Senior Data Engineer at Skillfield designing distributed data processing solutions using Apache Spark. Collaborates on cloud and on-prem solutions across enterprise levels in a hybrid work environment.
Responsibilities
Design, develop, and maintain ETL and ELT pipelines using Apache Spark (batch and streaming)
Build Spark applications in Scala, applying distributed processing best practices
Optimise Spark workloads to improve performance, scalability, and reliability
Work within the Hadoop ecosystem, including HDFS, Hive, and HBase
Design and support high-performance analytical solutions using ClickHouse
Build and manage data ingestion workflows using Apache NiFi
Operate and troubleshoot data platforms in Linux-based environments
Partner with data architects on solution design, schemas, and data models
Investigate and resolve data pipeline failures and performance issues
Maintain technical documentation and delivery artefacts in Confluence
Track delivery progress and work items using Jira
Requirements
Hands-on experience building solutions with Apache Spark
Strong Scala development capability
Experience working in Linux environments
Practical knowledge of HDFS, Hive, and HBase
Experience with ClickHouse or comparable analytical databases
A solid understanding of distributed systems and performance optimisation
Experience working across cloud, hybrid, or on-prem platforms
Familiarity with Git-based workflows and CI/CD pipelines
Nice to Have
Experience with Kafka or other streaming platforms
Exposure to Databricks, EMR, or managed Spark services
Experience with orchestration tools such as Airflow
Awareness of data security, identity management, and governance practices
Benefits
Enjoy flexibility, support, and a focus on sustainable delivery
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