Lead AWS Data Engineer - Scalable Data Pipelines (Remote)

Lingaro Group Philippines; Manila; Hybrid; PHP 1,004,000 - 1,451,000; Full time

Benefits offered by this job

Workation program

Udemy learning platform access

Buddy onboarding & internal training

Promotions from within

Flexible hours

Job summary

Lingaro Group Philippines is seeking a seasoned Data Engineer to design and maintain scalable data pipelines using Python, SQL, and DBT. The role emphasizes building reliable data models, leveraging Iceberg, and optimizing Spark/Athena workloads on AWS.

The successful candidate will collaborate with product and data stakeholders, implement CI/CD and IaC practices, and contribute to observability and governance across data platforms.

Qualifications

• 4–6 years of experience as a Data Engineer.
• Experience designing scalable, reliable data pipelines.
• Strong Python-based data pipeline development skills.
• Strong SQL and data modeling expertise.
• Familiarity with DBT, Airflow, and Spark environments.
• Experience with AWS data services (Athena, Lambda, Glue, SageMaker).
• Clear communication with engineers and stakeholders.
• Fluency in English.

Responsibilities

• Modify Lambda functions, SQL queries, and processing jobs to add features.
• Refactor code to ingest/process external data.
• Add quality checks to existing pipelines.
• Design data models leveraging Iceberg format for silver and gold layers.
• Optimize queries for performance.
• Apply data validation rules.
• Build automated quality checks.
• Document the data preparation process with transformations and code comments.
• Store all code in GitLab with meaningful commit messages and versioning.

Skills

Data pipelines

Python

SQL

DBT

Airflow

Iceberg

AWS

Data modeling

Testing

CI/CD

IaC

Observability

Communication

Fluent English

Tools

DBT

Airflow

Iceberg

Athena

Spark

Lambda

Aurora

EventBridge

Glue

SageMaker

Job description

Lingaro Group Philippines is seeking a seasoned Data Engineer to design and maintain scalable data pipelines using Python, SQL, and DBT. The role emphasizes building reliable data models, leveraging Iceberg, and optimizing Spark/Athena workloads on AWS.

The successful candidate will collaborate with product and data stakeholders, implement CI/CD and IaC practices, and contribute to observability and governance across data platforms.