
Senior Data Engineer
Department:Data Engineer
Type:REMOTE
Region:EU
Location:Poland
Experience:Mid-Senior level
Estimated Salary:PLN90,000 - PLN130,000
Skills:
PYTHONKAFKAAPACHE FLINKAPACHE SPARKAPACHE HUDIAPACHE ICEBERGRDBMSPOSTGRESQLMYSQLS3GCSAWSGCPAZUREETLELTDATA MODELINGDATA QUALITY
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Job Description
Posted on: October 29, 2025
We are building a large real-time data pipeline to move data from an RDBMS to several destinations - datalake, search engine (e.g. OpenSearch). 300M+ records, 10Tb volume. Real-Time + Historical data load. Transformation and aggregations on the stream.
- Tech Stack:
Python
Kafka
Apache Flink / Apache Spark (Streaming)
Apache Hudi / Apache Iceberg
Requirements:Required skills:
- 5+ years of experience as a Data Engineer or similar role, with hands-on expertise in large-scale, production-grade data pipelines.
- Proven experience designing and running real-time data streaming systems (Kafka + Flink / Spark Streaming).
- Strong proficiency in Python for data engineering (data processing, orchestration, automation).
- Solid understanding of distributed systems, data partitioning, checkpointing, and fault-tolerant stream processing.
- Practical experience with Apache Hudi or Apache Iceberg for incremental data storage and schema evolution.
- Experience with RDBMS sources (PostgreSQL, MySQL, etc.) and data lakes / object storage (S3, GCS, etc.).
- Deep understanding of ETL / ELT design patterns, data modeling, and data quality principles.
- Experience deploying and maintaining data infrastructure in cloud environments (AWS / GCP / Azure).
- Excellent analytical and problem-solving skills, with the ability to design robust, scalable, and efficient architectures.
- Strong communication skills and ability to collaborate with cross-functional teams.
Responsibilities:
- Collaborate with business stakeholders and technical teams to understand and analyze data requirements
- Lead the design and implementation of data models and database structures that meet business needs
- Profile, refactor, and tune performance in the database
- Design and implement complex ETL processes to extract, transform, and load data from various source systems into the data warehouse
- Ensure data integrity, consistency, and accuracy through robust data quality assurance measures
- Review and support team members, providing guidance and mentorship
- Supervise and contribute to the data-driven strategy for the project, aligning it with business objectives
Originally posted on LinkedIn
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