Senior Data Engineer - Remote/Hybrid, Snowflake & AI Pipelines

APPLY

Philippines

Hybrid

PHP 900,000 - 1,800,000

Full time

14 days+

Application generator

Stand out for this role — generate a tailored resume and cover letter in about a minute.

Get past ATS filters

Benefits offered by this job

Generous vacation policy

Flexible work arrangements

Training budget and AI upskilling

Job summary

APPLY is seeking a Senior Data Engineer to design, build, and optimize scalable data pipelines and cloud data warehouses. You will collaborate with cross-functional teams to enable analytics, reinforce governance, and drive AI-enabled data initiatives.

The role involves hands-on work with Snowflake, BigQuery, Python, and dbt in a hybrid/remote-friendly setup across North and Latin America. Strong English communication and 5+ years of experience are required.

Qualifications

5+ years of experience in data engineering building modern cloud-based data platforms.
Strong hands-on experience with Snowflake including performance tuning, security, and data modeling.
Advanced SQL skills for analytics engineering and data transformation.
Proficiency in Python for data processing, automation, and orchestration.
Experience with dbt or similar analytics engineering frameworks.
Familiarity with orchestration tools such as Dagster or Apache Airflow.
Experience enabling ML/AI-driven use cases on top of data platforms.
Solid understanding of data privacy, governance, and compliance best practices.
Excellent English communication and collaboration skills.

Responsibilities

Design, build, and maintain scalable data pipelines and architectures to support analytical and operational workloads.
Develop and optimize ETL/ELT pipelines, ensuring efficient data extraction, transformation, and loading from various sources.
Work closely with backend and platform engineers to integrate data pipelines into cloud-native applications.
Manage and optimize cloud data warehouses, primarily BigQuery, ensuring performance, scalability, and cost efficiency.
Implement data governance, security, and privacy best practices, ensuring compliance with company policies and regulations.
Collaborate with analytics teams to define data models and enable self-service reporting and BI capabilities.
Develop and maintain data documentation, including data dictionaries, lineage tracking, and metadata management.
Monitor, troubleshoot, and optimize data pipelines, ensuring high availability and reliability.
Stay up to date with emerging data engineering technologies and best practices, continuously improving our data infrastructure.