Remote Apache Impala Engineer for Big Data Analytics

BairesDev; Peru (IL); Sur place; USD 120 000 - 180 000; Plein temps

Avantages offerts par ce poste

100% remote

USD or local currency

Hardware and software setup for home

Flexible hours

Parental leaves

Diverse growth opportunities

Résumé du poste

BairesDev is hiring a Software Engineer specializing in Apache Impala to lead the implementation and optimization of interactive SQL analytics on Hadoop platforms. You will focus on delivering high-performance query execution across petabyte-scale data environments, ensuring the Cloudera ecosystem operates at peak efficiency.

You will design, optimize, and tune Impala deployments, troubleshoot issues, and apply best practices for data partitioning and storage formats to enhance query speeds.

Qualifications

• 4+ years in Software/Data Eng or Big Data infra.
• Experience running interactive SQL analytics on Hadoop with Apache Impala.
• Proficiency with Cloudera ecosystem and MPP SQL architectures.

Responsabilités

• Design and maintain production-grade Apache Impala implementations for interactive analytics.
• Optimize complex MPP SQL queries to achieve low-latency results on large-scale datasets.
• Configure and tune Impala components within Hadoop clusters for stability and performance.
• Troubleshoot distributed query execution issues and resolve performance bottlenecks.
• Implement best practices for data partitioning and storage formats to speed up queries.

Connaissances

4+ years exp

English fluency

SQL analytics

Outils

Apache Impala

Cloudera

MPP SQL

Description du poste

BairesDev is hiring a Software Engineer specializing in Apache Impala to lead the implementation and optimization of interactive SQL analytics on Hadoop platforms. You will focus on delivering high-performance query execution across petabyte-scale data environments, ensuring the Cloudera ecosystem operates at peak efficiency.

You will design, optimize, and tune Impala deployments, troubleshoot issues, and apply best practices for data partitioning and storage formats to enhance query speeds.