Data Enginner

SUMMARY:
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POSITION INFO:

Job Description – Starburst Data Engineer 

Role Purpose 

We are seeking a Starburst Data Engineer to support and maintain an enterprise Starburst platform and assist with the migration of workloads from Apache Hive to Starburst. 

The role focuses on production support, troubleshooting, SQL query optimisation, platform stability, and helping users successfully run analytical workloads on Starburst. Strong SQL skills and Knowledge of Presto, Starburst or Trino are essential. 

Key Responsibilities 

• Assist with the migration of data workloads from Apache Hive to Starburst (Trino) 

• Investigate and resolve migration issues while providing support for production stability and operational continuity. 

• Monitor platform health, availability, query performance, and resource usage. 

• Investigate and resolve platform, connectivity, access, and SQL query issues. 

• Rewrite and optimize SQL queries for Starburst compatibility, maintainability, and query performance. 

• Optimize Starburst query performance through effective use of partitioning, file formats, caching, and related tuning techniques. 

• Troubleshoot slow or failed queries and recommend improvements. 

• Assess existing Hive schemas, queries, and pipelines for migration readiness. 

• Work with engineering, architecture, infrastructure, and business teams to resolve issues and improve platform performance. 

• Support platform upgrades, configuration changes, deployments, and operational improvements. 

• Maintain technical documentation, troubleshooting guides, and support procedures. 

• Participate in incident resolution and root-cause analysis. 

• Promote automation, monitoring, security, and operational best practices. 

Required Skills 

• Advanced SQL skills, including query optimization, complex joins, and window functions. 

• Understanding of partitioning, bucketing, indexing, and related data optimization strategies. 

• Strong debugging, troubleshooting, and performance tuning skills. 

• Experience with Apache Hive and distributed data processing environments. 

• Good to have Knowledge of Presto, Starburst or Trino. 

• Experience working with big data ecosystems such as HDFS, S3, and data lake architectures. 

• Knowledge of modern table for formats such as Parquet, ORC.  

• Knowledge of analytical file formats such as Parquet 

• Good to have knowledge of modern table formats such as Iceberg and Delta 

• Familiarity with cloud platforms such as AWS, Azure, or Google Cloud Platform. 

Preferred Skills 

• Experience supporting large-scale data platform modernization or migration initiatives. 

• Familiarity with performance benchmarking and workload optimization in distributed query environments. 

• Exposure to data governance, metadata management, and secure data access practices. 

• Ability to create clear technical documentation and communicate effectively with cross-functional teams. 

Professional Traits 

• Self-starter with strong ownership and accountability. 

• Strong support and customer-service mindset. 

• Disciplined, reliable, and highly committed to delivering quality work. 

• Strong team player with excellent collaboration and communication skills. 

• Quick learner with the ability to adapt to new technologies and environments. 

• Proactive approach to troubleshooting and problem-solving. 

• Able to work independently as well as in cross-functional teams. 

• Focused on continuous improvement, automation, and operational excellence. 

• Strong analytical and platform support mindset.