Data Engineer: AWS ETL Pipelines & Data Lake

Relx Plc; Manila; On-site; PHP 600,000 - 900,000; Full time

Job summary

Relx plc in Manila is hiring a Data Engineer to develop, test, and maintain ETL/ELT pipelines ingesting data from GA4, paid media, social media, and other platforms. You will build API and batch ingestion workflows, integrate data into an AWS data lake, and ensure data quality and governance.

The role requires 2–5 years in data engineering, strong SQL/Python skills, and hands-on AWS experience. Collaboration with engineers and analysts across a global business is essential.

Qualifications

• Bachelor’s degree in Engineering, CS, IT or related field.
• 2–5 years in data engineering or related roles.
• Proficient in SQL and Python.
• Experience building ETL/ELT pipelines.
• Experience with AWS or other cloud data platforms.
• Familiar with JSON, CSV, Parquet formats.
• Git, PRs, testing and deployment workflows.
• Able to collaborate across global teams.

Responsibilities

• Develop, test, and maintain ETL/ELT pipelines.
• Build API and batch-ingestion workflows with pagination and retries.
• Integrate marketing and engagement data into AWS data lake.
• Transform data into consistent, reusable datasets with standards.
• Monitor pipelines and troubleshoot data quality and performance issues.
• Collaborate with Sr. Engineers and stakeholders to translate requirements into tasks.
• Implement data-governance, privacy, access, and retention rules.
• Participate in Agile planning, estimation, and retrospectives.

Skills

SQL

Python

ETL/ELT

Data pipelines

Data quality

Git workflows

Communication

Education

Bachelor's degree in Engineering/CS/IT or related

Tools

AWS

S3

Glue

Athena

CloudWatch

Databricks

PySpark

Airflow

PostgreSQL

MS SQL Server

Job description

Relx plc in Manila is hiring a Data Engineer to develop, test, and maintain ETL/ELT pipelines ingesting data from GA4, paid media, social media, and other platforms. You will build API and batch ingestion workflows, integrate data into an AWS data lake, and ensure data quality and governance.

The role requires 2–5 years in data engineering, strong SQL/Python skills, and hands-on AWS experience. Collaboration with engineers and analysts across a global business is essential.