Senior Big Data Engineer: Scale TB Pipelines & Lakehouse

V2 Solutions; Hinoba-an; On-site; PHP 900,000 - 1,500,000; Full time

Job summary

V2 Solutions is seeking an experienced Data Engineer to design and maintain scalable data pipelines and data platforms. You will build robust ETL/ELT processes, model data for performance, and optimize cloud-based data workflows in Azure/AWS/GCP environments.

The ideal candidate brings 7–10 years in big data, strong Python and SQL skills, and hands-on Spark/Hadoop experience, enabling production TB-scale datasets and reliable data lakehouse architectures.

Qualifications

• 7–10 years of relevant experience in big data engineering.
• Advanced proficiency in Python.
• Strong SQL skills.
• Hands-on experience with Apache Spark, Hadoop, or similar distributed systems.
• Proven track record of handling large-scale datasets (TBs) in production environments.
• Cloud development experience with Azure (preferred), AWS, or GCP.
• Solid understanding of data lake and data lakehouse architectures.
• ETL performance tuning and cost optimization techniques.

Responsibilities

• Design, develop, and maintain scalable ETL/ELT pipelines for processing large volumes of data (TBs and beyond).
• Model and structure data for performance, scalability, and usability.
• Work with cloud infrastructure (Azure preferred) to build and optimize data workflows.
• Leverage distributed computing frameworks like Apache Spark and Hadoop for large-scale data processing.
• Build and manage data lake/lakehouse architectures in line with best practices.
• Optimize ETL performance and manage cost-effective data operations.
• Collaborate with data science, analytics, and software engineering teams.
• Ensure data quality, integrity, and security across all stages of the data lifecycle.

Skills

Python

SQL

Spark

Hadoop

Azure

AWS

GCP

Airflow

Azure Data Factory

Tools

Airflow

Azure Data Factory

Job description

V2 Solutions is seeking an experienced Data Engineer to design and maintain scalable data pipelines and data platforms. You will build robust ETL/ELT processes, model data for performance, and optimize cloud-based data workflows in Azure/AWS/GCP environments.

The ideal candidate brings 7–10 years in big data, strong Python and SQL skills, and hands-on Spark/Hadoop experience, enabling production TB-scale datasets and reliable data lakehouse architectures.