Expected, Python, SQL, Spark, Airflow, AWS, Iceberg, Django

Optional, Kubernetes, Kafka, NiFi, Trino, Hudi, Java, Scala, Docker, Databricks, Cloudera

About the project, As a Data Engineer, you will join a senior engineering team working on a greenfield data platform. You will be involved in building the solution end-to-end, combining strong backend engineering with data ingestion and data processing., , The project involves integrating data from multiple file-based and API sources into a modern cloud data warehouse, with a strong focus on data quality, reliability, scalability, and production readiness. We are also looking for talented engineers to join other exciting data projects, including:, , Development and maintenance of a large platform for processing automotive data. A significant amount of data is processed in both streaming and batch modes. The technology stack includes Spark, Cloudera, Airflow, Iceberg, Python, and AWS., , Design and development of a universal data platform for global aerospace companies. This Azure and Databricks powered initiative combines diverse enterprise and public data sources. The data platform is at the early stages of the development, covering design of architecture and processes as well as giving freedom for technology selection., , Centralized reporting platform for a growing US telecommunications company. This project involves implementing BigQuery and Looker as the central platform for data reporting. It focuses on centralizing data, integrating various CRMs, and building executive reporting solutions to support decision-making and business growth.

This is how we work, in house, at the client's site, you can change the project, you have influence on the choice of tools and technologies, you have influence on the technological solutions applied, you have influence on the product, you develop the code "from scratch", you focus on product development, agile, scrum

Team members, technical leader, big data developer, data scientist, project manager

Your responsibilities, Design and develop scalable data ingestion pipelines for file-based and API data sources using Python., Build and maintain backend components responsible for data processing, validation, and integration., Design and develop REST APIs using Python and Django., Implement robust data quality, validation, and error-handling mechanisms., Design and maintain data models and work with modern cloud data platforms and warehouses., Develop and maintain automated data-quality tests., Work with cloud services and workflow orchestration tools such as Airflow., Contribute to CI/CD pipelines and application environment configuration., Ensure solutions are reliable, maintainable, scalable, and production-ready., Write and maintain technical documentation and operational runbooks., Collaborate with engineers and stakeholders to translate business and technical requirements into effective solutions., Use AI-assisted development tools and workflows as part of day-to-day software delivery.

At least 4+ years of commercial experience in backend or data engineering, including work with production-grade data pipelines or Big Data systems., Proven hands-on experience with Snowflake as a modern cloud data platform., Strong programming skills in Python, including solid hands-on experience with Django., Hands-on experience designing and building data ingestion / ETL-ELT pipelines using both file-based and API data sources., Working knowledge of AWS, particularly S3 and Secrets Manager., Experience with workflow orchestration tools such as Airflow / AWS MWAA or equivalent., Strong understanding of data validation, data quality, error handling, and production reliability., Experience designing or working with REST APIs., Understanding of data security and compliance requirements, including PII handling, audit trails, and data retention policies., Experience using AI coding assistants or agentic workflows as part of day-to-day software development., Excellent communication skills and the ability to clearly document technical decisions for both engineering and operational stakeholders., Excellent English communication skills (C1 level), both written and spoken.

Optional, Experience with dbt or similar data transformation tools., Experience with Kafka or other streaming technologies., Familiarity with structured data-exchange formats., Experience with Databricks.

Division of working time, New features - 80%, Maintenance / Bug fixing - 5%, Client support - 5%, Document writing - 5%, Meetings - 5%

What we offer, Work in a supportive team of passionate enthusiasts of AI & Big Data., Engage with top-tier global enterprises and cutting-edge startups on international projects., Enjoy flexible work arrangements, allowing you to work remotely or from modern offices and coworking spaces., Accelerate your professional growth through career paths, knowledge-sharing initiatives, language classes, and sponsored training or conferences, including partnerships with Databricks and Anthropic, which offer industry-leading training materials and certifications., Participate in team-building events and utilize the integration budget., Celebrate work anniversaries, birthdays, and milestones., Access medical and sports packages, eye care, and well-being support services, including psychotherapy and coaching., Get full work equipment for optimal productivity, including a laptop and other necessary devices., With our backing, you can boost your personal brand by speaking at conferences, writing for our blog, or participating in meetups., Experience a smooth onboarding with a dedicated buddy, and start your journey in our friendly, supportive, and autonomous culture.

Development opportunities we offer, assistance in preparation to public speeches, conferences abroad, conferences in Poland, development budget, external training, industry-specific e-learning platforms, intracompany training, soft skills training, substantive support from technological leaders, support of IT events, technical knowledge exchange within the company, time for development of your ideas

Benefits, sharing the costs of sports activities, private medical care, sharing the costs of foreign language classes, sharing the costs of professional training & courses, remote work opportunities, flexible working time, fruits, integration events, no dress code, video games at work, birthday celebration, employee referral program, Reimbursement for prescription glasses or contact lenses

Recruitment stages, Let's get to know each other (45 min), Technical Interview (1 h), Management Interview (1 h)

Important: , Addepto may publish job opportunities on external job boards, but all applications are collected and processed through our official recruitment system: Recruitee, , Please make sure that any further recruitment communication you receive comes from an official Addepto recruitment channel. If you receive a job offer, interview invitation, or recruitment email from an unofficial or unverified source, please be cautious, as it may not come from Addepto.

Addepto, Addepto is a leading AI consulting ( and data engineering ( company that builds scalable, ROI-focused AI solutions for some of the world's largest enterprises and pioneering startups, including Rolls Royce, Continental, Porsche, ABB, and WGU. With an exclusive focus on Artificial Intelligence and Big Data, Addepto helps organizations unlock the full potential of their data through systems designed for measurable business impact and long-term growth., , The company's work extends beyond client engagements. Drawing from real-world challenges and insights, Addepto has developed its own product - ContextClue - and actively contributes open-source solutions to the AI community. This commitment to transforming practical experience into scalable innovation has earned Addepto recognition by Forbes as one of the top 10 AI consulting companies worldwide., , As part of KMS Technology, a US-based global technology group, Addepto combines deep AI specialization with enterprise-scale delivery capabilities—enabling the partnership to move clients from AI experimentation to production impact, securely and at scale.

Data Engineer (Snowflake)

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