always mean climbing some ladder, but upleveling skill – closing gaps, growing and being self actualized. 

Conscious Teamwork – No politics. No bullshit. Rather integrity, emotional intelligence, transparency and curiosity. Attack ideas, not people. 

Cheers,

👨🏻‍🦲

Patrick Stiles

CEO @ Vidalytics

We are seeking a Site Reliability Engineer; this is a fully remote job in the European time zone.

What You'll Be Doing

• Configuring and optimizing Nginx, php-fpm, PostgreSQL, ElasticSearch, Redis, RabbitMQ in production (daily routine)
• Monitoring system health with Prometheus, Victoria Metrics, Icinga, Opsgenie, Jira Service Management (daily routine)
• Managing cloud infrastructure: compute, storage, IAM, VPCs, load balancers
• Ensuring high availability and responding to incidents
• Participating in monthly on-call rotation (1 shift/month, 24h, with compensating days off)

Must Have

• Linux (RHEL) is required
• TCP/IP networking, firewalls, routing, load balancing
• Production experience with Nginx, php-fpm, PostgreSQL, ElasticSearch, Redis, RabbitMQ
• Monitoring stack: Prometheus, Victoria Metrics, Icinga, Opsgenie
• Cloud infrastructure management (any major cloud)
• English - Upper-Intermediate spoken (required)

Nice to Have

• Terraform, Ansible, Jenkins, GitLab CI
• Docker, Kubernetes, Helm
• Puppet DSL, PuppetDB
• ELK / OpenSearch stack

Conditions

• FOP contract
• Schedule: local business hours, Mon–Fri + 1 on-call shift/month (24h) with 2 compensating days off
• 24 vacation days/year

About the Project

We're looking for a Senior Data Engineer to join an early-stage AI platform where you'll have the opportunity to shape the data architecture from the ground up.

The project is currently in the discovery and platform design phase. Together with AI and backend engineers, you'll build a scalable data platform powering next-generation AI applications, including Retrieval-Augmented Generation (RAG), AI Agents, intelligent document processing, and LLM-driven workflows.

This is a greenfield project where you'll be involved in architectural decisions, technology selection, and designing reliable data pipelines for AI systems.

What You'll Do

• Design and implement scalable data ingestion pipelines
• Build reliable ETL/ELT workflows for structured and unstructured data
• Design data models for analytics and AI workloads
• Build and optimize data pipelines supporting RAG and AI Agent systems
• Ensure data quality, governance, observability, and reliability
• Optimize performance and infrastructure costs
• Collaborate with AI Engineers on vector search, embeddings, and retrieval pipelines
• Participate in architecture discussions and technology selection

• Contribute to platform scalability and production readiness

   

Required Skills

• 5+ years of commercial Data Engineering experience
• Strong Python development skills
• Experience designing ETL/ELT pipelines
• Understanding RAG architectures
• Experience working with cloud platforms (AWS, Azure, or GCP)
• Strong understanding of data modeling
• Experience with PostgreSQL or other relational databases
• Strong experience with vector databases
• Experience building scalable data processing systems
• Understanding of Data Warehouses, Data Lakes, or Lakehouse architectures

Nice to Have

• Apache Airflow
• Kafka
• dbt
• Snowflake
• Redis
• LangChain
• LangGraph
  
  If you're interested, feel free to send your CV

We are looking for a Data Engineer to join our team and play a key role in building scalable, reliable, and business-focused data products from the ground up. This is a great opportunity to contribute to the development of core data infrastructure, influence technical decisions, and help establish best practices in data engineering across the organization.

Responsibilities:

• Build data engineering products (data models, pipelines, data quality automations, monitoring), end-to-end ownership of data products.
• Collaborate closely with data analysts, PMs, and stakeholders on both new and existing data products

• Apply best engineering CI/CD practices to data workflows and processes

   

Requirements:

• 3+ years of experience in Data Engineering, Analytics Engineering, or a related field
• Strong knowledge of SQL, Python, and dbt
• Hands-on experience with ELT/ETL, data quality, and analytics engineering
• Experience working with cloud platforms such as AWS, GCP, or Azure

• Experience with cloud data warehouses such as Databricks, Snowflake, BigQuery, Redshift, or similar

   

Nice to have:

• Strong attention to automation
• DevOps background
• Product engineering mindset (focus on business impact, not just data engineering)
• Experience with BI tools and delivering impactful analysis

We are looking for an Integration Engineer.

 In this role, you will design and scale data pipelines that process large volumes of advertising data, ensure stable data synchronization across external marketing platforms, and lead new integration initiatives from API evaluation to production rollout. You will play a key role in shaping the platform’s integration strategy and building scalable, AI-enabled integration solutions that power our core data infrastructure.

Requirements
- 5+ years in backend/data engineering, including 2+ years working with advertising/marketing APIs.
- Hands-on experience with Meta Marketing API and/or LinkedIn Marketing API: real work with rate limits, async reports, breakdowns, attribution windows.
- Strong Python skills: production-grade code with error handling, logging, and tests.
- Solid understanding of data pipeline patterns: idempotency, backfill, incremental sync, schema evolution.
- Experience with GCP or comparable cloud (AWS/Azure) at the service design level.

- Actively use AI-assisted development tools (e.g., Copilot, Cursor, Claude Code) in daily engineering workflows for code generation, debugging, documentation, and data pipeline design, applying sound engineering judgment when validating AI-generated outputs.

Nice to Have
- Knowledge of the Programmatic ecosystem: DV360, The Trade Desk, OpenRTB.
- Experience with BigQuery and/or ClickHouse.
- Pulumi / Terraform for IaC.
- Understanding of advertising metrics: impressions, clicks, conversions, ROAS, attribution models.

Responsibilities
- Own the architecture and evolution of all platform integrations: Meta Marketing API, LinkedIn Marketing API, Programmatic channels (DV360, The Trade Desk, etc.).
- Lead a team of 2-4 engineers: code reviews, sprint planning, mentorship.
- Design and maintain data pipelines: Ad Platform APIs to BigQuery/ClickHouse via Cloud Run Jobs and n8n workflows.
- Ensure data sync reliability: monitoring, alerting, error handling, retry strategies.
- Work with API rate limits, OAuth flows, and webhooks across advertising platforms - Drive new integration projects from API evaluation through production rollout. 
- Collaborate with the product team to prioritize the integration roadmap.

What We Offer

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

Вимоги до володіння мовами

Англійська – Вище середнього

Українська - Носій мови

Data Engineer, Meta Marketing API, LinkedIn Marketing API, Python, Claude Code

Про компанію InsulaLabs

Insula Labs is a Ukrainian IT company.
We build skilled, talented teams that are committed to the long-term game. The main business model is outstaffing, which allows clients to quickly scale their teams thanks to access to our highly qualified specialists. 90% of our people are based in Ukraine. Work is organized in a remote format for everyone.
Our goal is to become a driving force for the successful projects of our partners, forming powerful teams that set the pace and achieve results. We strive for long-term cooperation in which each team member plays a key role and achieves professional growth.

Are you passionate about building cutting-edge, AI-ready data platforms from the ground up? We are looking for a Senior Data Engineer to join our Data Engineering Team and lead high-impact, greenfield initiatives.

You will work on building modern cloud-native data platforms, migrating on-premises legacy systems to the cloud, and laying the architectural foundation for AI-ready data infrastructure.

In this role, you will collaborate closely with Machine Learning, Data Science, and Product teams, serving as a key technical contributor and thought leader. You will also drive R&D efforts around agentic AI architectures, event-driven systems, and LLM-ready data pipelines — turning architectural concepts into production-grade solutions.

Responsibilities:

• Design and build scalable, cloud-native data platforms from greenfield to production
• Implement near-real-time ingestion pipelines using event-driven patterns
• Define and enforce platform standards, including Data Lake / Lakehouse principles, medallion architecture, and data contracts
• Refactor and optimise existing Spark and PySpark scripts for performance and maintainability
• Introduce best practices for code quality, testing, and CI/CD across data pipelines
• Drive adoption of AI tooling and agentic workflows within the data engineering team
• Ensure data quality, observability, and reliability across all pipelines and platforms

• Develop self-service tooling and microservices to simplify platform usage for other teams

   

Requirements:

• 5+ years of professional experience in Data Engineering
• Strong Python and SQL development skills for pipeline development and optimisation
• Proficiency in Apache Spark / PySpark, including query optimisation and performance tuning
• Hands-on experience with Databricks (preferred) or Snowflake
• Experience with at least one major cloud provider: Azure (preferred), AWS, or GCP
• Experience with stream processing technologies (Kafka, Spark Structured Streaming)
• Solid understanding of ETL/ELT patterns, data modelling (dimensional, Data Vault), and data warehousing
• Experience with orchestration tools (Apache Airflow, Azure Data Factory, or equivalent)
• Knowledge of Infrastructure as Code (Terraform or equivalent)
• Understanding of production-grade system requirements: reliability, scalability, observability, and performance

• Upper-Intermediate English level

   

Will be a plus

• Familiarity with RAG pipeline design and LLM integration patterns
• Knowledge of data governance frameworks and tools (Unity Catalog, Apache Atlas, or similar)
• Experience with dbt for data transformation and modelling

• Familiarity with MLflow, Feature Stores, or ML platform integration

   

Personal profile

• Self-driven and proactive in identifying improvements
• Comfortable working in a fast-paced, innovative environment
• Strong problem-solving mindset with attention to detail
• Open to experimenting with emerging technologies and approaches

_____________________________________________________________

Ти захоплюєшся створенням передових, AI-ready дата-платформ з нуля? Ми шукаємо Senior Data Engineer, щоб ти приєднався(-лася) до нашої команди Data Engineering та очолив(-ла) масштабні, інноваційні ініціативи з нуля.

Ти працюватимеш над побудовою сучасних хмарних дата-платформ, міграцією локальних (on-premises) легасі-систем у хмару та створенням архітектурного фундаменту для AI-ready дата-інфраструктури.

У цій ролі ти тісно співпрацюватимеш з командами Machine Learning, Data Science та Product, виступаючи ключовим технічним експертом та лідером думок. Також ти вестимеш R&D-роботи над agentic AI-архітектурами, подієво-орієнтованими системами та LLM-ready дата-пайплайнами — перетворюючи архітектурні концепції на готові до продакшену рішення.

Обовʼязки:

• Проєктувати та створювати масштабовані, хмарні дата-платформи від концепції до продакшену
• Реалізовувати пайплайни для майже реального часу (near-real-time ingestion) з використанням подієво-орієнтованих патернів
• Визначати та впроваджувати стандарти платформи, включно з принципами Data Lake / Lakehouse, медальйонною архітектурою та дата-контрактами
• Рефакторити та оптимізувати наявні скрипти на Spark та PySpark для підвищення продуктивності та зручності підтримки
• Запроваджувати найкращі практики якості коду, тестування та CI/CD для дата-пайплайнів
• Сприяти впровадженню AI-інструментів та agentic-підходів у команді дата-інженерів
• Забезпечувати якість, спостережуваність (observability) та надійність усіх пайплайнів і платформ

• Розробляти self-service інструменти та мікросервіси, що спрощують використання платформи іншими командами

   

Вимоги:

• 5+ років комерційного досвіду в Data Engineering
• Сильні навички розробки на Python та SQL для створення та оптимізації пайплайнів
• Впевнене володіння Apache Spark / PySpark, включно з оптимізацією запитів та налаштуванням продуктивності
• Практичний досвід роботи з Databricks (бажано) або Snowflake
• Досвід роботи з принаймні одним великим хмарним провайдером: Azure (бажано), AWS або GCP
• Досвід роботи з технологіями потокової обробки даних (Kafka, Spark Structured Streaming)
• Глибоке розуміння ETL/ELT-патернів, моделювання даних (dimensional, Data Vault) та побудови дата-складів
• Досвід роботи з інструментами оркестрації (Apache Airflow, Azure Data Factory або аналогами)
• Знання Infrastructure as Code (Terraform або аналогів)
• Розуміння вимог до продакшен-рішень: надійність, масштабованість, спостережуваність, продуктивність

• Рівень англійської — Upper-Intermediate

   

Буде плюсом:

• Знайомство з проєктуванням RAG-пайплайнів та патернами інтеграції LLM
• Знання фреймворків і інструментів для data governance (Unity Catalog, Apache Atlas або подібних)
• Досвід роботи з dbt для трансформації та моделювання даних

• Знайомство з MLflow, Feature Stores або інтеграцією з ML-платформами

   

Особистий профіль:

• Самомотивованість та проактивність у пошуку покращень
• Комфортна робота у швидкому та інноваційному середовищі
• Сильне аналітичне мислення та увага до деталей
• Відкритість до експериментів з новими технологіями та підходами

Client: USA
Format: Outstaff
Workload: Full-time
Duration: Long-term

We're looking for a Senior Data Engineer to join an early-stage AI product where you'll have an opportunity to influence the architecture from day one.

The project is currently in the discovery and platform design phase. We're building a scalable AI data platform focused on data ingestion, processing, retrieval, and LLM-powered workflows.

Requirements:
 - 5+ years of Data Engineering experience

 - Build data ingestion and transformation workflows
 - Strong ETL/ELT experience in cloud environments

 - Design data models for analytical and AI workloads
 - Advanced SQL and relational database design
 - Optimize data quality, performance, and reliability

 - Collaborate with AI Engineers on RAG pipelines and vector search

 - Participate in architecture discussions and technical decision-making

If you're interested, feel free to send your CV

At Promova, we’re redefining language education for the AI-powered era — making learning accessible, personal, and inspiring for millions of people worldwide. Our 150+ teammates unite around one mission: to connect people, bridge cultures, and empower lifelong learners — in every country except aggressor states (yes, even Antarctica).

We blend AI innovation with human creativity to help people speak with confidence and truly belong anywhere. If you want to test bold ideas, move fast, and make an impact — you’ll feel right at home.

About the Role

We are looking for a Data Engineer who will own and shape the data infrastructure that powers every analytical and AI-driven decision at Promova.

In this role, you’ll build a reliable, scalable data platform — not dashboards or one-off reports, but the foundation that lets anyone in the organization get answers on their own, with the help of AI agents and without waiting on a middleman.

Clean, well-documented, trustworthy data is the product. You will own it end to end: from raw source intake to the final datasets that power marketing, product, and business decisions at scale.

Why This Role Is Your Next Challenge

• Direct Business Impact: The data platform you build is the infrastructure the entire company runs on. Every team — marketing, product, etc — depends on the reliability and quality of what you ship. This is foundational work that scales with the business.
• AI-First Culture: You won’t be figuring out AI alone. We have a dedicated squad focused on AI adoption and a full setup ready to use: Claude Desktop connected to Tableau, Notion, and our internal data sources. You’ll be building the data layer that makes AI agents actually useful.
• Multiproduct Ecosystem: As Promova expands into new products, you’ll integrate new data sources and adapt pipelines — building once in a way that scales across the whole ecosystem from day one.

What We’re Looking For
Core experience:

• 2+ years of hands-on experience as a Data Engineer or in a similar data infrastructure role.
• Strong SQL proficiency and practical experience working with cloud data warehouses (BigQuery preferred).
• Experience designing and maintaining ETL/ELT pipelines and layered data warehouse architecture (raw → stage → final).
• Hands-on experience with pipeline orchestration tools (Airflow, MWAA, or Cloud Functions): task dependencies, error handling, retry logic, failure recovery.
• Solid understanding of data quality practices: validation, NULL/duplicate handling, freshness and consistency monitoring.

Bonus points:

• Experience in subscription-based products (web and/or mobile).

What You Will Do

• Develop and optimize the data warehouse (BigQuery): design and maintain the raw → stage → final layer architecture.
• Connect and integrate new data sources: product, payment, marketing, internal services — into a unified pipeline.
• Orchestrate and ensure pipeline reliability: manage task dependencies, error handling, retry logic, and recovery from failures.
• Maintain data quality: build validation checks, handle NULLs and duplicates, monitor freshness and consistency.
• Prepare data as a product for AI agents: clean, documented, predictable datasets that can be trusted without manual verification.
• Contribute to analytical tasks where automation falls short, and support the team through the transition to self-service analytics.

Corporate Benefits
🎓Growth — offered to help develop your skills, advance your career, and reach your full potential: сompensation for additional training at external events and seminars; access to a large electronic library; paid online courses and conferences;

🧘🏼Wellbeing — offered to support your overall health, happiness, and resilience: work remotely from any safe location worldwide; flexible work schedule; 20 paid vacation days per year; an unlimited number of sick days, medical insurance coverage; mental health support; power station reimbursement; employee discounts and special benefits for remote employees.

🏄🏼‍♂️Fun & Activities — offered to foster informal communication and strengthen social connections among teammates: remote team compensation for gathering and team-building episodes.

Interview Process

• Intro-call with Recruiter
• Meeting with the Hiring Manager
• Bar-raising

Interested? Apply now and let’s make the growth happen!