Data Engineer

Software Mind

full-time

Posted on: 10/2/2025

Location Type: Remote

Location: Remote • 🇵🇱 Poland

✨ AI Apply

Mid-LevelSenior

AirflowAmazon RedshiftApacheAWSAzureBigQueryCloudETLGoogle Cloud PlatformHadoopJavaKafkaNoSQLPythonScalaSparkSQL

About the role

The Data Engineer will be responsible for building, maintaining, and optimizing the data pipelines and architectures that power International SOS's mission-critical analytics and operational platforms.
Design, construct, install, and maintain scalable and robust data pipelines
Integrate data from a wide variety of sources, both structured and unstructured
Optimize data delivery and re-design infrastructure for greater scalability and performance
Collaborate with data scientists, business analysts, and product managers to deliver data solutions aligned with business needs
Develop and maintain data models, databases, and ETL processes
Ensure data quality, reliability, and integrity across systems
Participate in data architecture and design reviews
Assist in implementing data governance and data security best practices
Monitor and troubleshoot data pipeline issues and performance bottlenecks

6+ years of professional experience in data engineering or similar roles
Proficiency in SQL and experience with relational and NoSQL databases
Strong programming skills in Python, Scala, or Java
Experience with big data tools such as Spark, Hadoop, Kafka
Familiarity with cloud data platforms (AWS, Azure, GCP)
Hands-on experience with data pipeline orchestration tools (e.g., Apache Airflow, DBT)
Knowledge of data warehousing concepts and tools (e.g., Snowflake, Redshift, BigQuery)
Understanding of data privacy regulations and security standards
Strong problem-solving and communication skills
Bachelor’s degree in Computer Science, Engineering or related field
Required Languages: English to a very high standard written and oral

Benefits

Tip: use these terms in your resume and cover letter to boost ATS matches.

SQLPythonScalaJavaSparkHadoopKafkadata pipeline orchestrationdata warehousingETL processes

problem-solvingcommunicationcollaboration