Jobs Data Engineer

🚀We are looking for a Middle+/Senior Data Engineer to join a long-term data platform project. The role is focused on building, maintaining, and optimizing scalable data pipelines, data warehouses, and cloud-based data platforms for high-load business environments.

The ideal candidate has strong hands-on experience with Python, SQL, Spark/PySpark, cloud data services, and modern ETL/ELT pipelines. Experience with AWS is highly important, while Databricks, Snowflake, BigQuery, dbt, Airflow, Kafka/Kinesis, and Terraform are strong advantages.

🧩Responsibilities:

• Design, build, and maintain scalable batch and near-real-time data pipelines.
• Develop and optimize ETL/ELT workflows using Python, SQL, Spark/PySpark, Airflow, dbt, or similar tools.
• Work with cloud-based data platforms and services, especially AWS.
• Build and support data lakes, lakehouse architectures, and data warehouses.
• Integrate data from APIs, databases, SaaS tools, files, and streaming/event-based sources.
• Optimize data processing performance, query execution, partitioning, and storage costs.
• Ensure data quality, reliability, monitoring, logging, and validation across pipelines.
• Collaborate with engineers, analysts, BI teams, data scientists, and business stakeholders.
• Support documentation, data modeling, and data dictionary creation where needed.
• Contribute to CI/CD, infrastructure automation, and cloud data platform improvements.

🔑Requirements:

• 3-5 years of experience in Data Engineering or closely related roles.
• Strong hands-on experience with Python, SQL, and Spark/PySpark.
• Experience building and maintaining production-grade ETL/ELT pipelines.
• Strong understanding of data warehouses, data lakes, lakehouse architectures, and data modeling.
• Experience with AWS data services such as S3, Glue, Lambda, Athena, EMR, Redshift, Firehose, Kinesis, SQS, or EventBridge.
• Experience with orchestration and transformation tools such as Airflow, dbt, Prefect, Dagster, or similar.
• Experience with at least one modern data platform: Databricks, Snowflake, BigQuery, Redshift, or similar.
• Understanding of data quality, monitoring, observability, and performance optimization.
• Experience with Git, CI/CD, Docker, Terraform, AWS CDK, or other DevOps/IaC tools.
• Ability to work independently, communicate clearly, and take ownership of delivery.

• English level: Upper-Intermediate or higher.

   

🧩Nice to Have:

• Experience with Kafka, Kinesis, Pub/Sub, or other streaming/event-driven technologies.
• Experience with Delta Lake, Iceberg, Hudi, or other lakehouse table formats.
• Experience with Kubernetes.
• Experience in high-load, fintech, healthcare, telecom, eCommerce, SaaS, or analytics-heavy products.
• Experience with BI/reporting tools such as Tableau, Looker, Metabase, Power BI, or similar.
• Exposure to AI/ML or LLM-related data workflows.
• Experience with GCP or Azure data services.

🎯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

What You’ll Own

• Build production systems for AI-driven vulnerability research and exploit development.
• Develop tooling for vulnerability discovery, triage, reproduction, and validation at scale.
• Work across OS internals, binaries, runtimes, kernels, dynamic analysis, instrumentation, and low-level performance.
• Partner with vulnerability researchers, security operators, and engineers to automate manual cyber workflows.
• Own problems end-to-end, from research and design to shipped production code.

Requirements

• 2+ years of vulnerability research, offensive security, or low-level engineering experience. Exceptional new grads with strong CTF, systems, or exploitation work will be considered.
• Hands-on experience with reverse engineering, binary analysis, exploit development, fuzzing, dynamic analysis, bug hunting, CTFs, or comparable low-level security work.
• Deep low-level systems fluency, including OS internals, kernels, runtimes, memory corruption, debugging, dynamic instrumentation, or performance-sensitive systems.
• Strong builder mindset and ability to ship reliable tools and production systems.
• Comfortable working in ambiguity and moving fast.
• Willing to relocate to Washington DC after an initial period, with full relocation support. The role is expected to be in-office 5 days per week.

Nice to Have

• Strong CTF background, especially pwn, rev, kernel, browser, or systems-heavy challenges.
• Published vulnerability research, CVEs, exploit writeups, or security talks.
• Experience with fuzzing, symbolic execution, emulation, program analysis, or binary rewriting.
• Open-source contributions to low-level security, reversing, debugging, tracing, fuzzing, or OS tooling.
• Exposure to ML / AI systems, especially applied to code, binaries, security automation, or program analysis.
• Early-stage startup, founder, or early-engineer experience.

What We Look For

• Strong vulnerability research instincts.
• Low-level technical depth.
• Builder mindset — able to turn research workflows into scalable systems.
• Comfort with ambiguity, speed, and high ownership.
• Motivation to help build a category-defining company in AI-native offensive cyber.

Must-have skills

• Ad-monetization domain (25%) — deep understanding of RTB, Header Bidding, Waterfalls, Fill Rate, eCPM/CPM optimization, and advertiser demand.
• Ad mediation platforms + mobile advertising SDKs (20%) — hands-on integration and optimization.
• Software development (20%) — strong backend, distributed systems, APIs, and performance optimization.
• Mobile development (15%) — Android and/or iOS.
• Analytical, data-driven optimization (12%) — analyze large-scale monetization data and implement data-driven improvements.
• High-scale consumer app experience (8%) — experience with high-scale consumer applications reaching millions of users.

Nice-to-have skills

• Hands-on with AppLovin MAX, Google Ad Manager, AdMob, Unity Ads, or IronSource.
• Building internal optimization engines using AI or Machine Learning.
• Familiarity with attribution, user segmentation, A/B testing, and predictive monetization models.

Responsibilities

• Design, develop, and optimize the core monetization infrastructure across multiple mobile applications.
• Improve ad waterfall and bidding performance to maximize eCPM, fill rate, ARPDAU, and total ad revenue.
• Integrate and optimize mediation platforms (AppLovin MAX, AdMob, LevelPlay, etc.).
• Build intelligent optimization systems for ad placement, frequency, segmentation, and pricing.
• Develop backend services and automation tools for real-time monetization decisions.
• Analyze monetization performance using large-scale data and implement data-driven improvements.
• Optimize SDK integrations, latency, memory usage, and overall ad performance.
• Work closely with Growth, Product, and Data teams to continuously increase LTV and user monetization.
• Research and implement new monetization technologies, bidding strategies, and demand sources.

What you'll own

• Increase overall monetization performance across millions of users.
• Maximize fill rate, eCPM, advertiser competition, and total revenue.
• Build the next generation of the monetization engine using automation and AI.
• Deliver measurable business impact through engineering excellence.

We are looking for a Senior Fabric Developer passionate about building systems that shape business outcomes. You will drive and manage large-scale data migration and modernization initiatives and work with cross-functional teams to deliver trusted, high-quality data that drives business intelligence, analytics, and innovation.

Responsibilities and Duties: 
- Strong Kimball/Medallion data warehouse expertise, delivered through Microsoft Fabric (Delta lakehouses, Spark notebooks) on an Azure SQL MI source. 
- Heavy AI-assisted development requires rigorous post-generation validation and code review. 
- Able to work near EST hours, up to 3 pm EST would be excellent, all the way to 5 pm EST would be perfect. 

Full-time remote job. 6-month contract.

Welcome to LITSLINK — a top software development company.

We are looking for a Middle AI/ML Engineer to join our growing AI practice.

You will work on client and internal projects focused on Generative AI, LLM-powered applications, AI Agents, RAG systems, Computer Vision, NLP, and intelligent automation solutions.

Please note: we are primarily looking for engineers with hands-on experience building GenAI solutions. Experience with LLMs, RAG systems, AI Agents, and AI-powered automations is highly preferred.

Tech Stack: Python, OpenAI, Anthropic, Gemini, Hugging Face, LangChain, LangGraph, LlamaIndex, RAG, AI Agents, Vector Databases, AWS/GCP/Azure

Key Responsibilities:

• Design, develop, and optimize AI-powered applications and services.
• Build solutions based on LLMs, RAG pipelines, AI Agents, and Generative AI technologies.
• Integrate AI systems with APIs, databases, and business platforms.
• Evaluate, optimize, and improve AI solutions.
• Collaborate with software engineers, product teams, and stakeholders.
• Conduct technical research and evaluate emerging AI technologies.
• Contribute to architecture decisions, code reviews, and engineering best practices.

Requirements:

• 2+ years of commercial experience in AI/ML engineering, AI Engineering, Data Science, or related roles.
• Experience building GenAI solutions is highly preferred.
• Practical experience with Generative AI and LLM-based applications.
• Hands-on experience building RAG systems, AI Agents, AI Assistants, or AI-powered automations.
• Strong Python programming skills.
• Solid understanding of Machine Learning fundamentals.
• Experience with PyTorch, TensorFlow, or the Hugging Face ecosystem.
• Experience working with OpenAI, Anthropic, Gemini, Hugging Face, or similar AI platforms.
• Experience with prompt engineering, LLM evaluation, and optimization techniques.
• Understanding of REST APIs and software development best practices.
• Strong analytical and problem-solving skills.
• Intermediate+ English level.

Nice to Have:

• Experience with LangChain, LangGraph, LlamaIndex, CrewAI, AutoGen, or similar frameworks.
• Experience with vector databases (Pinecone, Weaviate, Qdrant, Chroma, etc.).
• Experience with AWS, GCP, or Azure.
• Experience deploying AI solutions to production environments.
• Knowledge of MLOps practices and model lifecycle management.
• Experience with Computer Vision or NLP projects.
• Experience mentoring junior engineers.

What We Offer:

• Opportunity to work on cutting-edge AI projects.
• Access to modern AI tools and technologies.
• Collaborative and innovative engineering culture.
• Professional development and career growth opportunities.
• Remote-first environment.
• Competitive compensation package.

Recruitment Process:

• HR Interview
• Technical Interview
• Offer

We are seeking a Palantir Foundry & AIP Engineer with hands-on experience across the full Foundry ecosystem and Palantir’s Artificial Intelligence Platform (AIP). This role goes beyond data engineering: you will design, build, and operationalize AI-powered workflows, agents, and applications that drive tangible business outcomes. The ideal candidate is a self-starter, able to translate complex business needs into scalable technical solutions, and confident working directly with stakeholders to maximize the value of Foundry and AIP.

• Responsibilities:

  · Data & Workflow Engineering: Design, develop, and maintain scalable pipelines, transformations, and applications within Palantir Foundry.
  · AIP & AI Enablement:
  o Support the design and deployment of AIP use cases such as copilots, retrieval workflows, and decision-support agents.
  o Ground agents and logic flows using RAG (retrieval‐augmented generation) by connecting to relevant data sources, embedding/vector search, ontology content.
  o Use Ontology-Augmented Generation (OAG) when needed: operational decision making where logic, data, actions and relationships are embedded in the Ontology.
  o Collaborate with senior engineers on agent design, instructions, and evaluation using AIP’s native features.
  · End-to-End Delivery: Work with stakeholders to capture requirements, design solutions, and deliver working applications.
  · User Engagement: Provide training and support for business teams adopting Foundry and AIP.
  · Governance & Trust: Ensure solutions meet standards for data quality, governance, and responsible use of AI.
  · Continuous Improvement: Identify opportunities to expand AIP adoption and improve workflow automation.

• Mandatory Skills Description:

  Minimum 10 Years of experience in IT/Data.
  Minimum 5 years of experience as a Data Platform Engineer/Data Engineer.
  · 2+ years of professional experience with the Palantir Foundry ecosystem (data integration, ontology, pipelines, applications).
  · Strong technical skills in Python, PySpark, SQL, and data modelling.
  · Practical experience using or supporting AIP features such as RAG workflows, copilots, or agent-based applications.
  · Ability to work independently and engage directly with non-technical business users.
  · Strong problem-solving mindset and ownership of delivery.

• Nice-to-Have Skills Description:

  · Familiarity with AIP Agent Studio concepts (agents, instructions, tools, testing).
  · Exposure to AIP Evals and evaluation/test-driven approaches.
  · Experience with integration patterns (APIs, MCP, cloud services).
  · Consulting or applied AI/ML background.

Description

Our client is looking for a hands-on Principal Data Engineer & Architect to lead the design, evolution, and execution of their core data engineering ecosystem. This role is built specifically for an elite technical leader who loves mapping out highly reliable distributed architectures but is driven by a strong desire to stay close to the metal—allocating approximately 70% of their time to writing mission-critical production code, core data libraries, and internal frameworks, and 30% to high-level architectural design, data infrastructure governance, and technical mentorship.
 

About Our Client

Our client is a venture-backed, AI-powered platform built specifically for consumer brands. It connects seamlessly to fragmented external sources like banks, POS systems, and advertising platforms to deliver daily profit & loss snapshots, cash flow plans, and peer benchmarking—all in real time. With integrations stretching across finance, e-commerce, and marketing tools, the platform provides the clarity and automation brands need to grow confidently.
 

What You’ll Do

Architect Data Infrastructure (70% Focus): Maintain a heavy, hands-on presence in the codebase. Author core data processing libraries, distributed computing frameworks, and high-scale data platforms in JavaScript (Node.js/NestJS) and Python to establish gold standards for the engineering team.

Design Data Systems (30% Focus): Design and evolve a robust, multi-tenant data architecture capable of handling massive datasets and high-throughput processing across hundreds of distinct data domains concurrently.

Data Quality & Governance: Establish bulletproof data integrity and observability patterns. Focus on robust processing workflows, comprehensive data validation, automated quality checks, and end-to-end distributed tracing across the data lifecycle.

Scale Data Pipelines: Define and enforce efficient data architectures, high-throughput streaming patterns, and transaction boundaries to guarantee accurate real-time financial reporting at scale.

Technical Leadership & Mentorship: Act as an elite technical sounding board for the engineering organization. Conduct comprehensive architecture reviews, upskill senior engineers, and champion modern DevOps, testing, and deployment workflows.
 

What We’re Looking For

Deep Industry Experience: 8+ years of professional software engineering experience, with a proven history of designing, deploying, and maintaining large-scale data processing and distributed data infrastructure solutions.

Polyglot Mastery in Data Engineering: Highly proficient in both JavaScript/TypeScript (Node.js, NestJS) and Python, with the ability to build sophisticated data pipelines and distributed systems using each language’s native strengths.

Advanced Data Engineering & Architecture Expertise: Extensively experienced with distributed systems, high-scale storage solutions, query optimization, and complex data architecture patterns for massive, high-velocity datasets.

Data Modeling & Schema Excellence: Expert-level understanding of relational (SQL) and non-relational (NoSQL) databases, schema design, complex data validation, mapping workflows, and ETL pipeline design.

True Builder Mentality: A strong architectural thinker who actively rejects the “ivory-tower” approach and remains deeply passionate about shipping high-quality production code every single week.
 

Would Be a Plus

Direct technical experience within FinTech, e-commerce SaaS platforms, or real-time data streaming architectures (e.g., Kafka, RabbitMQ).

Familiarity with financial data aggregates or banking networks (e.g., Plaid, Yodlee, Stripe).

Experience setting up data ingestion pipelines optimized for downstream AI/LLM analysis models.
 

What We Offer

Highly competitive principal-level base salary + substantial early-stage equity package.

Comprehensive medical, dental, and vision insurance coverage.

Flexible, remote-first working culture with an elite engineering group.

Direct technical influence over the foundational platform architecture of a fast-growing, venture-backed startup.

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

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.

Owns the technical direction, quality, and delivery enablement of the data platform within the team. Ensures scalable architecture, reliable releases, and strong engineering practices while enabling the team to deliver efficiently within defined engineering and release standards.

• Responsibilities:

  Architecture & Technical Ownership
  • Owns end-to-end technical design across Snowflake, dbt, ADF, and Azure components
  • Acts as the final technical decision authority within the team
  • Ensures alignment with enterprise architecture and data governance standards
  • Maintains architecture documentation and diagrams
  ________________________________________
  Engineering Excellence
  • Defines and enforces coding standards and best practices
  • Reviews critical PRs and ensures maintainability and scalability
  • Drives performance optimization and cost efficiency
  • Continuously improves development efficiency by reducing technical complexity and removing bottlenecks
  ________________________________________
  CI/CD & Release Ownership
  • Owns and improves CI/CD pipelines and deployment processes
  • Defines and enforces the release process, ensuring it is standardized and consistently followed
  • Establishes release criteria based on Definition of Done, testing, and required approvals
  • Ensures all changes meet release criteria before deployment to production
  • Oversees and coordinates production releases, including validation of readiness and risk assessment
  • Has authority to block releases that do not meet defined quality and governance standards
  • Ensures pipelines enforce quality gates (tests, validations, approvals where required)
  • Continuously improves release safety and reduces production incidents
  ________________________________________
  Quality & Definition of Done
  • Ensures adherence to Definition of Done (including testing and documentation)
  • Works with QA and team to ensure test coverage aligns with acceptance criteria
  ________________________________________
  Team Enablement & Mentoring
  • Mentors engineers and supports technical growth
  • Leads knowledge sharing and supports complex problem-solving
  ________________________________________
  Planning & Delivery Support
  • Contributes to sprint planning with technical estimates, risks, and dependencies
  • Owns identification and prioritization of technical debt in collaboration with the Product Owner
  ________________________________________
  Production Ownership
  • Leads incident analysis and root cause resolution
  • Ensures monitoring, alerting, and data quality validation mechanisms are in place across pipelines and in production
  • Maintains runbooks for operational readiness
  ________________________________________
  Ways of Working
  • Collaborates closely with Product Owner and Scrum Master to align technical delivery with business priorities; supports team continuity and helps facilitate meetings when the Scrum Master is absent
  • Proactively works with upstream data source teams and other squads to resolve cross-team dependencies, data issues, and production bugs
  • Drives technical alignment across teams/squads where shared data models, pipelines, or integrations are involved
  • Acts as the primary technical point of contact for external teams and stakeholders

• Mandatory Skills Description:

  7+ experience in Data Engineering and development of DWH solutions
  Hands-on experience with Snowflake, dbt, Azure Data Factory
  Experience with Azure Cloud Solutions, Azure DevOps
  Practical experience and understanding of CI/CD processes
  Experience of technical leadership in Agile SDLC

• Nice-to-Have Skills Description:

  Experience with AWS and/or GCP cloud solutions
  Certifications related to DWH

Want to work on technologies used by data platforms at a global scale?

We’re looking for Senior and Middle+ Java Engineers to join a long-term cloud data infrastructure project focused on modern Data Lakehouse technologies, distributed systems, and open-source development.

You’ll be building integrations between data processing frameworks and cloud services, improving compatibility across the ecosystem, and contributing to technologies that power large-scale analytics platforms. If you enjoy solving complex backend challenges and working close to the open-source community, this role is for you.

What you’ll be working on

• Develop new features for large-scale data infrastructure components.
• Build integrations between distributed data processing frameworks and cloud storage services.
• Improve compatibility across modern data processing engines.
• Contribute to high-quality, production-grade backend services.
• Participate in architecture discussions and technical design.
• Collaborate with engineers across international teams and contribute to engineering best practices.

Tech stack

Must have

• Java
• Python (working proficiency)
• Experience with at least one of: Apache Flink, Spark, Kafka, or Apache Beam
• Understanding of Data Lake / Lakehouse architecture
• Experience with Google Cloud Platform (BigLake, GCS, KMS, or related services)

Nice to have

• Apache Iceberg
• Open Source contributions
• Experience with distributed systems
• Cross-system integration experience

What we’re looking for

• Strong commercial experience with Java backend development.
• Experience building data-intensive or distributed backend systems.
• Solid understanding of cloud-native architectures.
• Experience working with modern data processing technologies.
• Strong problem-solving skills and ownership mindset.
• Good communication skills and ability to work in a distributed international team.

What we offer

• Paid vacation and sick leave
• 11 official public holidays per year
• Personal Career Development Plan (CDP)
• Challenging engineering projects with modern cloud technologies
• Paid external training, conferences, and professional certifications
• Internal tech talks, workshops, and English classes
• Employee support program (healthcare, legal assistance, partner discounts)
• Corporate library with paper and e-books

If you’re excited about distributed systems, cloud data platforms, and building software that makes an impact beyond a single product, let’s talk!

Apply now or send us a message – we’d love to share more details about the project and see if it’s the right fit for you.

Acropolium, together with its international partner in the energy industry, is looking for an experienced Data Engineer to join a project focused on GDPR compliance and enterprise data lifecycle management.

You will become part of the agile Unlocking & Deletion team, responsible for developing and maintaining an end-to-end data deletion process across multiple enterprise systems. The team builds and enhances the GDPR Orchestrator, ensuring secure, compliant, and automated deletion workflows in accordance with GDPR requirements.

Project Details

• Industry: Energy
• Start Date: August 1, 2026
• End Date: December 31, 2026 (extension possible)
• Location: 100% Remote
• Workload: Full-time
• Languages: German (B2+) and English (B2+)

Responsibilities

• Develop and enhance the GDPR Orchestrator using Apache Airflow and Azure Data Factory
• Integrate new enterprise systems into the end-to-end data deletion process
• Implement new GDPR-compliant deletion scenarios across existing systems
• Optimize data deletion workflows and overall process efficiency
• Reduce technical debt and improve maintainability
• Advise the team on enhancements related to Snowflake and data selection strategies
• Collaborate with technical and business stakeholders to deliver reliable data solutions

Requirements

• Strong commercial experience with Azure Data Factory
• Strong experience with Apache Airflow
• Advanced SQL skills
• Solid understanding of Data Warehousing concepts
• Experience designing and optimizing ETL/ELT pipelines
• Good communication and stakeholder management skills
• Self-driven, organized, and proactive working style
• German – B2 or higher
• English – B2 or higher

Nice to Have

• Experience with Snowflake
• Experience with GDPR compliance and data deletion processes
• Experience working with enterprise data platforms
• Knowledge of cloud-based data architectures

Our Hiring Process

• Intro Call with Recruiter
• Technical Interview
• Client Interview
• Offer Stage

What We Offer
Culture & People-First Approach

• 💙 On average, team members stay at Acropolium for more than 5 years
• 🤝 Strong internal communication & empathy — we're human-first, KPI-second
• 👨‍👩‍👧‍👦 Family values & social engagement are encouraged
• 👋 Warm onboarding and supportive team environment
• 🗣️ Open communication, feedback culture, and support for individual growth

Employee Well-being & Development
 

• 🎖️ Ongoing care and support for employees serving in the military
• 📚 Learning culture with internal knowledge sharing and support for external courses
• 🧭 Personal Development Plans (PDPs) to support long-term career growth

Key Responsibilities  

• Design, build, and maintain scalable, reliable data pipelines (batch and streaming).  
• Develop and optimise data models, warehouses, and lakehouse architectures.  
• Build and automate CI/CD pipelines for data workflows and deployments.  
• Ensure data quality, integrity, lineage, and governance across environments.  
• Implement proactive monitoring and alerting for pipelines and data infrastructure (CloudWatch, Grafana).  
• Manage IaC for consistent, reliable data infrastructure.  
• Troubleshoot and optimise pipeline and query performance across environments.  
• Lead incident resolution and root cause analysis for data systems.  
• Collaborate with analysts, data scientists, and engineering teams, ensuring security, scalability, and operational excellence to understand data requirements and translate them into technical solutions  
• Document data architecture, lineage, and workflows  

Must have  

• 5+ years in data engineering, with solid DevOps/platform engineering exposure.  
• Strong SQL and data modelling skills (dimensional, normalised, lakehouse).  
• Proficient in Python; working knowledge of Scala, Java, or Go.  
• Hands-on experience with data pipeline/orchestration tools (Airflow, DBT).  
• Experience with distributed processing frameworks (Spark, Flink, or similar).  
• Advanced AWS expertise (Glue, EMR, Redshift, Athena, S3, Lambda, Kinesis).  
• CI/CD tools (GitHub Actions, GitLab CI, Jenkins, CircleCI).  
• Infrastructure as Code (CDK, CloudFormation).  
• Experience with streaming/event-driven architecture (Kafka, Kinesis, Apache Flink, or Pub/Sub).  
• Observability tools: Grafana, CloudWatch.  
• Expertise with data warehouse platforms (Redshift, Snowflake).  

Desirable  

• Experience with containerisation and orchestration (Docker, ECS, Kubernetes).  
• Understanding of data governance, cataloguing, and security/compliance (GDPR, lineage tools).  
• Experience with GitHub Enterprise, Atlassian APIs, and Slack bots.  
• Understanding of cost optimisation strategies in multi-cloud and data warehouse environments.  

We are looking for AI/LLM Engineer to join our team and work on cutting-edge AI solutions based on modern Large Language Models. You will be involved in building, fine-tuning, and optimizing AI systems, integrating LLMs into products, and developing scalable AI pipelines and agent-based architectures.

Requirements:

- Commercial experience with Python

- Experience with LLMs

- Strong understanding of prompt engineering

- Experience with AI agent orchestration frameworks

- English level Upper-Intermediate

Responsibilities:

- Develop and optimize AI/LLM-based solutions

- Fine-tune and customize open-source language models

- Build RAG pipelines and embedding-based search systems

- Design and maintain AI agents and orchestration flows

- Collaborate with engineering and product teams

- Research and implement new AI technologies and approaches

Nice to Have:

- Experience with LangChain, LlamaIndex, AutoGen, CrewAI, or similar frameworks

- Knowledge of GPU infrastructure and model deployment

- Experience with Docker and cloud platforms

- Understanding of transformers architecture and Hugging Face ecosystem

We are looking for a highly motivated and results-driven Head of Data & AI to join our team full-time. In this strategic role, you will shape the vision, architecture, and delivery frameworks for Data Engineering, Data Science, Quant and Data Analytics, unifying these teams into a single, high-impact function. This is a key leadership position, guiding both technical and managerial directions for our data organization.
We drive fintech innovation through deep analytical expertise and a data-first, engineering-driven approach.
 

Key Responsibilities
 

Data Engineering

• Design and evolve a scalable, reliable, and maintainable data platform architecture
• Oversee development of robust ETL/ELT pipelines and real-time data streaming systems
• Establish engineering best practices, including code reviews, CI/CD, data contracts, and observability
• Lead technology selection and resource planning across ClickHouse, Spark, and supporting infrastructure
• Ensure data quality through monitoring, alerting, SLA ownership, and remediation processes
• Manage infrastructure costs and drive optimization across storage, compute, and cloud resources
   

Artificial Intelligence & Large Language Models

• Define and develop the company's overall AI direction and roadmap, aligning initiatives with long-term business strategy
• Ensure operational stability and observability of ML services
• Define and drive LLM strategy, including identifying high-value use cases, evaluating model providers (OpenAI, Anthropic, open-source), and leading end-to-end implementation
• Architect and oversee LLM-powered products, including RAG pipelines, AI agents, and intelligent automation workflows integrated into core business processes
• Establish MLOps/LLMOps best practices, including model versioning, evaluation frameworks, prompt management, and drift/hallucination monitoring
• Drive responsible AI governance, including bias detection, explainability (SHAP, LIME), fairness auditing, and compliance with emerging AI regulations
• Evaluate and integrate vector databases (Pinecone, Weaviate, pgvector) and embedding strategies to power semantic search and knowledge retrieval
• Champion AI-assisted development practices (e.g., GitHub Copilot, Cursor) and foster an AI-augmented engineering culture across data teams
   

Data Analytics & Quant

• Drive advanced analytics, strategy, and Quant development
• Partner with stakeholders to translate complex business challenges into data-driven solutions
• Define and own key metrics, dashboards, and reporting frameworks to support executive and board-level decision-making
• Lead experimentation practices to validate business impact of models and initiatives
• Mentor teams, setting technical standards and career development paths
   

Requirements

• 7+ years of hands-on experience across Data Engineering, Data Science, Quant, Data Analytics, delivering end-to-end solutions
• 3+ years of managerial experience, leading data teams
• Bachelor’s or Master’s degree in Computer Science, Mathematics, Physics, Engineering, or a related field
• Strong programming skills in Python, with experience writing clean, production-grade code
• Solid understanding of software engineering best practices (CI/CD, testing, code reviews, clean architecture)
• Deep understanding of core ML algorithms: regression, gradient boosting, time series, etc.
• Practical experience with ML libraries and platforms (e.g., scikit-learn, XGBoost, TensorFlow, PyTorch)
• Strong foundation in mathematical statistics, probability theory, and quantitative modeling
• Proficient in SQL and experience with analytical and OLAP databases
• English Upper-Intermediate
   

Nice to Have

• Background in trading or fintech
• Experience analyzing and modeling time series or high-frequency data
• Familiarity with anti-fraud systems, risk modeling, or portfolio analytics
• Practical experience with integration of LLM with corporate systems for internal users
   

We offer

• 20 paid vacation days per year
• 10 paid sick leave days per year
• Public holidays according to current legislation
• Medical insurance
• Opportunity to work remotely
• Professional education budget
• Language learning budget
• Wellness budget (gym membership, sports gear and related expenses)