Senior Data Engineer
Summary
Build and scale data pipelines for a global hotel platform, processing raw data into revenue-driving insights using PySpark, AWS, and Kafka.
We are looking for strong engineers with solid experience in AWS, Spark/PySpark, data pipelines, and distributed data processing who are open to new opportunities and future project engagements.
Requirements
Must have
5+ years of commercial experience in Data Engineering
Strong experience with AWS
Hands-on experience with Spark / PySpark
Experience building and maintaining data pipelines and ETL/ELT processes
Experience with AWS S3
Experience with Kafka, Kinesis, or similar streaming technologies
Good knowledge of SQL and experience with PostgreSQL, MySQL, Redshift, or similar databases
Experience with DynamoDB or other NoSQL databases
Experience working with containerized applications, ideally AWS ECS / Fargate
Strong understanding of distributed data processing and scalable data architectures
Good English communication skills
Nice to have
AWS Glue
Amazon EMR
AWS Batch
AWS Step Functions
Apache Flink
Apache Beam
Cassandra / ScyllaDB
Experience with real-time data processing
Experience with cloud-based data platforms
What we’re looking for
Strong problem-solving and analytical skills
Ability to work independently and take ownership of technical tasks
Experience designing and improving data pipelines
Ability to work with large-scale datasets
Good communication and collaboration skills
Willingness to work on different international projects depending on your experience and expertise