Senior Data Engineer / Tech Lead (Spark)

Our requirements

• At least 5 years of commercial experience in Data Engineering or Big Data projects
• Strong programming skills in Python
• Very good knowledge of SQL
• Strong hands-on experience with Apache Spark and distributed data processing
• Practical experience with workflow orchestration tools, preferably Apache Airflow
• Experience with Apache Iceberg and/or modern lakehouse architectures
• Experience working with Docker and Kubernetes
• Good understanding of data modelling, data pipelines, and data processing architectures
• Experience working with relational databases and/or query engines such as PostgreSQL or Trino
• General understanding of cloud environments and cloud-based data solutions
• Ability to take ownership of technical solutions and contribute to architectural and technical decisions
• Experience supporting other engineers through technical guidance, knowledge sharing, or mentoring
• Ability to work independently and take ownership of project deliverables
• Strong communication and collaboration skills
• Fluent English (at least C1 level).
• Bachelor’s degree in technical or mathematical studies.

Optional

• Experience with an MLOps framework such as Kubeflow or MLFlow.
• Familiarity with Databricks and/or dbt.

Your responsibilities

• Design, develop, and maintain scalable data pipelines using Python, SQL, Spark, and Airflow
• Build and improve data processing solutions based on Apache Iceberg and modern lakehouse architectures
• Work with technologies such as PyArrow, PyIceberg, PostgreSQL, and Trino
• Take technical ownership of selected areas and contribute to technical and architectural decisions
• Combine hands-on development with technical leadership and knowledge sharing within the team
• Build and maintain containerized workloads using Docker and Kubernetes
• Ensure data pipelines are scalable, reliable, maintainable, and production-ready
• Collaborate with engineers and other stakeholders to understand business and technical requirements and translate them into effective solutions
• Contribute to engineering best practices, including code quality, testing, CI/CD, and automation
• Monitor, troubleshoot, and continuously improve existing data pipelines and platform components
• Use modern development practices, including AI-assisted development, to improve engineering efficiency

About the project

This is how we organize our work

Division of working time

• 80%

  New features
• 5%

  Maintenance / Bug fixing
• 5%

  Client support
• 5%

  Document writing
• 5%

  Meetings

Important:

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 a partnership with Databricks, which offers industry-leading training materials and certifications.
• Choose your preferred form of cooperation: B2B or a contract of mandate, and enjoy 20 fully paid days off.
• 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

• 1.
  Let's get to know each other (45 min)
• 2.
  Technical Interview (1 h)
• 3.
  Management Interview (1 h)

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