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We are seeking a Senior Data / Big Data Engineer for a banking project to deliver complex solutions, guide the platform's data strategy, define standards, and support team development.
Job Responsibility:
Design and develop custom data pipelines for batch and near-real-time processing
Ingest data from diverse sources and debug platform/application errors
Optimize performance over Avro and Parquet on HDFS, including partitioning and bucketing
Debug Spark and Impala sessions (SHS, Impala)
Design secure data solutions following security-by-design principles
Monitor Big Data applications using Kafka, InfluxDB, Grafana
Perform DevOps tasks: CI/CD with Jenkins, version control with Git/SVN
Create documentation and standardize procedures
Mentor junior colleagues and transfer technical know-how
Contribute to the long-term data strategy of the platform
Requirements:
Strong experience with the Cloudera Hadoop stack: HDFS, Hive Metastore, Impala, Spark
Advanced SQL skills and scripting experience in Bash, Python, PowerShell
Experience in Linux production environments
Familiarity with Airflow, Informatica, NiFi
Proven ability to independently design complex data solutions
Communicative, systematic, and responsible with strong team collaboration skills
Nice to have:
Experience with Databricks – Data Engineering
Exposure to Azure Data Stack (Data Factory, ADLS, Synapse, etc.)