Senior Data Engineer / Tech Lead (Spark)
New
A
AddeptoData engineering
Workplace type: remote; Country code: PLFull-TimeSenior
Salary21,000 - 28,560 PLN per month
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Job Details
- Languages
- Fluent English (at least C1 level).
- Experience
- At least 4 years of commercial experience in Data Engineering or Big Data projects
- Required Skills
- DockerPostgreSQLPythonSQLApache AirflowKubernetesSparkData modeling
Requirements
- Have at least 4 years of commercial experience in Data Engineering or Big Data projects.
- Have strong programming skills in Python.
- Have very good knowledge of SQL.
- Have strong hands-on experience with Apache Spark and distributed data processing.
- Have practical experience with workflow orchestration tools, preferably Apache Airflow.
- Have experience with Apache Iceberg and/or modern lakehouse architectures.
- Have experience working with Docker and Kubernetes.
- Understand data modelling, data pipelines, and data processing architectures.
- Have experience with relational databases and/or query engines such as PostgreSQL or Trino.
- Have a general understanding of cloud environments and cloud-based data solutions.
- Be able to own technical solutions and contribute to architectural and technical decisions.
- Have experience providing technical guidance, knowledge sharing, or mentoring.
- Have a bachelor’s degree in technical or mathematical studies.
- Be fluent in English at least at C1 level.
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 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 stakeholders to translate business and technical requirements into solutions.
- Contribute to code quality, testing, CI/CD, and automation practices.
- Monitor, troubleshoot, and continuously improve existing data pipelines and platform components.
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