Data Engineer

Overview

We are seeking an experienced Data Platform Engineer to design, build, optimize, and support modern analytics platforms and lakehouse solutions. You will play a key role in developing scalable data pipelines, optimizing distributed query workloads, and supporting enterprise analytics platforms across a high-performance data ecosystem.

Key Responsibilities

• Design, develop, and optimize enterprise data platforms and analytics solutions.
• Build and maintain scalable data pipelines and lakehouse architectures.
• Support and optimize MPP query engines, data warehouses, and distributed processing environments.
• Drive performance tuning, platform modernization, and workload optimization initiatives.
• Collaborate with architects, analysts, and engineering teams to deliver reliable and scalable data solutions.
• Support platform automation, CI/CD, governance, and operational best practices.
• Troubleshoot complex data platform issues and ensure operational excellence.

General Qualifications

• Bachelor's Degree in Computer Science, Information Technology, Data Engineering, or a related discipline.
• 7-8+ years of experience in Data Engineering, Analytics Engineering, Data Platforms, or Big Data ecosystems.
• Experience working in enterprise-scale analytics and data environments.

Mandatory Skills

• Hands-on experience with Apache Doris (or similar MPP platforms such as StarRocks, ClickHouse, or Greenplum).
• Advanced SQL development and query optimization skills.
• Strong understanding of Apache Doris architecture, data models, partitioning, and performance tuning.
• Experience with Apache Iceberg, Delta Lake, or Apache Hudi.
• Experience with Snowflake and/or Apache Spark.
• Hands-on experience with Trino, PrestoSQL, or Presto.
• Solid knowledge of MPP/distributed query processing, performance optimization, and data architecture concepts.
• Experience working with cloud object storage, Parquet, and ORC file formats.
• Proficiency in Python, Java, or Scala.
• Experience with Git and CI/CD pipelines for data platforms.

Nice-to-Have Skills

• Experience with modern lakehouse architectures and data mesh concepts.
• Cloud platform experience (AWS, Azure, or GCP).
• Data warehouse and analytics platform migration projects.
• Infrastructure automation and DevOps practices.
• Real-time analytics and streaming technologies.