Senior Data Engineer (Big Data & Cloud ETL)

Posted 12 days agoViewed

💎 Seniority level: Senior, 6+ years

📍 Location: European Union

🔍 Industry: Software Development

🏢 Company: SPACE44

⏳ Experience: 6+ years

🪄 Skills: AWSPythonSQLApache AirflowCloud ComputingETLKafkaMongoDBSnowflakeCassandraData engineeringData modelingScripting

Minimum 6 years of experience as a Data Engineer working with large-scale data architectures
Strong expertise in SQL for data manipulation, optimization, and analytics
Advanced proficiency in Python for ETL, scripting, and data automation
In-depth experience with Apache Spark for big data processing and distributed computing
Proven experience with Kafka for real-time data streaming and event processing
Hands-on experience with cloud-native ETL tools such as AWS Glue and Azure Data Factory
Familiarity with data warehousing platforms like Snowflake or BigQuery
Knowledge of NoSQL databases like MongoDB or Cassandra
Comfortable working in modern cloud environments and Agile remote teams
BSc in Computer Science, Data Engineering, or a relevant field

Design, build, and manage ETL/ELT pipelines using tools like AWS Glue, Azure Data Factory, and Apache Airflow
Develop scalable real-time and batch data processing solutions using Apache Spark and Kafka
Write optimized, production-grade SQL queries and perform performance tuning across data systems
Build and maintain data lakes and warehouses, including platforms like Snowflake and BigQuery
Work with structured and semi-structured data across relational and NoSQL databases (e.g., MongoDB, Cassandra)
Collaborate with data analysts, engineers, and product teams to define data models and architecture
Ensure data integrity, quality, and lineage throughout the pipeline
Automate workflows, testing, and deployment for data systems in cloud-native environments
Monitor and troubleshoot pipeline performance and reliability