Data Engineer: Pipelines, Insights & Hybrid Work

Pronet Gaming; Taguig; Hybrid; PHP 900,000 - 1,200,000; Full time

Benefits offered by this job

HMO + 1 dependent

Annual Wellness Bonus

Performance Bonus

20 Vacation Days

10 Sick Days

Birthday Day Off

Referral bonuses

Training & development

Hybrid work - 2 days WFH / 3 days in/0

Job summary

Pronet Gaming in the Philippines is seeking a Data Engineer who enjoys turning data into actionable insights and building scalable pipelines. You will collect, store, process, and analyze datasets, selecting the best tools and ensuring seamless integration into our architecture.

You will monitor data quality, contribute dashboards for stakeholders, and help expand our streaming and batch processing capabilities using Spark and related technologies.

Qualifications

• Solid foundation in object-oriented design and development.
• Unix/Linux systems and shell scripting.
• Java/Scala programming.
• Building and consuming RESTful APIs.
• SQL and NoSQL databases; data modeling and trade-offs.
• Columnar, distributed, and row-based databases management.
• Strong research to apply best practices.
• Passion for improving systems and exploring new tech.
• Proactive, self-motivated and results-focused.
• Excellent English communication skills, both written and spoken.
• Experience with open-source big data technologies (Hadoop/HBase/Hive/Kafka/Storm) is a plus.
• Familiarity with streaming architectures is a plus.

Responsibilities

• Monitor and improve data quality and reliability.
• Develop insightful reports and dashboards for stakeholders.
• Build and maintain scalable data pipelines using Spark.

Skills

Object-oriented design

Unix/Linux

Java/Scala

RESTful APIs

SQL/NoSQL

Data modeling

Big data concepts

English communication

Big data techs (Hadoop/HBase/Hive/Kafa

Tools

Spark

Job description

Pronet Gaming in the Philippines is seeking a Data Engineer who enjoys turning data into actionable insights and building scalable pipelines. You will collect, store, process, and analyze datasets, selecting the best tools and ensuring seamless integration into our architecture.

You will monitor data quality, contribute dashboards for stakeholders, and help expand our streaming and batch processing capabilities using Spark and related technologies.